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Purpose: Cutaneous metastasis (CM) accounts for 5–30% of patients with breast cancer (BC) and presents unfavorable response to treatment and poor prognosis. A better understanding of the molecular alterations involved in metastasis is essential, which would help identify diagnostic and efficacy biomarkers for CM. Materials: : We retrospectively reviewed a total of 13 patients with histological or cytological diagnosis of breast cancer and CM. Clinical information was extracted from the medical records. The mutational landscape of matched primary tumors with their lymph nodes or CM tissues were analyzed using next-generation sequencing (NGS) of 425 cancer-relevant genes. All tissues were also analyzed by immunohistochemistry (IHC). The association of prognosis with various clinical and molecular factors was also evaluated. Results: More than half of the patients were Ki67 low (< 50%, 53.7%). Most patients (12, 92.3%) had other metastasis sites other than skin. The median time from diagnosis to the presentation of CM (T1) was 15 months (range: 0–94 months) and the median time from CM to death (T2) was 13 months (range 1–78). The most frequently altered genes across the three types of tissues were TP53 (69.6%, 16/23), PIK3CA (34.8%, 8/23), and MYC (26.1%). The number of alterations in CM tends to be higher than in primary tumors (median 8 vs. 6, P = 0.077). Copy number loss in STK11, copy number gain in FGFR4, TERT, AR, FLT4 and VEGFA and mutations in ATRX, SRC, AMER1 and RAD51C were significantly enriched in CM (all P < 0.05). Ki67 high group (> 50%) showed significantly shorter T1 than the Ki67 low group (≤ 50%) (median 12.5 vs. 50.0 months, P = 0.036). TP53, PIK3CA mutations, and TERT amplification group were associated with inferior T2 (median 11 vs. 36 months, P = 0.065; 8 vs. 36 months, P = 0.013, 7 vs. 36 months, P = 0.003, respectively). All p values were not adjusted. Conclusion: We compared the genomic features of primary breast cancer tissues with their corresponding CM tissues and discussed potential genes and pathways that may contribute to the skin metastasis of advanced breast cancers patients. TP53, PIK3CA mutant, and TERT amplification may serve as biomarkers for poor prognosis for CM patients. [ABSTRACT FROM AUTHOR]

Objective: Breast cancer is a type of cancer that originates in breast tissue cells. It is the most common cancer type in the world after lung cancer. The prognosis of the disease mostly depends on the type and stage of cancer. One of the worst prognoses is seen in a specific type called Triple-negative breast cancer (TNBC), which represents not having any of the three most recognized receptors, namely estrogen, progesterone, and c-erb2 receptors. Our objective was to determine the difference in overall and disease-free survival for breast cancer types categorized by receptor status. Methods: This is a retrospective matched case-control study with breast cancer patients of two types. A total of 102 patients were divided equally into having TNBC of 51 patients in one arm and triple-positive breast cancer (TPBC) of 51 patients in the other arm. Analyses were run for disease prognostic values and patients' demographic values. Results: Disease free survival were 63±10.6 months and 93.2±4.9 months in the fifth year for the TNBC and TPBC groups, respectively. (p=0.004) Overall survival was significantly different as 73.9±7.3 months for TNBC and 97.7±2.3 months for TPBC (p=0.002). Conclusion: TNBC prognosis is worse than that of other breast cancer types. The most important reason is being unable to use hormonal treatment because of the receptor status, and a disease-specific targeted treatment could not have been developed so far. Therefore, it is necessary to identify new molecular targets and develop treatments for them. [ABSTRACT FROM AUTHOR]

Background: Obesity is associated with an increased breast cancer risk in postmenopausal women and may contribute to worse outcomes. Black women experience higher obesity and breast cancer mortality rates than non-Black women. We examined associations between race, obesity, and clinical tumor stage with breast cancer prognosis. Methods: We conducted a prospective cohort study in 1,110 breast cancer patients, using univariable and multivariable Cox regression analyses to evaluate the effects of obesity, race/ethnicity, and clinical tumor stage on progression-free and overall survival (PFS and OS). Results: 22% of participants were Black, 64% were Hispanic White, and 14% were non-Hispanic White or another race. 39% of participants were obese (body mass index [BMI] ≥ 30 kg/m2). In univariable analyses, tumor stage III-IV was associated with worse PFS and OS compared to tumor stage 0-II (hazard ratio [HR] = 4.68, 95% confidence interval [CI] = 3.52–6.22 for PFS and HR = 5.92, 95% CI = 4.00-8.77 for OS). Multivariable analysis revealed an association between Black race and worse PFS in obese (HR = 2.19, 95% CI = 1.06–4.51) and non-obese (HR = 2.11, 95% CI = 1.05–4.21) women with tumors staged 0-II. Obesity alone was not associated with worse PFS or OS. Conclusions: Results suggest a complex interrelationship between obesity and race in breast cancer prognosis. The association between the Black race and worse PFS in tumor stages 0-II underscores the importance of early intervention in this group. Future studies are warranted to evaluate whether alternative measures of body composition and biomarkers are better prognostic indicators than BMI among Black breast cancer survivors. [ABSTRACT FROM AUTHOR]

