MRPL13 is a metastatic and prognostic marker of breast cancer: A silico analysis accompanied with experimental validation.

BACKGROUND: Although progress has been made in accurate diagnosis and targeted treatments, breast cancer (BC) patients with metastasis still present a grim prognosis. With the continuous emergence and development of new personalized and precision medicine targeting specific tumor biomarkers, there is an urgent need to find new metastatic and prognostic biomarkers for BC patients. METHODS: We were dedicated to identifying genes linked to metastasis and prognosis in breast cancer through a combination of in silico analysis and experimental validation. RESULTS: A total of 25 overlap differentially expressed genes were identified. Ten hub genes (namely MRPL13, CTR9, TCEB1, RPLP0, TIMM8B, METTL1, GOLT1B, PLK2, PARL and MANBA) were identified and confirmed. MRPL13, TCEB1 and GOLT1B were shown to be associated with the worse overall survival (OS) and were optionally chosen for further verification by western blot. Only MRPL13 was found associated with cell invasion, and the expression of MRPL13 in metastatic BC was significantly higher than in primary BC. CONCLUSION: We proposed MRPL13 could be a potential novel biomarker for the metastasis and prognosis of breast cancer.

Electrochemical biosensors for early detection of breast cancer.

Breast cancer continues to be a significant contributor to global cancer deaths, particularly among women. This highlights the critical role of early detection and treatment in boosting survival rates. While conventional diagnostic methods like mammograms, biopsies, ultrasounds, and MRIs are valuable tools, limitations exist in terms of cost, invasiveness, and the requirement for specialized equipment and trained personnel. Recent shifts towards biosensor technologies offer a promising alternative for monitoring biological processes and providing accurate health diagnostics in a cost-effective, non-invasive manner. These biosensors are particularly advantageous for early detection of primary tumors, metastases, and recurrent diseases, contributing to more effective breast cancer management. The integration of biosensor technology into medical devices has led to the development of low-cost, adaptable, and efficient diagnostic tools. In this framework, electrochemical screening platforms have garnered significant attention due to their selectivity, affordability, and ease of result interpretation. The current review discusses various breast cancer biomarkers and the potential of electrochemical biosensors to revolutionize early cancer detection, making provision for new diagnostic platforms and personalized healthcare solutions.

Genetically engineered CD276-anchoring biomimetic nanovesicles target senescent escaped tumor cells to overcome chemoresistant and immunosuppressive breast cancer.

Chemotherapy-induced cellular senescence leads to an increased proportion of cancer stem cells (CSCs) in breast cancer (BC), contributing to recurrence and metastasis, while effective means to clear them are currently lacking. Herein, we aim to develop new approaches for selectively killing senescent-escape CSCs. High CD276 (95.60%) expression in multidrug-resistant BC cells, facilitates immune evasion by low-immunogenic senescent escape CSCs. CALD1, upregulated in ADR-resistant BC, promoting senescent-escape of CSCs with an anti-apoptosis state and upregulating CD276, PD-L1 to promote chemoresistance and immune escape. We have developed a controlled-released thermosensitive hydrogel containing pH- responsive anti-CD276 scFV engineered biomimetic nanovesicles to overcome BC in primary, recurrent, metastatic and abscopal humanized mice models. Nanovesicles coated anti-CD276 scFV selectively fuses with cell membrane of senescent-escape CSCs, then sequentially delivers siCALD1 and ADR due to pH-responsive MnP shell. siCALD1 together with ADR effectively induce apoptosis of CSCs, decrease expression of CD276 and PD-L1, and upregulate MHC I combined with Mn2+ to overcome chemoresistance and promote CD8+T cells infiltration. This combined therapeutic approach reveals insights into immune surveillance evasion by senescent-escape CSCs, offering a promising strategy to immunotherapy effectiveness in cancer therapy.

Visible-short wavelength near infrared hyperspectral imaging coupled with multivariate curve resolution-alternating least squares for diagnosis of breast cancer.

