Breast Cancer Research Articles

NIMG-31. CASE REPORT: DIAGNOSIS OF AN INFILTRATIVE GLIOMA IN A LI-FRAUMENI SYNDROME PATIENT OBSCURED BY LESION RESPONSIVENESS TO NSCLC TREATMENT

Abstract Li-Fraumeni syndrome is a rare, autosomal dominant disorder linked to germline mutations of the TP53 suppressor gene. Patients with this syndrome are predisposed to various malignancies and a variety of brain tumors to include choroid plexus carcinoma, medulloblastoma, and glioma. We present a 46-year-old woman with a history of Li-Fraumeni syndrome which manifested with multiple systemic malignancies including breast cancer, ovarian teratoma, and leiomyosarcoma. The patient had been undergoing MRI brain surveillance since 2018, which was initially notable for a right cerebellar midline focus of enhancement associated with slowly evolving right middle cerebellar peduncle FLAIR signal, with no detectable neurologic symptoms. She underwent systemic therapy for non-small cell lung cancer (NSCLC) with pemetrexed/cisplatin. Her next MRI brain in August 2023 showed resolution of the cerebellar enhancement with small residual FLAIR signal. In April 2024, the patient presented with new neurologic symptoms to include ataxia, dizziness, difficulty swallowing, and memory loss. Repeat MRI brain revealed new infiltrative FLAIR signal throughout the right temporal lobe extending from the posterior fossa, contiguous with the previously seen cerebellar findings and consistent with infiltrative glioma. Due to fragmented records and care in multiple systems, her updated MRI initially created a diagnostic challenge with a radiographic interpretation of likely encephalitis. This is a unique case documenting a middle-aged female with Li-Fraumeni syndrome, followed for multiple cancers, presenting with new neurologic symptoms and progressive infiltrative FLAIR changes spanning from the cerebellum into the right temporal lobe. These findings highlight the natural history of a TP53 deficient tumor that ostensibly responded to a cisplatin-based regimen given for a different indication, thereby delaying time to symptom onset and need for biopsy. Surveillance of low grade lesions in patients with underlying tumor predisposition syndromes must be interpreted in context of systemic disease burden and concurrent treatments for other neoplasms.

Correction: Height and breast cancer risk in premenopausal Korean women aged under 40 years of age

Correction: Height and breast cancer risk in premenopausal Korean women aged under 40 years of age

Baseline predictors associated with successful weight loss among breast cancer survivors in the Lifestyle, Exercise, and Nutrition (LEAN) study

Baseline predictors associated with successful weight loss among breast cancer survivors in the Lifestyle, Exercise, and Nutrition (LEAN) study

Brca1 haploinsufficiency promotes early tumor onset and epigenetic alterations in a mouse model of hereditary breast cancer

Brca1 haploinsufficiency promotes early tumor onset and epigenetic alterations in a mouse model of hereditary breast cancer

Harnessing curcumin and nanotechnology for enhanced treatment of breast cancer bone metastasis

Harnessing curcumin and nanotechnology for enhanced treatment of breast cancer bone metastasis

Comprehensive analysis of the metabolomics and transcriptomics uncovers the dysregulated network and potential biomarkers of Triple Negative Breast Cancer

Comprehensive analysis of the metabolomics and transcriptomics uncovers the dysregulated network and potential biomarkers of Triple Negative Breast Cancer

Breast metastasis from large cell neuroendocrine carcinoma of the lung: a case report