Background: Developing countries have a significantly higher incidence of breast cancer in patients younger than 40 years as compared to developed countries. This study aimed to examine if young age at diagnosis is an independent prognostic factor for worse survival outcomes in breast cancer as well as the effect of age on Disease-free survival (DFS) and local recurrence free survival (LRFS) after adjusting for various tumor characteristics, local and systemic treatments. Methods: This is a secondary analysis of prospective cohort of patients from two existing databases. We identified patients with breast cancer aged 40 years or less and we matched them to those older than 40 years. We also matched based on stage and molecular subtypes. In cohort 1, we matched at a ratio of 1:1, while in cohort 2 we matched at a ratio of 1:3. Results: In cohort 1, Disease-free survival (DFS) at 5 years was significantly shorter for those younger than 40 years (75.6% and 92.7% respectively; p < 0.03). On multivariate analysis, only chemotherapy was found to be significant, while age was not found to be an independent predictor of prognosis. Local recurrence free survival at 5 years was similar between both age categories. Only hormonal therapy is a significant predictor for LRFS at 5 years. In the second cohort, DFS and LRFS at 3 years were similar between those younger and those older than 40 years. On multivariate analysis, no factor including age was found to be an independent predictor of prognosis. Conclusion: Data in the literature is controversial on the effect of young age on breast cancer prognosis. Our findings could not demonstrate that age is an independent prognostic factor in our population. There is a need for outcomes from larger, prospective series that have longer follow-ups and more data from our region. [ABSTRACT FROM AUTHOR]

To look for links between diffusion and IVIM parameters and different molecular subtypes and prognostic factors through histogram analysis. A total of 139 patients with breast cancer who had pre-operative MRI examinations were enrolled in this retrospective study. Histograms of the diffusion and IVIM parameters were analyzed for the whole tumor, and an association was investigated between the parameters and the different molecular prognostic factors and subtypes using the nonparametric test, Spearman's rank correlation, and receiver operating characteristic (ROC) curve. The histogram metrics of the diffusion and IVIM parameters were significantly different for molecular prognostic factors such as human epidermal receptor factor-2 (HER2), progesterone receptor, estrogen receptor, and ki-67. All histogram metrics displayed a poor correlation with all groups (r = −0.28-0.29). There were significant differences in the histogram metrics for the Luminal B-HER2 (−) vs. HER2-positive (non-luminal) subtypes in the mean and 10th percentile D, with the area under the curves (AUCs) of 0.742 and 0.700, respectively, and for the Luminal A and HER2-positive (non-luminal) subtypes in the 90th percentile and entropy of D*, with AUCs of 0.769 and 0.727, respectively. The histogram metrics of IVIM parameters exhibited links with breast cancer prognosis factors and combined subtypes. [ABSTRACT FROM AUTHOR]

Background: Increasing evidence has shown that connexins are involved in the regulation of tumor development, immune escape, and drug resistance. This study investigated the gene expression patterns, prognostic values, and potential mechanisms of connexins in breast cancer. Methods: We conducted a comprehensive analysis of connexins using public gene and protein expression databases and clinical samples from our institution. Connexin mRNA expressions in breast cancer and matched normal tissues were compared, and multiomics studies were performed. Results: Gap junction beta‐2 mRNA was overexpressed in breast cancers of different pathological types and molecular subtypes, and its high expression was associated with poor prognosis. The tumor membrane of the gap junction beta‐2 mutated group was positive, and the corresponding protein was expressed. Somatic mutation and copy number variation of gap junction beta‐2 are rare in breast cancer. The gap junction beta‐2 transcription level in the p110α subunit of the phosphoinositide 3‐kinase mutant subgroup was higher than that in the wild‐type subgroup. Gap junction beta‐2 was associated with the phosphoinositide 3‐kinase‐Akt signaling pathway, extracellular matrix–receptor interaction, focal adhesion, and proteoglycans in cancer. Furthermore, gap junction beta‐2 overexpression may be associated with phosphoinositide 3‐kinase and histone deacetylase inhibitor resistance, and its expression level correlated with infiltrating CD8+ T cells, macrophages, neutrophils, and dendritic cells. Conclusions: Gap junction beta‐2 may be a promising therapeutic target for targeted therapy and immunotherapy and may be used to predict breast cancer prognosis. [ABSTRACT FROM AUTHOR]