This study investigates the application of visible-short wavelength near-infrared hyperspectral imaging (Vis-SWNIR HSI) in the wavelength range of 400-950 nm and advanced chemometric techniques for diagnosing breast cancer (BC). The research involved 56 ex-vivo samples encompassing both cancerous and non-cancerous breast tissue from females. First, HSI images were analyzed using multivariate curve resolution-alternating least squares (MCR-ALS) to exploit pure spatial and spectral profiles of active components. Then, the MCR-ALS resolved spatial profiles were arranged in a new data matrix for exploration and discrimination between benign and cancerous tissue samples using principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA). The PLS-DA classification accuracy of 82.1 % showed the potential of HSI and chemometrics for non-invasive detection of BC. Additionally, the resolved spectral profiles by MCR-ALS can be used to track the changes in the breast tissue during cancer and treatment. It is concluded that the proposed strategy in this work can effectively differentiate between cancerous and non-cancerous breast tissue and pave the way for further studies and potential clinical implementation of this innovative approach, offering a promising avenue for improving early detection and treatment outcomes in BC patients.

Deciphering the role of LGALS2: insights into tertiary lymphoid structure-associated dendritic cell activation and immunotherapeutic potential in breast cancer patients.

Recent advances in cancer research have highlighted the pivotal role of tertiary lymphoid structures (TLSs) in modulating immune responses, particularly in breast cancer (BRCA). Here, we performed an integrated analysis of bulk transcriptome data from over 6000 BRCA samples using biological network-based computational strategies and machine learning (ML) methods, and identified LGALS2 as a key marker within TLSs. Single-cell sequencing and spatial transcriptomics uncover the role of LGALS2 in TLS-associated dendritic cells (DCs) stimulation and reveal the complexity of the tumor microenvironment (TME) at both the macro and micro levels. Elevated LGALS2 expression correlates with prolonged survival, which is associated with a robust immune response marked by diverse immune cell infiltration and active anti-tumor pathways leading to a 'hot' tumor microenvironment. The colocalization of LGALS2 with TLS-associated DCs and its role in immune activation in BRCA were confirmed by hematoxylin-eosin (HE), immunohistochemistry (IHC), and in vivo validation analyses. The identification of LGALS2 as a key factor in BRCA not only highlights its therapeutic potential in novel TLS-directed immunotherapy but also opens new avenues in patient stratification and treatment selection, ultimately improving clinical management.

Comparison of clinicopathological characteristics, efficacy of neoadjuvant therapy, and prognosis in HER2-low and HER2-ultralow breast cancer.

BACKGROUND: This study aims to analyze potential differences in clinicopathology, efficacy of neoadjuvant therapy (NAT), and clinical outcome among HER2-null, HER2-ultralow and HER2-low breast cancers. METHODS: Consecutive cases of HER2-negative breast cancer that received NAT were included. They were classified as HER2-null (no staining), HER2-ultralow (incomplete faint staining in ≤ 10% of tumour cells) and HER2-low (HER2-1 + or HER2-2+, in situ hybridisation negative). Subgroup analysis was performed based on the HER2 expression level. RESULTS: Out of 302 patients, 215 (71.19%) were HER2-low, 59 (19.54%) were HER2-ultralow, and 28 (9.27%) were HER2-null. In comparison to the HER2-ultralow group, the HER2-low group exhibited higher expression frequencies of ER (p < 0.001), PR (p < 0.001), and AR (p = 0.004), along with a greater prevalence of the luminal subtype (p < 0.001). The HER2-ultralow group also demonstrated a higher prevalence of lymph node metastasis compared to the HER2-null group (p = 0.026). Varied rates of pathologic complete response (pCR) were observed among the three subgroups: HER2-null, HER2-ultralow, and HER2-low, with rates of 35.71%, 22.03%, and 12.56%, respectively. Only the HER2-low subgroup exhibited a significant difference compared to HER2-null (p = 0.001). Despite variations in pCR rates, the three subgroups exhibited comparable disease-free survival (DFS) (p = 0.571). Importantly, we found HER2-low patients with better treatment response (RCB-0/I) exhibited significantly better DFS than those with significant residual disease (RCB-II/III) (P = 0.036). The overall rate of HER2 immunohistochemical score discordance was 45.24%, mostly driven by the conversion between HER2-0 and HER2-low phenotype. Notably, 32.19% of cases initially classified as HER2-0 phenotype on baseline biopsy were later reclassified as HER2-low after neoadjuvant therapy, and it is noteworthy that 22 out of these cases (78.57%) originally had an HER2-ultralow status in the pretreatment biopsy sample. CONCLUSIONS: Our results demonstrate the distinct clinicopathological features of HER2-low and HER2-ultralow breast tumors and confirm that RCB is an effective predictor of prognosis in HER2-low populations for the first time. Notably, our findings demonstrate high instability in both HER2-low and HER2-ultralow expression from the primary baseline biopsy to residual disease after NAT. Furthermore, this study is the first to investigate the clinicopathological feature and the effectiveness of NAT for HER2-ultralow breast cancer.