Abstract Background Primary breast carcinoma is far more common than breast metastases. Common breast metastases usually come from lymphoma, leukemia, melanoma, and ovarian cancers. Breast metastases from neuroendocrine carcinomas are considered an exceeding rare entity. It has been reported in the literature that the pathological presentation of this particular metastatic tumor is very challenging as it shares many morphological characteristics with primary breast carcinoma. Case presentation We report a case of a patient with large cell neuroendocrine carcinoma of the lung metastasizes to both breasts. The patient was initially presented with brain metastasis of unknown origin. Further radiological imaging workup showed multiple bilateral breast masses and bilateral lymphadenopathy, which raised concern for secondary lymphoma of the breast. The histopathology of this case was challenging, particularly when triple negative invasive ductal carcinoma diagnosis had been made. Multidisciplinary meetings between medical oncologists, radiologists, and pathologists profoundly helped confirming the diagnosis of metastatic large cell neuroendocrine tumor to the breast. Conclusion Large cell neuroendocrine carcinoma of the lung is a relatively uncommon diagnosis with generally poor prognosis. Large cell neuroendocrine carcinoma that metastasizes to the breast is even scarcer. Correlation between clinical assessment, radiological imaging, and pathological evaluation is the key in making such an unusual and complex diagnosis. Additionally, radiologists should be aware of metastatic presentations of the breast and avoid confusion with mimicking benign entities or primary breast carcinomas.

MR tomographic evaluation of the effectiveness of neoadjuvant chemotherapy for breast cancer based on pharmacokinetic numerical analysis of tumor uptake of paramagnetic contrast in intravenous contrast enhancement

Background. In clinical practice, MRI pathophysiological and pharmacokinetic models with calculations of contrast transport indicators are unacceptably little used.Aim of the study. To propose a pharmacokinetic technique for the quantitative assessment of primary tumors and metastases, the effectiveness of breast cancer chemotherapy (BC), from dynamic contrast enhancement MRI. Material and methods. 18 patients were included who underwent neoadjuvant chemotherapy (NACHT) in four cycles for breast cancer T1-3N0-1M0, followed by radical surgical removal of the tumor. According to the results of a three — year follow-up, patients with a relapse — free course (n = 11) formed group 1, and seven patients with detected metastatic lesions (3 in the liver, 2 in the lungs, 2 in the brain) — group 2. For the initial 120–180 s of MRI with contrast after the injection of a paramagnetic, the simplification is valid for concentrations in tumor and blood and for tranfer coefficient: d{СОПУХОЛЬ(t)} / dt = ККр-Оп * СКРОВЬ (t) , from which it is obvious: ККр-Оп = (СОПУХОЛЬ(Т)) / (∫CКРОВЬ(t) dt), which was used in all calculations of the contrast transfer constant. Gadobutrol contrast is 0.1M/10 kg of body weight, TR = 5.5–6 ms, TE = 2.5 ms. Results. If, after the first cycle of NACHT, the ККр-Оп of the primary breast cancer is < 0.22 ml/min/g of tissue, the probability of subsequent relapse-free course = 0.78. Similarly, a decrease in the KCr-Op Ккр-Оп of the sentinel lymph node after the first cycle of NAHT < 0.08 ml/min/g of tissue with a probability of 0.75 predicts a relapse-free course. Conclusion. The proposed method for calculating the ККр-Оп transfer coefficient allows obtaining additional diagnostic and prognostic information in patients with local and locally advanced forms of breast cancer.

FOSL1 is a key regulator of a super-enhancer driving TCOF1 expression in triple-negative breast cancer

Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer with an unmet clinical need, but its epigenetic regulation remains largely undefined. By performing multiomic profiling, we recently revealed distinct super-enhancer (SE) patterns in different subtypes of breast cancer and identified a number of TNBC-specific SEs that drive oncogene expression. One of these SEs, TCOF1 SE, was discovered to play an important oncogenic role in TNBC. However, the molecular mechanisms by which TCOF1 SE promotes the expression of the TCOF1 gene remain to be elucidated. Here, by using combinatorial approaches of DNA pull-down assay, bioinformatics analysis and functional studies, we identified FOSL1 as a key transcription factor that binds to TCOF1 SE and drives its overexpression. shRNA-mediated depletion of FOSL1 results in significant downregulation of TCOF1 mRNA and protein levels. Using a dual-luciferase reporter assay and ChIP-qPCR, we showed that binding of FOSL1 to TCOF1 SE promotes the transcription of TCOF1 in TNBC cells. Importantly, our data demonstrated that overexpression of FOSL1 drives the activation of TCOF1 SE. Lastly, depletion of FOSL1 inhibits tumor spheroid growth and stemness properties of TNBC cells. Taken together, these findings uncover the key epigenetic role of FOSL1 and highlight the potential of targeting the FOSL1-TCOF1 axis for TNBC treatment.