Background: pregnancy-associated breast cancer (PABC) affects one in 3000 pregnancies, often presenting with aggressive features. Methods: We retrospectively evaluated a cohort of 282 young BC patients (≤45 years old) treated between 1995 and 2019, dividing them into three groups: nulliparous women, women with PABC (diagnosed within 2 years since last pregnancy) and women with BC diagnosed > 2 years since last pregnancy. This last group was further stratified according to the time between pregnancy and BC. The analysis encompassed histological factors (tumor size, histotype, grading, nodal involvement, multifocality, lympho-vascular invasion, hormone receptor expression, Ki-67 index, and HER2 expression), type of surgery and recurrence. Results: Age at diagnosis was younger in nulliparous than in parous women (p < 0.001). No significant differences were noticed regarding histological characteristics and recurrences. At univariate analysis, nodal involvement (OR = 2.4; p < 0.0001), high tumor grade (OR = 2.6; p = 0.01), and lympho-vascular invasion (OR = 2.3; p < 0.05), but not pregnancy (OR = 0.8; p = 0.30), influenced DFS negatively. Multivariate analysis confirmed nodal involvement as the only negative independent prognostic factor for a worse DFS (OR = 2.4; p = 0.0001). Conclusions: in our experience, pregnancy is not an independent adverse prognostic factor for BC DFS. [ABSTRACT FROM AUTHOR]

Immune cells play a key role in tumor microenvironment. The purpose of this study was to investigate the infiltration and clinical indication of immune cells including their combined prognostic value in microenvironment of triple negative breast cancer. Methods: We investigated 100 patients with triple negative breast cancer by Opal/Tyramide Signal Amplification multispectral immunofluorescence between 2003 and 2017 at Zhejiang Provincial people's Hospital. Intratumoral and stromal immune cells of triple negative breast cancer were classified and quantitatively analyzed. Survival outcomes were compared using the Kaplan–Meier method and further analyzed with multivariate analysis. Results: Infiltration level of stromal B lymphocytes, stromal and intratumoral CD8+ T cells, stromal CD4+ T cells, stromal PD-L1 and intratumoral tumor associated macrophages 2 cells were shown as independent factors affecting disease-free survival and overall survival in univariate analysis. Stromal B lymphocytes, T stage, N stage and pathological type were independent predictive factors for both DFS and OS in multivariate analysis. We firstly found that patients with B lymphocytes-enriched subtypes have a better prognosis than those with T lymphocytes-enriched subtypes and tumor-associated macrophage-enriched subtypes. Conclusion: The present study identified a bunch of immune targets and subtypes, which could be exploited in future combined immunotherapy/chemotherapy strategies for triple negative breast cancer patients. [ABSTRACT FROM AUTHOR]

Background: Breast cancer is a major global health concern, and there is a continuous search for novel biomarkers to predict its prognosis. The mitochondrial protein NDUFAF6, previously studied in liver cancer, is now being investigated for its role in breast cancer. This study aims to explore the expression and functional significance of NDUFAF6 in breast cancer using various databases and experimental models. Methods: We analyzed breast cancer samples from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and Human Protein Atlas (HPA) databases, supplemented with immunohistochemistry (IHC) staining to assess NDUFAF6 expression. A breast cancer cell xenograft mouse model was used to evaluate tumor growth, apoptosis, and NDUFAF6 expression. Survival probabilities were estimated through Kaplan–Meier plots and Cox regression analysis. A Protein–Protein Interaction (PPI) network was constructed, and differentially expressed genes related to NDUFAF6 were analyzed using GO, KEGG, and GSEA. The relationship between NDUFAF6 expression, immune checkpoints, and immune infiltration was also evaluated. Results: NDUFAF6 was found to be overexpressed in breast cancer patients and in the xenograft mouse model. Its expression correlated with worse clinical features and prognosis. NDUFAF6 expression was an independent predictor of breast cancer outcomes in both univariate and multivariate analyses. Functionally, NDUFAF6 is implicated in several immune-related pathways. Crucially, NDUFAF6 expression correlated with various immune infiltrating cells and checkpoints, particularly promoting PD-L1 expression by inhibiting the NRF2 signaling pathway. Conclusion: The study establishes NDUFAF6 as a potential prognostic biomarker in breast cancer. Its mechanism of action, involving the inhibition of NRF2 to upregulate PD-L1, highlights its significance in the disease's progression and potential as a target for immunotherapy. [ABSTRACT FROM AUTHOR]

