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The Journal of Pathology Jul 2022Breast cancer affects one in seven women worldwide during their lifetime. Widespread mammographic screening programs and education campaigns allow for early detection of... (Review)
Review
Breast cancer affects one in seven women worldwide during their lifetime. Widespread mammographic screening programs and education campaigns allow for early detection of the disease, often during its asymptomatic phase. Current practice in treatment and recurrence monitoring is based primarily on pathological evaluations but can also encompass genomic evaluations, both of which focus on the primary tumor. Although breast cancer is one of the most studied cancers, patients still recur at a rate of up to 15% within the first 10 years post-surgery. Local recurrence was originally attributed to tumor cells contaminating histologically normal (HN) tissues beyond the surgical margin, but advances in technology have allowed for the identification of distinct aberrations that exist in the peri-tumoral tissues themselves. One leading theory to explain this phenomenon is the field cancerization theory. Under this hypothesis, tumors arise from a field of molecularly altered cells that create a permissive environment for malignant evolution, which can occur with or without morphological changes. The traditional histopathology paradigm dictates that molecular alterations are reflected in the tissue phenotype. However, the spectrum of inter-patient variability of normal breast tissue may obfuscate recognition of a cancerized field during routine diagnostics. In this review, we explore the concept of field cancerization focusing on HN peri-tumoral tissues: we present the pathological and molecular features of field cancerization within these tissues and discuss how the use of peri-tumoral tissues can affect research. Our observations suggest that pathological and molecular evaluations could be used synergistically to assess risk and guide the therapeutic management of patients. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.
Topics: Breast; Breast Neoplasms; Early Detection of Cancer; Female; Humans; United Kingdom
PubMed: 35362092
DOI: 10.1002/path.5902 -
Pathologica Apr 2022Phyllodes tumors (PT) are fibroepithelial neoplasms of the breast showing a peculiar leaf-like appearance. They account for 0.3 to 1% of all primary breast tumors and... (Review)
Review
Phyllodes tumors (PT) are fibroepithelial neoplasms of the breast showing a peculiar leaf-like appearance. They account for 0.3 to 1% of all primary breast tumors and 2.5% of all fibroepithelial breast tumors. PT are classified into benign, borderline and malignant based upon their stromal morphology with a distribution of 60%, 20%, and 20%, respectively. Malignant PT of the breast constitute an uncommon challenging group of fibroepithelial neoplasms. They have a relatively high tendency to recur, although distant metastasis is uncommon, and nearly exclusive to malignant PT. Adequate surgical resection remains the standard approach to achieve maximal local control. Giant malignant PT are rare and a pose a diagnostic dilemma for pathologists, especially when comprised of sarcomatous elements. This review highlights the morphological features of PT detected in cytology and histology specimens and discusses diagnostic pitfalls and differential diagnosis.
Topics: Breast; Breast Neoplasms; Female; Humans; Neoplasm Recurrence, Local; Neoplasms, Fibroepithelial; Phyllodes Tumor
PubMed: 35414723
DOI: 10.32074/1591-951X-754 -
Deutsches Arzteblatt International Aug 2019Most clinical breast changes in women are benign; in only 3% to 6% of cases are they due to breast cancer. How- ever, there is a lack of up-to-date, evidence-based... (Review)
Review
BACKGROUND
Most clinical breast changes in women are benign; in only 3% to 6% of cases are they due to breast cancer. How- ever, there is a lack of up-to-date, evidence-based treatment recommendations for the various benign differential diagnoses.
METHODS
Selective literature search of PubMed from 1985 to May 2019, including current national (AWMF, Arbeitsgemeinschaft der Wissenschaftlichen Medizinischen Fachgesellschaften [Association of Scientific Medical Societies in Germany]) and inter- national guidelines.
RESULTS
Mastalgia and fibrocystic changes are common (around 50% of all women over the age of 30). Fibroadenomas occur in 25% of women; they are the most common benign tumors of the breast and do not require treatment. With most benign breast changes the risk of dedifferentiation is very low. However, it is important in the differential diagnosis to distinguish between such benign changes and breast cancer or changes that carry a risk of malignancy. Complex cysts, for example, carry a risk of malig- nancy of 23% to 31%, papillary lesions 16% , and radial scars 7%. Where there is doubt, histological confirmation should be sought by means of percutaneous biopsy.
CONCLUSION
Benign breast changes can be definitively distinguished from malignant lesions through the selective use of avail- able diagnostic investigations and interdisciplinary collaboration. When lesions of uncertain malignant potential are found (B3 in the biopsy classification), complete excision is indicated. Prospective studies on the early diagnosis of breast cancer in lesions carrying a risk of malignancy are desirable.
Topics: Breast; Breast Neoplasms; Diagnosis, Differential; Female; Germany; Humans
PubMed: 31554551
DOI: 10.3238/arztebl.2019.0565 -
Military Medical Research Apr 2022Granulomatous lobular mastitis (GLM) is a rare and chronic benign inflammatory disease of the breast. Difficulties exist in the management of GLM for many front-line...