Psychometric properties of the Turkish version of the perceived barriers of mammography scale.

AIM: Early diagnosis and screening of breast cancer are of vital importance in the fight against the disease. It is crucial to identify the underlying barriers that prevent women from undergoing mammography and to develop necessary strategies to overcome these obstacles. The purpose of this study was to adapt "The Perceived Barriers of Mammography Scale (PBMS-23)" into Turkish and to conduct a validity and reliability study. METHODS: This study used a methodological approach. The study was conducted with 233 women admitted to the Gynecology Outpatient Clinic of a university hospital. Data were collected by using the Introductory Information Form, PBMS-23, Champion's Health Belief Model Scale for Mammography Screening (CHBMS-MS). Psychometric properties of the scale were tested with content validity, confirmatory factor analysis, convergent validity, and test-retest reliability coefficient. RESULTS: Content validity confirmatory factor analysis resulted in 𝜒2/SD = 1.67; CFI = 0.97, NFI = 0.92, GFI = 0.86, RMSEA = 0.054. The scale had a Cronbach's alpha of 0.87, while the subscales had Cronbach's alpha values of 0.34 to 0.80. The intraclass correlation coefficient values calculated for the test-retest reliability were between 0.83 and 0.96 for the subscales and 0.96 for the overall scale. There is a positive and statistically significant relationship (p < 0.01) between the CHBMS-MS barriers dimension and prejudices dimension scores and all subdimensions and the total of the PBMS-23. CONCLUSION: The PBMS-23 was accepted as a valid and reliable tool with 23 items and eight-factor structure that can be useful in measuring Turkish women's barriers to mammography.

A simple cell proliferation assay and the inflammatory protein content show significant differences in human plasmas from young and old subjects.

Some studies showed a "rejuvenating" effect of exposing aging tissues to a young environment. In mouse heterochronic parabiosis experiments, in response to young organisms, old animals lived longer than isochrony old age-matched conjoint animals. Comparable "rejuvenating" effects were obtained by injecting young plasma in old mice. This raised great hopes of slowing down the senescence process in humans by the injection of young plasma, as well as to prevent or cure age-related diseases. Some clinical trials are currently being performed or were recently completed. However, these studies are small and of limited duration, and we still lack convincing evidence to support the effectiveness of young plasma injection. It is urgent to perform additional investigations, including the development of an assay to measure the cell proliferation induction capability of different human plasmas, before one can seriously think of a large-scale treatment of humans. We adopted a simple method to measure the potential of different plasmas in supporting cell line proliferation, regardless of the co-presence of a platelet lysate. By comparing plasmas from young and old subjects, we observed a decreased activity in plasmas from old individuals. The young plasma effect may be attributed to specific proteins and growth factors more abundant in younger individuals that could decrease with age. Alternatively, or at the same time, the reduced cell proliferation support could be due to inhibitors present in the old plasma. Studying the different protein content of young and old plasmas was out of the scope of this article. Such differences should be adequately investigated by proteomics using many samples. However, a preliminary study of the different protein content of young and old plasmas was part of the assay validation using a commercially available cytokine array for parallel determination of the relative levels of 105 selected human proteins. We could show the existence of specific differences between young and old plasmas and that plasmas from old individuals presented a higher concentration of "inflammatory" proteins.