Curcumin Induces MCF-7 Breast Cancer Cell Apoptosis Through miR-15a Alteration

Background: In recent years, the application of herbal compounds in cancer treatment has shown significant progress. Curcumin (CUR), a natural polyphenol, demonstrates potent anti-cancer effects against various cancers, including breast cancer (BC). Curcumin targets a range of molecular pathways, contributing to the inhibition of cancer cell proliferation, metastasis, and angiogenesis, and promoting apoptosis. Objectives: This study aimed to assess the effect of CUR on BC cells, focusing on alterations in the expression levels of Mir-15a and Bcl-2 through the apoptotic pathway. Methods: The cytotoxicity of CUR was evaluated using an MTT assay. Changes in the expression of Mir-15a and Bcl-2 genes were analyzed by real-time PCR, and cell apoptosis was measured using flow cytometry. Data analysis was conducted using SPSS. Results: The MTT assay results indicated that cell viability decreased as CUR concentration increased (5 – 25 µM). Real-time PCR results showed a significant decrease in the expression of Mir-15a and Bcl-2 (P < 0.05). Flow cytometry findings demonstrated that CUR treatment at the IC50 concentration for 48 hours induced apoptosis in 75.9% of MCF-7 cells. Conclusions: Our study provides a crucial foundation indicating that CUR induces apoptosis in MCF-7 cells by modulating the expression of Mir-15a.

A IMPORTÂNCIA DO ALEITAMENTO MATERNO PARA ESTREITAR O VÍNCULO AFETIVO ENTRE MÃE E FILHO

Breastfeeding plays a crucial role in strengthening the bond between mother and child. In addition to providing vital nutrition in the first months and years of a child's life, breastfeeding also promotes a healthy, affectionate relationship. Exclusive practice in the first months is the best form of nutrition, intensifying the emotional bond and contributing to healthy development. Adequate guidance on breastfeeding techniques during the prenatal and postpartum period is essential to ensure the effectiveness of this process. Furthermore, breastfeeding offers benefits for both the baby and the mother, helping with postpartum recovery and protecting against diseases such as breast cancer. However, challenges persist in promoting breastfeeding, with rates below recommendations in some regions due to social and cultural factors. It is essential that health policies and professionals offer support and education to mothers, regardless of their ethnic origin or financial situation. Childcare consultations play a crucial role in monitoring a child's growth and promoting child health. Therefore, the active involvement of health professionals, public policies and society in general is necessary to create an environment favorable to breastfeeding. Breastfeeding is essential for promoting healthy relationships between mothers and children, contributing to the physical and emotional health of both.

Early Compliance with Commission on Cancer Operative Standards for Breast Cancer Surgery

Early Compliance with Commission on Cancer Operative Standards for Breast Cancer Surgery

High CTLA-4 gene expression is an independent good prognosis factor in breast cancer patients, especially in the HER2-enriched subtype

BackgroundBreast cancer (BC) is the most common cancer in women and the leading cause of cancer-related death worldwide. This heterogeneous disease has been historically considered a non-immunogenic type of cancer. However, recent advances in immunotherapy have increased the interest in knowing the role of the immune checkpoints (IC) and other immune regulation pathways in this neoplasia.MethodsIn this retrospective study, we evaluated the correlation of mRNA expression of CTLA-4, PDCD1 (PD1), CD274 (PD-L1), PDCD1LG2 (PD-L2), CD276 (B7-H3), JAK2, and FOXO1 with clinicopathological factors and BC patient’s outcome by real-time quantitative polymerase chain reaction (qPCR).ResultsOur results showed that immunoregulatory gene expression depends on BC immunophenotype being CTLA-4 and PDCD1 (PD1) overexpressed on triple-negative/basal-like (TN/BL) and luminal B/HER2-positive phenotypes, respectively, and CD276 (B7-H3), JAK2 and FOXO1 associated with both luminal A and luminal B/HER2-negative tumors. In addition, we found that these genes can also be related to aggressive and non-aggressive clinicopathological characteristics in BC. Finally, survival analysis showed that CTLA-4 expression levels emerge as a significant independent factor of good prognosis in BC patients, especially in the HER2-enriched subtype.ConclusionConsidering all these data, we can conclude that the expression of immunoregulatory genes depends on tumor phenotype and has potential clinical implications in BC patients.