Simple Summary: Significant strides have been made in the understanding and management of breast cancer (BC), yet it remains a pervasive and life-threatening illness globally, necessitating precise diagnostic and therapeutic approaches. Molecular subtyping of BC is crucial for prognostic and predictive purposes due to its diverse clinical behaviors. Disparities in diagnosis and outcomes across different populations, particularly among individuals of African heritage, underscore the importance of localized research efforts. Early detection and treatment are imperative for improving survival rates, prompting the emergence of radiogenomics within precision medicine as a promising avenue. Radiogenomics, which integrates genetic patterns with imaging features, holds potential for enhancing early detection, prognosis, and treatment selection. By eliminating the need for biopsy and sequencing, it streamlines clinical workflows and contributes to advancing individualized patient care. However, challenges such as reproducibility, standardization, and data integration remain, highlighting the need for further research and validation, particularly in prospective multi-institutional settings. Despite limitations, radiogenomics stands as a promising frontier in breast cancer research, with the potential to revolutionize patient care through its non-invasive approach and ability to correlate genomic information with imaging phenotypes. Despite significant progress in the prevention, screening, diagnosis, prognosis, and therapy of breast cancer (BC), it remains a highly prevalent and life-threatening disease affecting millions worldwide. Molecular subtyping of BC is crucial for predictive and prognostic purposes due to the diverse clinical behaviors observed across various types. The molecular heterogeneity of BC poses uncertainties in its impact on diagnosis, prognosis, and treatment. Numerous studies have highlighted genetic and environmental differences between patients from different geographic regions, emphasizing the need for localized research. International studies have revealed that patients with African heritage are often diagnosed at a more advanced stage and exhibit poorer responses to treatment and lower survival rates. Despite these global findings, there is a dearth of in-depth studies focusing on communities in the African region. Early diagnosis and timely treatment are paramount to improving survival rates. In this context, radiogenomics emerges as a promising field within precision medicine. By associating genetic patterns with image attributes or features, radiogenomics has the potential to significantly improve early detection, prognosis, and diagnosis. It can provide valuable insights into potential treatment options and predict the likelihood of survival, progression, and relapse. Radiogenomics allows for visual features and genetic marker linkage that promises to eliminate the need for biopsy and sequencing. The application of radiogenomics not only contributes to advancing precision oncology and individualized patient treatment but also streamlines clinical workflows. This review aims to delve into the theoretical underpinnings of radiogenomics and explore its practical applications in the diagnosis, management, and treatment of BC and to put radiogenomics on a path towards fully integrated diagnostics. [ABSTRACT FROM AUTHOR]

Simple Summary: Breast cancer tumors are considered to have intratumoral, as well as human epidermal growth factor receptor 2 (HER2), heterogeneity. Tumors with high intratumoral heterogeneity (ITH) have demonstrated therapeutic resistance. However, studies on cancer heterogeneity as a prognostic factor in breast cancer have been limited. Therefore, we evaluated HER2 ITH, which was manifested by the shape of HER2 fluorescence in situ hybridization amplification distributed histograms (HER2 FISH distributions) with the HER2 gene copy number within a tumor sample. We aimed to determine whether high HER2 heterogeneity is clinically significant for poor prognosis due to resistance to postoperative adjuvant therapy with HER2-targeted agents in primary breast cancer. Indeed, we were able to show herein that high HER2 heterogeneity is significantly associated with poorer prognosis in patients with HER2-positive breast cancer. These results indicated that high HER2 heterogeneity is a factor predicting poor prognosis in patients with HER2-positive breast cancer. Our present observation seemed to be clinically important, because it is expected that our HER2 FISH distribution analysis of heterogeneity might be a convenient and clinically useful method for the prognosis prediction of patients after HER2 adjuvant therapy. Purpose: Breast cancer tumors frequently have intratumoral heterogeneity (ITH). Tumors with high ITH cause therapeutic resistance and have human epidermal growth factor receptor 2 (HER2) heterogeneity in response to HER2-targeted therapies. This study aimed to investigate whether high HER2 heterogeneity levels were clinically related to a poor prognosis for HER2-targeted adjuvant therapy resistance in primary breast cancers. Methods: This study included patients with primary breast cancer (n = 251) treated with adjuvant HER2-targeted therapies. HER2 heterogeneity was manifested by the shape of HER2 fluorescence in situ hybridization amplification (FISH) distributed histograms with the HER2 gene copy number within a tumor sample. Each tumor was classified into a biphasic grade graph (high heterogeneity [HH]) group or a monophasic grade graph (low heterogeneity [LH]) group based on heterogeneity. Both groups were evaluated for disease-free survival (DFS) and overall survival (OS) for a median of ten years of annual follow-up. Results: Of 251 patients with HER2-positive breast cancer, 46 (18.3%) and 205 (81.7%) were classified into the HH and LH groups, respectively. The HH group had more distant metastases and a poorer prognosis than the LH group (DFS: p < 0.001 (HH:63% vs. LH:91% at 10 years) and for the OS: p = 0.012 (HH:78% vs. LH:95% at 10 years). Conclusions: High HER2 heterogeneity is a poor prognostic factor in patients with HER2-positive breast cancer. A novel approach to heterogeneity, which is manifested by the shape of HER2 FISH distributions, might be clinically useful in the prognosis prediction of patients after HER2 adjuvant therapy. [ABSTRACT FROM AUTHOR]