HER2-targeted therapies for HER2-positive early-stage breast cancer: present and future.

Breast cancer (BC) has the second highest incidence among cancers and is the leading cause of death among women worldwide. The human epidermal growth factor receptor 2 (HER2) is overexpressed in approximately 20%-30% of BC patients. The development of HER2-targeted drugs, including monoclonal antibodies (mAbs), tyrosine kinase inhibitors (TKIs) and antibody-drug conjugates (ADCs), has improved the operation rate and pathological remission rate and reduced the risk of postoperative recurrence for HER2-positive early-stage BC (HER2+ EBC) patients. This review systematically summarizes the mechanisms, resistance, therapeutic modalities and safety of HER2-targeted drugs and helps us further understand these drugs and their use in clinical practice for patients with HER2+ EBC.

TGF-ß and TNF-α interaction promotes the expression of MMP-9 through H3K36 dimethylation: implications in breast cancer metastasis.

Increased MMP-9 expression in the tumor microenvironment (TME) plays a crucial role in the extracellular matrix remodeling to facilitate cancer invasion and metastasis. However, the mechanism of MMP-9 upregulation in TME remains elusive. Since TGF-ß and TNF-α levels are elevated in TME, we asked whether these two agents interacted to induce/augment MMP-9 expression. Using a well-established MDA-MB-231 breast cancer model, we found that the synergy between TGF-ß and TNF-α led to MMP-9 upregulation at the transcriptional and translational levels, compared to treatments with each agent alone. Our in vitro findings are corroborated by co-expression of elevated MMP-9 with TGF-ß and TNF-α in human breast cancer tissues. Mechanistically, we found that the MMP-9 upregulation driven by TGF-ß/TNF-α cooperativity was attenuated by selective inhibition of the TGF-ßRI/Smad3 pathway. Comparable outcomes were observed upon inhibition of TGF-ß-induced phosphorylation of Smad2/3 and p38. As expected, the cells defective in Smad2/3 or p38-mediated signaling did not exhibit this synergistic induction of MMP-9. Importantly, the inhibition of histone methylation but not acetylation dampened the synergistic MMP-9 expression. Histone modification profiling further identified the H3K36me2 as an epigenetic regulatory mark of this synergy. Moreover, TGF-ß/TNF-α co-stimulation led to increased levels of the transcriptionally permissive dimethylation mark at H3K36 in the MMP-9 promoter. Comparable outcomes were noted in cells deficient in NSD2 histone methyltransferase. In conclusion, our findings support a cooperativity model in which TGF-ß could amplify the TNF-α-mediated MMP-9 production via chromatin remodeling and facilitate breast cancer invasion and metastasis.

A nomogram with Nottingham prognostic index for predicting locoregional recurrence in breast cancer patients.