The food environment and postdiagnosis weight gain among Black women breast cancer survivors in Maryland

The food environment and postdiagnosis weight gain among Black women breast cancer survivors in Maryland

DNA methylation classifier to diagnose pancreatic ductal adenocarcinoma metastases from different anatomical sites

BackgroundWe have recently constructed a DNA methylation classifier that can discriminate between pancreatic ductal adenocarcinoma (PAAD) liver metastasis and intrahepatic cholangiocarcinoma (iCCA) with high accuracy (PAAD-iCCA-Classifier). PAAD is one of the leading causes of cancer of unknown primary and diagnosis is based on exclusion of other malignancies. Therefore, our focus was to investigate whether the PAAD-iCCA-Classifier can be used to diagnose PAAD metastases from other sites.MethodsFor this scope, the anomaly detection filter of the initial classifier was expanded by 8 additional mimicker carcinomas, amounting to a total of 10 carcinomas in the negative class. We validated the updated version of the classifier on a validation set, which consisted of a biological cohort (n = 3579) and a technical one (n = 15). We then assessed the performance of the classifier on a test set, which included a positive control cohort of 16 PAAD metastases from various sites and a cohort of 124 negative control samples consisting of 96 breast cancer metastases from 18 anatomical sites and 28 carcinoma metastases to the brain.ResultsThe updated PAAD-iCCA-Classifier achieved 98.21% accuracy on the biological validation samples, and on the technical validation ones it reached 100%. The classifier also correctly identified 15/16 (93.75%) metastases of the positive control as PAAD, and on the negative control, it correctly classified 122/124 samples (98.39%) for a 97.85% overall accuracy on the test set. We used this DNA methylation dataset to explore the organotropism of PAAD metastases and observed that PAAD liver metastases are distinct from PAAD peritoneal carcinomatosis and primary PAAD, and are characterized by specific copy number alterations and hypomethylation of enhancers involved in epithelial-mesenchymal-transition.ConclusionsThe updated PAAD-iCCA-Classifier (available at https://classifier.tgc-research.de/) can accurately classify PAAD samples from various metastatic sites and it can serve as a diagnostic aid.

Design And Synthesis Of Novel Thiazole Linked Tetrahydropyridine Analogues As Anticancer Agents

A library of new thiazole linked tetrahydropyridines (6a‐q) synthesized and screened for their invitro anticancer activity against human breast adeno carcinoma cell viz. MCF‐7 and MDA‐MB‐231. The two compounds 6d containing ‐F and ‐Cl functions in para and meta position of phenyl ring (9.94 ± 1.02µM, 9.78 ± 1.08µM) and 6e with ‐Cl and ‐NH2 functions on pyridine ring (9.72 ± 0.91 µM,9.54 ± 0.95µM) demonstrated outstanding activity against both the cell lines when compared to Doxorubicin. The benzofuran analogue 6o presented good activity with an IC50 value of 12.19 ± 1.03µM (MCF‐7) and 12.22 ± 1.07µM (MDA‐MB‐231). The molecular docking study of potent molecule 6e against crystal structure of breast tumor kinase presented promising docking score and binding interactions. Predicted pharmacokinetics properties of compounds 6a‐q and presented boiled diagram of compounds 6d and 6e implied favourable drug‐likeness properties.