Granulomatous lobular mastitis (GLM) is a rare and chronic benign inflammatory disease of the breast. Difficulties exist in the management of GLM for many front-line surgeons and medical specialists who care for patients with inflammatory disorders of the breast. This consensus is summarized to establish evidence-based recommendations for the management of GLM. Literature was reviewed using PubMed from January 1, 1971 to July 31, 2020. Sixty-six international experienced multidisciplinary experts from 11 countries or regions were invited to review the evidence. Levels of evidence were determined using the American College of Physicians grading system, and recommendations were discussed until consensus. Experts discussed and concluded 30 recommendations on historical definitions, etiology and predisposing factors, diagnosis criteria, treatment, clinical stages, relapse and recurrence of GLM. GLM was recommended as a widely accepted definition. In addition, this consensus introduced a new clinical stages and management algorithm for GLM to provide individual treatment strategies. In conclusion, diagnosis of GLM depends on a combination of history, clinical manifestations, imaging examinations, laboratory examinations and pathology. The approach to treatment of GLM should be applied according to the different clinical stage of GLM. This evidence-based consensus would be valuable to assist front-line surgeons and medical specialists in the optimal management of GLM.
Topics: Breast; Consensus; Female; Granulomatous Mastitis; Humans; Recurrence
PubMed: 35473758
DOI: 10.1186/s40779-022-00380-5 -
Clinical Imaging Jan 2021Contrast-enhanced mammography (CEM) combines conventional mammography with iodinated contrast material to improve cancer detection. CEM has comparable performance to... (Review)
Review
Contrast-enhanced mammography (CEM) combines conventional mammography with iodinated contrast material to improve cancer detection. CEM has comparable performance to breast MRI without the added cost or time of conventional MRI protocols. Thus, this technique may be useful for indications previously reserved for MRI, such as problem-solving, determining disease extent in patients with newly diagnosed cancer, monitoring response to neoadjuvant therapy, evaluating the posttreatment breast for residual or recurrent disease, and potentially screening in women at intermediate- or high-risk for breast cancer. This article will provide a comprehensive overview on the past, present, and future of CEM, including its evolving role in the diagnostic and screening settings.
Topics: Breast; Breast Neoplasms; Contrast Media; Female; Humans; Magnetic Resonance Imaging; Mammography; Sensitivity and Specificity
PubMed: 33032103
DOI: 10.1016/j.clinimag.2020.09.003 -
Breast (Edinburgh, Scotland) Feb 2020Diagnosis of early invasive breast cancer relies on radiology and clinical evaluation, supplemented by biopsy confirmation. At least three issues burden this approach:... (Review)
Review
Diagnosis of early invasive breast cancer relies on radiology and clinical evaluation, supplemented by biopsy confirmation. At least three issues burden this approach: a) suboptimal sensitivity and suboptimal positive predictive power of radiology screening and diagnostic approaches, respectively; b) invasiveness of biopsy with discomfort for women undergoing diagnostic tests; c) long turnaround time for recall tests. In the screening setting, radiology sensitivity is suboptimal, and when a suspicious lesion is detected and a biopsy is recommended, the positive predictive value of radiology is modest. Recent technological advances in medical imaging, especially in the field of artificial intelligence applied to image analysis, hold promise in addressing clinical challenges in cancer detection, assessment of treatment response, and monitoring disease progression. Radiomics include feature extraction from clinical images; these features are related to tumor size, shape, intensity, and texture, collectively providing comprehensive tumor characterization, the so-called radiomics signature of the tumor. Radiomics is based on the hypothesis that extracted quantitative data derives from mechanisms occurring at genetic and molecular levels. In this article we focus on the role and potential of radiomics in breast cancer diagnosis and prognostication.
Topics: Artificial Intelligence; Biopsy; Breast; Breast Neoplasms; Early Detection of Cancer; Female; Humans; Image Interpretation, Computer-Assisted; Machine Learning; Magnetic Resonance Imaging; Mammography; Prognosis; Ultrasonography, Mammary; Workflow
PubMed: 31739125
DOI: 10.1016/j.breast.2019.10.018 -
Developmental Cell Jun 2022The breast is a dynamic organ whose response to physiological and pathophysiological conditions alters its disease susceptibility, yet the specific effects of these...
The breast is a dynamic organ whose response to physiological and pathophysiological conditions alters its disease susceptibility, yet the specific effects of these clinical variables on cell state remain poorly annotated. We present a unified, high-resolution breast atlas by integrating single-cell RNA-seq, mass cytometry, and cyclic immunofluorescence, encompassing a myriad of states. We define cell subtypes within the alveolar, hormone-sensing, and basal epithelial lineages, delineating associations of several subtypes with cancer risk factors, including age, parity, and BRCA2 germline mutation. Of particular interest is a subset of alveolar cells termed basal-luminal (BL) cells, which exhibit poor transcriptional lineage fidelity, accumulate with age, and carry a gene signature associated with basal-like breast cancer. We further utilize a medium-depletion approach to identify molecular factors regulating cell-subtype proportion in organoids. Together, these data are a rich resource to elucidate diverse mammary cell states.