Background: The Nottingham prognostic index (NPI) has been shown to negatively impact survival in breast cancer (BC). However, its ability to predict the locoregional recurrence (LRR) of BC remains still unclear. This study aims to determine whether a higher NPI serves as a significant predictor of LRR in BC. Methods: In total, 238 patients with BC were included in this analysis, and relevant clinicopathological features were collected. Correlation analysis was performed between NPI scores and clinicopathological characteristics. The optimal nomogram model was determined by Akaike information criterion. The accuracy of the model's predictions was evaluated using receiver operating characteristic curves (ROC curves), calibration curves and goodness of fit tests. The clinical application value was assessed through decision curve analysis. Results: Six significant variables were identified, including age, body mass index (BMI), TNM stage, NPI, vascular invasion, perineural invasion (P<0.05). Two prediction models, namely a TNM-stage-based model and an NPI-based model, were constructed. The area under the curve (AUC) for the TNM-stage- and NPI-based models were 0.843 (0.785,0.901) and 0.830 (0.766,0.893) in training set and 0.649 (0.520,0.778) and 0.728 (0.610,0.846) in validation set, respectively. Both models exhibited good calibration and goodness of fit. The F-measures were 0.761vs 0.756 and 0.556 vs 0.696, respectively. Clinical decision curve analysis showed that both models provided clinical benefits in evaluating risk judgments based on the nomogram model. Conclusions: a higher NPI is an independent risk factor for predicting LRR in BC. The nomogram model based on NPI demonstrates good discrimination and calibration, offering potential clinical benefits. Therefore, it merits widespread adoption and application.

Lipid profiling of RON and DEK-dependent signaling in breast cancer guides discovery of gene networks predictive of poor outcomes.

Recurrent and metastatic breast cancer is frequently treatment resistant. A wealth of evidence suggests that reprogrammed lipid metabolism supports cancer recurrence. Overexpression of the RON and DEK oncoproteins in breast cancer is associated with poor outcome. Both proteins promote cancer metastasis in laboratory models, but their influence on lipid metabolite levels remain unknown. To measure RON- and DEK-dependent steady-state lipid metabolite levels, a nuclear magnetic resonance (NMR)-based approach was utilized. The observed differences identified a lipid metabolism-related gene expression signature that is prognostic of overall survival (OS), distant metastasis-free survival (DMFS), post-progression survival (PPS), and recurrence-free survival (RFS) in patients with breast cancer. RON loss led to decreased cholesterol and sphingomyelin levels, whereas DEK loss increased total fatty acid levels and decreased free glycerol levels. Lipid-related genes were then queried to define a signature that predicts poor outcomes for patients with breast cancer patients. Taken together, RON and DEK differentially regulate lipid metabolism in a manner that predicts and may promote breast cancer metastasis and recurrence.

Prospects for breast cancer immunotherapy using microRNAs and transposable elements as objects.

One of the directions in treatment of chemoresistant breast cancer (BC) may include new methods of activating the immune response against tumor cells. Clinically used checkpoint inhibition using antibodies to PD-1 and PD-L1 works in some patients, but the lack of biomarkers means number of respondents is low. The possibility of combining this method with chemotherapy is limited by an increased risk of toxic liver damage, development of immune-related pneumonitis, and thyroid dysfunction. This article includes introduction into the clinic of new methods of immunotherapy for BC, among which epigenetic activation of retroelements, double-stranded transcripts of which stimulate the interferon response against the tumor, is promising. For this purpose, inhibitors of DNA methyltransferase*, histone deacetylase* and histone methyltransferase* are used (* subtitles in the main text). Their antitumor effect is also mediated by removal of repressive epigenetic marks from tumor suppressor genes. However, numerous studies have proven the role of retroelements in the carcinogenesis of various malignant neoplasms, including BC. Moreover, endogenous retroviruses HERV-K and LINE1 retrotransposons are planned to be used as diagnostic biomarkers for BC. Therefore, a rational approach to using viral mimicry in antitumor therapy of BC may be the simultaneous suppression of specific retrotransposons (drivers for carcinogenesis) using reverse transcriptase inhibitors and silencing of specific transposons involved in carcinogenesis using complementary microRNAs. To determine possible pathways of influence in this direction, 35 specific transposon-derived microRNAs* changes in BC were identified, which can become guides for targeted therapy of BC.

Breast cancer and rectal cancer associated with Lynch syndrome: A case report.