Human endogenous retroviruses (HERVs) are the remnants of ancient retroviral infections integrated into the human genome. Although most HERVs are silenced or rendered inactive by various regulatory mechanisms, they retain the potential to influence the nearby genes. We analyzed the regulatory map of 91 HERV-Ks on neighboring genes in human breast cancer and investigated the impact of HERV-Ks on the tumor microenvironment (TME) and prognosis of breast cancer. Nine RNA-seq datasets were obtained from GEO and NCBI SRA. Differentially expressed genes and HERV-Ks were analyzed using DESeq2. Validation of high-risk prognostic candidate genes using TCGA data. These included Overall survival (multivariate Cox regression model), immune infiltration analysis (TIMER), tumor mutation burden (maftools), and drug sensitivity analysis (GSCA). A total of 88 candidate genes related to breast cancer prognosis were screened, of which CD48, SLAMF7, SLAMF1, IGLL1, IGHA1, and LRRC8A were key genes. Functionally, these six key genes were significantly enriched in some immune function-related pathways, which may be associated with poor prognosis for breast cancer (p = 0.00016), and the expression levels of these genes were significantly correlated with the sensitivity of breast cancer treatment-related drugs. Mechanistically, they may influence breast cancer development by modulating the infiltration of various immune cells into the TME. We further experimentally validated these genes to confirm the results obtained from bioinformatics analysis. This study represents the first report on the regulatory potential of HERV-K in the neighboring breast cancer genome. We identified three key HERV-Ks and five neighboring genes that hold promise as novel targets for future interventions and treatments for breast cancer. [ABSTRACT FROM AUTHOR]

YTH N6-methyladenosine RNA binding protein 1 (YTHDF1), an m6A reader, has a role in the development and progression of breast cancer as well as the immunological microenvironment. The networks of competing endogenous RNA in cancer have received much attention in research. In tumor gene therapy, the regulatory networks of m6A and competing endogenous RNA are increasingly emerging as a new route. We evaluated the relationship between the YTHDF1 expression, overall survival, and clinicopathology of breast cancer using TCGA, PrognoScan, and other datasets. We used Western blot to demonstrate that YTHDF1 is substantially expressed in breast cancer tissues. Furthermore, we explored YTHDF1′s functions in the tumor mutational burden, microsatellite instability, and tumor microenvironment. Our findings indicate that YTHDF1 is a critical component of the m6A regulatory proteins in breast cancer and may have a particular function in the immunological microenvironment. Crucially, we investigated the relationship between YTHDF1 and the associated competitive endogenous RNA regulatory networks, innovatively creating three such networks (Dehydrogenase/Reductase 4-Antisense RNA 1-miR-378g-YTHDF1, HLA Complex Group 9-miR-378g-YTHDF1, Taurine Up-regulated 1-miR-378g-YTHDF1). Furthermore, we showed that miR-378g could inhibit the expression of YTHDF1, and that miR-378g/YTHDF1 could impact MDA-MB-231 proliferation. We speculate that YTHDF1 may serve as a biomarker for poor prognosis and differential diagnosis, impact the growth of breast cancer cells via the ceRNA network axis, and be a target for immunotherapy against breast cancer. [ABSTRACT FROM AUTHOR]

Background: Malnutrition is associated with poor overall survival (OS) in breast cancer patients; however, the most predictive nutritional indicators for the prognosis of patients with breast cancer are not well-established. This study aimed to compare the predictive effects of common nutritional indicators on OS and to refine existing nutritional indicators, thereby identifying a more effective nutritional evaluation indicator for predicting the prognosis in breast cancer patients. Methods: This prospective study analyzed data from 776 breast cancer patients enrolled in the "Investigation on Nutritional Status and its Clinical Outcome of Common Cancers" (INSCOC) project, which was conducted in 40 hospitals in China. We used the time-dependent receiver operating characteristic curve (ROC), Kaplan–Meier survival curve, and Cox regression analysis to evaluate the predictive effects of several nutritional assessments. These assessments included the patient-generated subjective nutrition assessment (PGSGA), the global leadership initiative on malnutrition (GLIM), the controlling nutritional status (CONUT), the nutritional risk index (NRI), and the prognostic nutritional index (PNI). Utilizing machine learning, these nutritional indicators were screened through single-factor analysis, and relatively important variables were selected to modify the PNI. The modified PNI, termed the cholesterol-modified prognostic nutritional index (CPNI), was evaluated for its predictive effect on the prognosis of patients. Results: Among the nutritional assessments (including PGSGA, GLIM, CONUT, NRI, and PNI), PNI showed the highest predictive ability for patient prognosis (time-dependent ROC = 0.58). CPNI, which evolved from PNI, emerged as the superior nutritional index for OS in breast cancer patients, with the time-dependent ROC of 0.65. It also acted as an independent risk factor for mortality (p < 0.05). Moreover, the risk of malnutrition and mortality was observed to increase gradually among both premenopausal and postmenopausal age women, as well as among women categorized as non-overweight, overweight, and obese. Conclusions: The CPNI proves to be an effective nutritional assessment tool for predicting the prognosis of patients with breast cancer. [ABSTRACT FROM AUTHOR]