Machine learning unveils key Redox signatures for enhanced breast Cancer therapy

BackgroundBreast cancer remains a leading cause of mortality among women worldwide, necessitating innovative prognostic models to enhance treatment strategies.MethodsOur study retrospectively enrolled 9,439 breast cancer patients from 12 independent datasets and single-cell data from 12 patients (64,308 cells). Moverover, 30 in-house clinical cohort were collected for validation. We employed a comprehensive approach by combining ten distinct machine learning algorithms across 108 different combinations to scrutinize 88 pre-existing signatures of breast cancer. To affirm the efficacy of our developed model, immunohistochemistry assays were performed. Additionally, we investigated various potential immunotherapeutic and chemotherapeutic interventions.ResultsThis study introduces an Artificial Intelligence-aided Redox Signature (AIARS) as a novel prognostic tool, leveraging machine learning to identify critical redox-related gene signatures in breast cancer. Our results demonstrate that AIARS significantly outperforms existing prognostic models in predicting breast cancer outcomes, offering a robust tool for personalized treatment planning. Validation through immunohistochemistry assays on samples from 30 patients corroborated our results, underscoring the model’s applicability on a wider scale. Furthermore, the analysis revealed that patients with low AIARS expression levels are more responsive to immunotherapy. Conversely, those exhibiting high AIARS were found to be more susceptible to certain chemotherapeutic agents, including vincristine.ConclusionsOur study underscores the importance of redox biology in breast cancer prognosis and introduces a powerful machine learning-based tool, the AIARS, for personalized treatment strategies. By providing a more nuanced understanding of the redox landscape in breast cancer, the AIARS paves the way for the development of redox-targeted therapies, promising to enhance patient outcomes significantly. Future work will focus on clinical validation and exploring the mechanistic roles of identified genes in cancer biology.

Fusing global context with multiscale context for enhanced breast cancer classification

Breast cancer is the second most common type of cancer among women. Prompt detection of breast cancer can impede its advancement to more advanced phases, thereby elevating the probability of favorable treatment consequences. Histopathological images are commonly used for breast cancer classification due to their detailed cellular information. Existing diagnostic approaches rely on Convolutional Neural Networks (CNNs) which are limited to local context resulting in a lower classification accuracy. Therefore, we present a fusion model composed of a Vision Transformer (ViT) and custom Atrous Spatial Pyramid Pooling (ASPP) network with an attention mechanism for effectively classifying breast cancer from histopathological images. ViT enables the model to attain global features, while the ASPP network accommodates multiscale features. Fusing the features derived from the models resulted in a robust breast cancer classifier. With the help of five-stage image preprocessing technique, the proposed model achieved 100% accuracy in classifying breast cancer on the BreakHis dataset at 100X and 400X magnification factors. On 40X and 200X magnifications, the model achieved 99.25% and 98.26% classification accuracy respectively. With a commendable classification efficacy on histopathological images, the model can be considered a dependable option for proficient breast cancer classification.

Immune infiltration correlates with transcriptomic subtypes in primary estrogen receptor positive invasive lobular breast cancer

Understanding interplay of breast cancer and microenvironment is critical. Here we identified two transcriptomic subtypes and five immune infiltration patterns from RNA-seq and multiplex immunohistochemistry from 21 ER + /HER2- ILCs. We found proliferative subtype associated with increased suppressive immune infiltration, and defined a signature associated with lower proliferative, pro-inflammatory TAM infiltration, and improved survival in ER+ breast cancer. Our work identified genes related to ILC immune microenvironment and prognosis.

A Machine Learning Approach for Breast Cancer Risk Prediction in Digital Mammography

Breast cancer is among the most prevalent cancers in the female population globally. Therefore, screening campaigns as well as approaches to identify patients at risk are particularly important for the early detection of suspect lesions. This study aims to propose a workflow for the automatic classification of patients based on one of the most relevant risk factors in breast cancer, which is represented by breast density. The proposed classification methodology takes advantage of the features automatically extracted from mammographic images, as digital mammography represents the major screening tool in women. Textural features were extracted from the breast parenchyma through a radiomics approach, and they were used to train different machine learning algorithms and neural network models to classify the breast density according to the standard Breast Imaging Reporting and Data System (BI-RADS) guidelines. Both binary and multiclass tasks have been carried out and compared in terms of performance metrics. Preliminary results show interesting classification accuracy (93.55% for the binary task and 82.14% for the multiclass task), which are promising compared to the current literature. As the proposed workflow relies on straightforward and computationally efficient algorithms, it could serve as a basis for a fast-track protocol for the screening of mammograms to reduce the radiologists’ workload.