BACKGROUND: The development mechanisms of Lynch syndrome (LS)-related breast cancer (BC) and rectal cancer are complex and variable, leading to personalized variations in diagnosis and treatment plans. CASE SUMMARY: This paper presents a comprehensive review of clinical diagnosis and treatment data from a patient with LS-associated BC and rectal cancer. Moreover, screening data and management guidelines, as well as relevant literature on LS, are included in this report. This study summarizes the molecular pathogenesis, clinicopathological features, and screening and management protocols for LS-associated BC and rectal cancer. CONCLUSION: Implementing early screening, prevention, and timely diagnosis and treatment measures is expected to reduce mitigate the incidence and mortality of LS-related BC and rectal cancer.

Identifying new biomarkers and potential therapeutic targets for breast cancer through the integration of human plasma proteomics: a Mendelian randomization study and colocalization analysis.

Background: The proteome is a crucial reservoir of targets for cancer treatment. While some targeted therapies have been developed, there are still significant challenges in early diagnosis and treatment, highlighting the need to identify new biomarkers and therapeutic targets for breast cancer. Therefore, we conducted a comprehensive proteome-wide Mendelian randomization (MR) study to identify novel biomarkers and potential therapeutic targets for breast cancer. Methods: Protein quantitative trait locus (pQTL) data were extracted from two published plasma proteome-wide association studies. Genetic variants associated with breast cancer were obtained from the Breast Cancer Association Consortium, which included 133,384 cases and 113,789 controls, and the Finnish cohort study, comprising 18,786 cases and 182,927 controls. We employed summary-based MR and colocalization methods to identify potential drug targets for breast cancer, which were subsequently validated using a two-sample MR approach. Finally, a protein-protein interaction (PPI) network was constructed to detect interactions between the identified proteins and existing cancer drug targets. Results: Gene-predicted levels of ten proteins were associated with breast cancer risk. Decreased levels of CASP8, DDX58, CPNE1, ULK3, PARK7, and BTN2A1, as well as increased levels of TNFRSF9, TNXB, DNPH1, and TLR1, were linked to an elevated risk of breast cancer. Among these, CASP8 and DDX58 were supported by tier-one evidence, while CPNE1, ULK3, PARK7, and TNFRSF9 received tier-two evidence support. The remaining proteins, TNXB, BTN2A1, DNPH1, and TLR1, were supported by tier-three evidence. CASP8, DDX58, CPNE1, ULK3, PARK7, and TNFRSF9 have already been identified as targets in drug development and potential therapeutic targets for breast cancer treatment. Additionally, ULK3 showed promise as a prognostic biomarker for breast cancer. Conclusions: The present study identified several novel potential drug targets and biomarkers for breast cancer, providing new insights into its diagnosis and treatment. The integration of PPI and druggability evaluations enhances the prioritization of these therapeutic targets, paving the way for future drug development efforts.

Breast cancer statistics 2024.

This is the American Cancer Society's biennial update of statistics on breast cancer among women based on high-quality incidence and mortality data from the National Cancer Institute and the Centers for Disease Control and Prevention. Breast cancer incidence continued an upward trend, rising by 1% annually during 2012-2021, largely confined to localized-stage and hormone receptor-positive disease. A steeper increase in women younger than 50 years (1.4% annually) versus 50 years and older (0.7%) overall was only significant among White women. Asian American/Pacific Islander women had the fastest increase in both age groups (2.7% and 2.5% per year, respectively); consequently, young Asian American/Pacific Islander women had the second lowest rate in 2000 (57.4 per 100,000) but the highest rate in 2021 (86.3 per 100,000) alongside White women (86.4 per 100,000), surpassing Black women (81.5 per 100,000). In contrast, the overall breast cancer death rate continuously declined during 1989-2022 by 44% overall, translating to 517,900 fewer breast cancer deaths during this time. However, not all women have experienced this progress; mortality remained unchanged since 1990 in American Indian/Alaska Native women, and Black women have 38% higher mortality than White women despite 5% lower incidence. Although the Black-White disparity partly reflects more triple-negative cancers, Black women have the lowest survival for every breast cancer subtype and stage except localized disease, with which they are 10% less likely to be diagnosed than White women (58% vs. 68%), highlighting disadvantages in social determinants of health. Progress against breast cancer could be accelerated by mitigating racial, ethnic, and social disparities through improved clinical trial representation and access to high-quality screening and treatment.