Background: The impact of alcohol consumption on breast cancer (BC) prognosis remains unclear. Methods: The authors examined short‐term alcohol intake in relation to recurrence and mortality in 3659 women who were diagnosed with stage I–IV BC from 2003 to 2013 in the Pathways Study. Alcohol drinking in the past 6 months was assessed at cohort entry (mean, 2 months postdiagnosis) and 6 months later using a food‐frequency questionnaire. Study end points were recurrence and death from BC, cardiovascular disease, and all causes. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated using multivariable Cox proportional hazards models. Results: Over an average follow‐up of 11.2 years, 524 recurrences and 834 deaths (369 BC‐specific and 314 cardiovascular disease‐specific) occurred. Compared with nondrinkers (36.9%), drinkers were more likely younger, more educated, and current or past smokers. Overall, alcohol consumption was not associated with recurrence or mortality. However, women with higher body mass index (BMI ≥ 30 kg/m2) had lower risk of overall mortality with increasing alcohol consumption for occasional drinking (HR, 0.71; 95% CI, 0.54–0.94) and regular drinking (HR, 0.77; 95% CI, 0.56–1.08) around the time of diagnosis, along with 6 months later, in a dose‐response manner (p <.05). Women with lower BMI (<30 kg/m2) were not at higher risk of mortality but were at possibly higher, yet nonsignificant, risk of recurrence for occasional drinking (HR, 1.29; 95% CI, 0.97–1.71) and regular drinking (HR, 1.19; 95% CI, 0.88–1.62). Conclusions: Alcohol drinking around the time of and up to 6 months after BC diagnosis was associated with lower risk of all‐cause mortality in obese women. A possible higher risk of recurrence was observed in nonobese women. Alcohol consumption around the time of and up to 6 months after breast cancer diagnosis was associated with lower risk of all‐cause mortality in women with obesity in the Pathways Study. A potential association of alcohol intake with increased risk of recurrence in women without obesity was suggested. [ABSTRACT FROM AUTHOR]

BACKGROUND Triple-negative breast cancer (TNBC) has a worse rate of recurrence, survival, and overall survival. This study aimed to find the survival of TNBC and its clinicopathological factors at Cipto Mangunkusumo Hospital. METHODS This study used survival analysis based on clinicopathology in 112 TNBC cases at Cipto Mangunkusumo Hospital, Jakarta, Indonesia, diagnosed from 2009 to 2019. Kaplan--Meier and log-rank tests were used for the analysis. Bivariate and multivariate analyses using Cox regression were performed to obtain the hazard ratios (HRs). RESULTS Most patients were diagnosed at the locally advanced stage (40.2%) compared to the early (33.0%) and metastatic stages (17.9%). The 5-year survival of TNBC was 81.2% with an HR value of 1.372 (p = 0.239) compared to luminal A. Bivariate analyses showed that the older age group with an HR of 6.845 (p = 0.013; CI 1.500--31.243), larger tumor size and extension (T) with an HR of 11.826 (p = 0.001; CI 2.707-51.653), broader regional lymph node involvement (N) with an HR of 8.929 (p = 0.019; CI 1.434-55.587), farther distant metastases (M) with an HR of 3.016 (p = 0.015; CI 1.242-7.322), more lymphovascular invasion with HR of 3.006 (p = 0.018; CI 1.209-7.477), and not operated- on cases with an HR of 9.165 (p<0.001; CI 3.303-25.434) significantly shortened the survival of TNBC. Multivariate analysis found that the only factor worsening the survival was not having surgery, with an HR of 6.175 (p<0.001; CI 1.518-34.288). CONCLUSIONS The 5-year survival rate of TNBC patients was 81.2%. Not having surgery was a clinicopathological factor that worsened survival outcomes in TNBC. [ABSTRACT FROM AUTHOR]