Topics: Animals; Breast; Breast Neoplasms; Female; Humans; Mammary Glands, Animal; Pregnancy; Proteomics; Transcriptome
PubMed: 35617956
DOI: 10.1016/j.devcel.2022.05.003 -
Nature Protocols Apr 2021Organoid technology has revolutionized the study of human organ development, disease and therapy response tailored to the individual. Although detailed protocols are...
Organoid technology has revolutionized the study of human organ development, disease and therapy response tailored to the individual. Although detailed protocols are available for the generation and long-term propagation of human organoids from various organs, such methods are lacking for breast tissue. Here we provide an optimized, highly versatile protocol for long-term culture of organoids derived from either normal human breast tissues or breast cancer (BC) tissues, as well as culturing conditions for a panel of 45 biobanked samples, including BC organoids covering all major disease subtypes (triple-negative, estrogen receptor-positive/progesterone receptor-positive and human epidermal growth receptor 2-positive). Additionally, we provide methods for genetic manipulation by Lipofectamine 2000, electroporation or lentivirus and subsequent organoid selection and clonal culture. Finally, we introduce an optimized method for orthotopic organoid transplantation in mice, which includes injection of organoids and estrogen pellets without the need for surgery. Organoid derivation from tissue fragments until the first split takes 7-21 d; generation of genetically manipulated clonal organoid cultures takes 14-21 d; and organoid expansion for xenotransplantation takes >4 weeks.
Topics: Animals; Biological Specimen Banks; Breast; Breast Neoplasms; Cell Culture Techniques; Clone Cells; Female; Genetic Techniques; Humans; Mice; Organoids; Time Factors; Transplantation, Heterologous
PubMed: 33692550
DOI: 10.1038/s41596-020-00474-1 -
Nature Communications Mar 2020Accurate identification of axillary lymph node (ALN) involvement in patients with early-stage breast cancer is important for determining appropriate axillary treatment...
Accurate identification of axillary lymph node (ALN) involvement in patients with early-stage breast cancer is important for determining appropriate axillary treatment options and therefore avoiding unnecessary axillary surgery and complications. Here, we report deep learning radiomics (DLR) of conventional ultrasound and shear wave elastography of breast cancer for predicting ALN status preoperatively in patients with early-stage breast cancer. Clinical parameter combined DLR yields the best diagnostic performance in predicting ALN status between disease-free axilla and any axillary metastasis with areas under the receiver operating characteristic curve (AUC) of 0.902 (95% confidence interval [CI]: 0.843, 0.961) in the test cohort. This clinical parameter combined DLR can also discriminate between low and heavy metastatic burden of axillary disease with AUC of 0.905 (95% CI: 0.814, 0.996) in the test cohort. Our study offers a noninvasive imaging biomarker to predict the metastatic extent of ALN for patients with early-stage breast cancer.
Topics: Adult; Aged; Aged, 80 and over; Axilla; Breast; Breast Neoplasms; Deep Learning; Elasticity Imaging Techniques; Female; Humans; Image Processing, Computer-Assisted; Lymph Node Excision; Lymph Nodes; Lymphatic Metastasis; Mastectomy; Middle Aged; Neoplasm Staging; Preoperative Period; Prognosis; Prospective Studies; ROC Curve; Reference Standards; Ultrasonography
PubMed: 32144248
DOI: 10.1038/s41467-020-15027-z -
Neoplasia (New York, N.Y.) Dec 2020The cellular heterogeneity of breast cancers still represents a major therapeutic challenge. The latest genomic studies have classified breast cancers in distinct... (Review)
Review
The cellular heterogeneity of breast cancers still represents a major therapeutic challenge. The latest genomic studies have classified breast cancers in distinct clusters to inform the therapeutic approaches and predict clinical outcomes. The mammary epithelium is composed of luminal and basal cells, and this seemingly hierarchical organization is dependent on various stem cells and progenitors populating the mammary gland. Some cancer cells are conceptually similar to the stem cells as they can self-renew and generate bulk populations of nontumorigenic cells. Two models have been proposed to explain the cell of origin of breast cancer and involve either the reprogramming of differentiated mammary cells or the dysregulation of mammary stem cells or progenitors. Both hypotheses are not exclusive and imply the accumulation of independent mutational events. Cancer stem cells have been isolated from breast tumors and implicated in the development, metastasis, and recurrence of breast cancers. Recent advances in single-cell sequencing help deciphering the clonal evolution within each breast tumor. Still, few clinical trials have been focused on these specific cancer cell populations.
Topics: Animals; Breast Neoplasms; Disease Models, Animal; Disease Susceptibility; Female; Humans; Incidence; Mammary Glands, Human; Mice; Neoplasm Staging; Neoplastic Stem Cells; Risk Assessment; Stem Cells
PubMed: 33142233
DOI: 10.1016/j.neo.2020.09.009