Role of inter- and extra-lesion tissue, transfer learning, and fine-tuning in the robust classification of breast lesions.

Accurate and unbiased classification of breast lesions is pivotal for early diagnosis and treatment, and a deep learning approach can effectively represent and utilize the digital content of images for more precise medical image analysis. Breast ultrasound imaging is useful for detecting and distinguishing benign masses from malignant masses. Based on the different ways in which benign and malignant tumors affect neighboring tissues, i.e., the pattern of growth and border irregularities, the penetration degree of the adjacent tissue, and tissue-level changes, we investigated the relationship between breast cancer imaging features and the roles of inter- and extra-lesional tissues and their impact on refining the performance of deep learning classification. The novelty of the proposed approach lies in considering the features extracted from the tissue inside the tumor (by performing an erosion operation) and from the lesion and surrounding tissue (by performing a dilation operation) for classification. This study uses these new features and three pre-trained deep neuronal networks to address the challenge of breast lesion classification in ultrasound images. To improve the classification accuracy and interpretability of the model, the proposed model leverages transfer learning to accelerate the training process. Three modern pre-trained CNN architectures (MobileNetV2, VGG16, and EfficientNetB7) are used for transfer learning and fine-tuning for optimization. There are concerns related to the neuronal networks producing erroneous outputs in the presence of noisy images, variations in input data, or adversarial attacks; thus, the proposed system uses the BUS-BRA database (two classes/benign and malignant) for training and testing and the unseen BUSI database (two classes/benign and malignant) for testing. Extensive experiments have recorded accuracy and AUC as performance parameters. The results indicate that the proposed system outperforms the existing breast cancer detection algorithms reported in the literature. AUC values of 1.00 are calculated for VGG16 and EfficientNet-B7 in the dilation cases. The proposed approach will facilitate this challenging and time-consuming classification task.

Predicting gene signature in breast cancer patients with multiple machine learning models.

AIMS: The aim of this study was to predict gene signatures in breast cancer patients using multiple machine learning models. METHODS: In this study, we first collated and merged the datasets GSE54002 and GSE22820, obtaining a gene expression matrix comprising 16,820 genes (including 593 breast cancer (BC) samples and 26 normal control (NC) samples). Subsequently, we performed enrichment analyses using Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Disease Ontology (DO). RESULTS: We identified 177 differentially expressed genes (DEGs), including 40 up-regulated and 137 down-regulated genes, through differential expression analysis. The GO enrichment results indicated that these genes are primarily involved in extracellular matrix organization, positive regulation of nervous system development, collagen-containing extracellular matrix, heparin binding, glycosaminoglycan binding, and Wnt protein binding, among others. KEGG enrichment analysis revealed that the DEGs were primarily associated with pathways such as focal adhesion, the PI3K-Akt signaling pathway, and human papillomavirus infection. DO enrichment analysis showed that the DEGs play a significant role in regulating diseases such as intestinal disorders, nephritis, and dermatitis. Further, through LASSO regression analysis and SVM-RFE algorithm analysis, we identified 9 key feature DEGs (CF-DEGs): ANGPTL7, TSHZ2, SDPR, CLCA4, PAMR1, MME, CXCL2, ADAMTS5, and KIT. Additionally, ROC curve analysis demonstrated that these CF-DEGs serve as a reliable diagnostic index. Finally, using the CIBERSORT algorithm, we analyzed the infiltration of immune cells and the associations between CF-DEGs and immune cell infiltration across all samples. CONCLUSIONS: Our findings provide new insights into the molecular functions and metabolic pathways involved in breast cancer, potentially aiding in the discovery of new diagnostic and immunotherapeutic biomarkers.

In Their Own Words: Patient Narratives of Breast Cancer Surgery and Reconstruction.