Simple Summary: Approximately 10% of breast cancer (BC) cases are hereditary, and germline pathogenic variants in BRCA1 and BRCA2 genes account for 20% of familial BC cases. Long-term follow-up data related to the prognosis and survival of either BRCA1 or BRCA2 BC patients are conflicting. The aim of this study is to report the analysis of our cohort of BRCA1/2 BC patients included in prospective follow-up after genetic testing. We compared clinicopathological characteristics and prognosis between BC patients with BRCA1 and BRCA2 and a control group without germline PV (BRCA-wt). The presence of BRCA mutation confers a higher risk of relapse and death in patients with BC in the Portuguese population. Prophylactic mastectomy and preventive salpingo-oophorectomy confer lower incidence of relapse and longer median invasive disease-free survival and overall survival, respectively. Background: Germline pathogenic variants (PV) in BRCA1 and BRCA2 genes, which account for 20% of familial breast cancer (BC) cases, are highly penetrant and are associated with Hereditary Breast/Ovarian Cancer Syndrome. Previous studies, mostly including higher numbers of BRCA1 BC patients, yielded conflicting results regarding BRCA1/2 BC outcomes. In the Portuguese population, BRCA2 BC is diagnosed more frequently than BRCA1 BC. We aimed to compare clinicopathological characteristics and prognosis between BC patients with BRCA1 and BRCA2 mutations and a control group without germline PV (BRCA-wt). Furthermore, we explored the frequency and outcomes of risk-reducing surgeries in BRCA-mutated patients. Methods: Prospective follow-up was proposed for patients with a diagnosed BRCA1/2 PV. For this study, a matched control group (by age at diagnosis, by decade, and by stage at diagnosis) included BC patients without germline PV. We compared overall survival (OS) and invasive disease-free survival (iDFS) within the three groups, and the use of risk-reducing surgeries among the BRCA cohort. Results: For a mean follow-up time of 113.0 months, BRCA-wt patients showed longer time to recurrence (p = 0.002) and longer OS (p < 0.001). Among patients with BRCA mutations, no statistical differences were found, although patients with BRCA2 BC had longer iDFS and OS. Uptake of risk-reducing surgeries (contralateral prophylactic mastectomy and salpingo-oophorectomy) were negative predictors of invasive disease and death, respectively. Conclusions: Testing positive for a BRCA PV is associated with a higher risk of relapse and death in patients with BC in the Portuguese population. Risk-reducing mastectomy and salpingo-oophorectomy were associated with lower incidence of relapse and longer median iDFS and OS, respectively. [ABSTRACT FROM AUTHOR]

Background: Metastatic breast cancer (MBC) patients with low expression of human epidermal growth factor 2 (HER2) have been proven to benefit from HER2 targeted therapy. We aimed to determine how HER2-low status affected survival and metastatic risk as well as how it affected pathological complete response (pCR) in neoadjuvant chemotherapy (NAC) patients. Methods: According to the results of immunohistochemistry (IHC) and in situ hybridization (ISH) testing, 321 female patients were sorted into HER2-low (IHC 1+/2+ with ISH negative) and HER2-zero (IHC 0) groups using propensity score matching (PSM). Overall survival (OS), disease-free survival (DFS), and distant disease-free survival (DDFS) were compared for both groups, while pCR was only analyzed for NAC patients. Results: In total, 97 patients in each group after PSM were included. We discovered that pCR was not associated with HER2 expression status in 45 patients who underwent NAC. Five-year OS in the HER2-low group was significantly higher (98.99%) than in the HER2-zero group (95.87%, P =.044); however, this difference was not reflected in the 5-year DFS (90.61 vs 90.52%, P =.868) and 5-year DDFS (93.67 vs 91.53%, P =.757). Meanwhile, multivariate analysis revealed that HER2-low expression could indicate better OS (P =.047, hazard ratios [HRs] = 16.121, 95% confidence interval [CI] = 1.035-251.046), but it had no prognostic value for DFS or DDFS. Conclusion: When compared with HER2-zero expression, HER2-low expression was not connected to pCR and could not modify metastasis risk in female patients with early-stage breast cancer (BC), but it may prolong patient survival. [ABSTRACT FROM AUTHOR]