BACKGROUND: Breast cancer's global burden prompts a comprehensive understanding of patient experiences surrounding surgical interventions. Social media platforms serve as a new potential avenue for analysis, reflecting patients' coping mechanisms and support-seeking behaviors. OBJECTIVE: This study's objective is to further understand patient experiences regarding breast cancer interventions via social media to improve physician-patient dialogue. METHODS: A cross-sectional study was conducted of Instagram and TikTok posts surrounding breast cancer surgeries using procedure-related hashtags. Content was categorized to prevalent themes related to Breast-Q foci and was subsequently analyzed. RESULTS: Data from 1,028 individuals were analyzed. Posts encompassed double mastectomy (39%), single mastectomy (22%), and combined deep inferior epigastric perforator flap, latissimus dorsi flap, and transverse rectus abdominis muscle flap reconstruction (39%). Frequently identified themes included 'Raising Awareness' (86.87%), 'Spreading Positivity' (53.11%), 'Resiliency' (31.03%), 'Online Support' (24.61%), 'Update of Appearance' (20.82%), 'Recovery/Rehab' (19.94%), and 'Scientific Explanation' (19.75%). Instagram posts more likely encompassed positivity (p < 0.001), resiliency (p = 0.001), and mental health (p = 0.011). TikTok posts more likely (p = 0.001) discussed scientific explanations, decision-making, and symptoms (p < 0.001). Preoperative posts more likely (p < 0.001) surrounded scientific explanations, decision-making, and fear. Postoperative posts more likely (p < 0.001) highlighted appearance updates, recovery/rehab, and positivity (p = 0.012). Experiences with mastectomy and reconstruction differed: recovery/rehab (p < 0.001), scientific explanations (p = 0.015), treatment process (p = 0.003), range of motion (p < 0.001), self-esteem (p = 0.017), and wound management (p = 0.008). CONCLUSION: Concerns of patients online reflect Breast-Q measures. Understanding these nuanced patient discussions can provide novel insights for providers. Tailoring interactions through these insights may facilitate enhanced support, discussions, and experiences throughout the treatment journey. Main Points Social media offers a unique insight into personal patient experiences Online breast surgery patient perspectives reflect Breast-Q measures Outlooks from shared online posts may facilitate physician-patient dialogue LEVEL OF EVIDENCE V: This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

Value of miR-31 and miR-150-3p as diagnostic and prognostic biomarkers for breast cancer.

BACKGROUND: The most prevalent malignancy among women is breast cancer (BC). MicroRNAs (miRNAs) play a role in the initiation and progression of BC by influencing breast cancer stem cells (BCSCs) but the diagnostic and prognostic roles of those miRNAs on BC patients are still unknown. It was aimed to investigate expression profiles, diagnostic and prognostic potentials of BCSC-related miRNAs in different subtypes (Luminal A and B, HER2 + and TNBC) of BC patients. METHODS AND RESULTS: Expression analysis of 15 BCSC-related miRNAs was performed in 50 breast tumor tissues and 20 adjacent non-tumor tissues obtained from BC patients using the qRT-PCR method. The expression levels of miR-31 and miR-150-3p were significantly upregulated in the tumor tissues compared to the adjacent non-tumor tissues (p < 0.05). miR-31 expression upregulated in the Luminal A and Luminal B group compared to non-tumor tissue (p < 0.05). miR-31 expression was determined to be significantly higher in the Luminal group (Luminal A and B) compared to the aggressive group (HER2 + and TNBC) (p < 0.05). According to the ROC analysis, the area under the curve (AUC) of miR-31 and miR-150-3p were 0.66 with a sensitivity of 68% and a specificity of 70%. A significant inverse correlation was observed between miR-31 expression with metastatic carcinoma status, in situ component, and Ki67 value in tumors, and high miR-150-3p expression was correlated with p63 expression (p < 0.05). CONCLUSION: miR-31 and miR-150-3p have the potential to serve as biomarkers for guiding diagnosis, evaluating prognosis, and metastatic process in patients with BC.