Background: Metaplastic breast cancer(MBC) is a specific pathological type of invasive breast cancer. There are few studies related to MBC due to its rarity. This study aimed to analyse the differences in clinicopathological characteristics and prognosis between Metaplastic breast cancer and triple-negative invasive ductal carcinoma (TN-IDC). Methods: We retrospectively compared the clinicopathological characteristics of patients diagnosed with MBC and TN-IDC at the Fourth Hospital of Hebei Medical University between 2011 and 2020 in a 1:2 ratio. The log-rank test was used to compare the two groups' disease-free survival (DFS) and overall survival (OS). For MBCs, we performed univariate and multivariate analyses using the Cox proportional hazards model to determine the characteristics that impacted OS and DFS. Results: A total of 81 patients with MBC and 162 patients with TN-IDC were included in this study. At initial diagnosis, MBC patients had larger tumour diameters(P = 0.03) and fewer positive lymph nodes (P = 0.04). Patients with MBC were more likely to have organ metastases after surgery (P = 0.03). Despite receiving the same treatment, MBC patients had worse DFS (HR = 1.66, 95%CI 0.90–3.08, P = 0.11) and OS (HR = 1.98, 95% CI 1.03–3.81, P = 0.04), and OS was statistically significant. Positive lymph nodes at initial diagnosis were associated with worse DFS (HR = 3.98, 95%CI 1.05–15.12, P = 0.04) and OS (HR = 3.70, 95%CI 1.03–13.34, P = 0.04) for patients with MBC. The efficacy of platinum-based agents is insensitive for MBC patients receiving chemotherapy. In addition, patients treated with preoperative chemotherapy had worse DFS compared to patients treated with postoperative chemotherapy (HR = 3.51, 95%CI 1.05–11.75, P = 0.04). Conclusions: The clinicopathological characteristics and prognosis of MBC and TN-IDC differ in many ways. Further studies are required to determine suitable treatment guidelines for patients with MBC. [ABSTRACT FROM AUTHOR]

Background: The tumor microenvironment and intercellular communication between solid tumors and the surrounding stroma play crucial roles in cancer initiation, progression, and prognosis. Radiomics provides clinically relevant information from radiological images; however, its biological implications in uncovering tumor pathophysiology driven by cellular heterogeneity between the tumor and stroma are largely unknown. We aimed to identify radiogenomic signatures of cellular tumor-stroma heterogeneity (TSH) to improve breast cancer management and prognosis analysis. Methods: This retrospective multicohort study included five datasets. Cell subpopulations were estimated using bulk gene expression data, and the relative difference in cell subpopulations between the tumor and stroma was used as a biomarker to categorize patients into good- and poor-survival groups. A radiogenomic signature-based model utilizing dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) was developed to target TSH, and its clinical significance in relation to survival outcomes was independently validated. Results: The final cohorts of 1330 women were included for cellular TSH biomarker identification (n = 112, mean age, 57.3 years ± 14.6) and validation (n = 886, mean age, 58.9 years ± 13.1), radiogenomic signature of TSH identification (n = 91, mean age, 55.5 years ± 11.4), and prognostic (n = 241) assessments. The cytotoxic lymphocyte biomarker differentiated patients into good- and poor-survival groups (p < 0.0001) and was independently validated (p = 0.014). The good survival group exhibited denser cell interconnections. The radiogenomic signature of TSH was identified and showed a positive association with overall survival (p = 0.038) and recurrence-free survival (p = 3 × 10–4). Conclusion: Radiogenomic signatures provide insights into prognostic factors that reflect the imbalanced tumor-stroma environment, thereby presenting breast cancer-specific biological implications and prognostic significance. [ABSTRACT FROM AUTHOR]

Background: For many years, the role of the microbiome in tumor progression, particularly the tumor microbiome, was largely overlooked. The connection between the tumor microbiome and the tumor genome still requires further investigation. Methods: The TCGA microbiome and genome data were obtained from Haziza et al.'s article and UCSC Xena database, respectively. Separate WGCNA networks were constructed for the tumor microbiome and genomic data after filtering the datasets. Correlation analysis between the microbial and mRNA modules was conducted to identify oncogenome associated microbiome module (OAM) modules, with three microbial modules selected for each tumor type. Reactome analysis was used to enrich biological processes. Machine learning techniques were implemented to explore the tumor type-specific enrichment and prognostic value of OAM, as well as the ability of the tumor microbiome to differentiate TP53 mutations. Results: We constructed a total of 182 tumor microbiome and 570 mRNA WGCNA modules. Our results show that there is a correlation between tumor microbiome and tumor genome. Gene enrichment analysis results suggest that the genes in the mRNA module with the highest correlation with the tumor microbiome group are mainly enriched in infection, transcriptional regulation by TP53 and antigen presentation. The correlation analysis of OAM with CD8+ T cells or TAM1 cells suggests the existence of many microbiota that may be involved in tumor immune suppression or promotion, such as Williamsia in breast cancer, Biostraticola in stomach cancer, Megasphaera in cervical cancer and Lottiidibacillus in ovarian cancer. In addition, the results show that the microbiome-genome prognostic model has good predictive value for short-term prognosis. The analysis of tumor TP53 mutations shows that tumor microbiota has a certain ability to distinguish TP53 mutations, with an AUROC value of 0.755. The tumor microbiota with high importance scores are Corallococcus, Bacillus and Saezia. Finally, we identified a potential anti-cancer microbiota, Tissierella, which has been shown to be associated with improved prognosis in tumors including breast cancer, lung adenocarcinoma and gastric cancer. Conclusion: There is an association between the tumor microbiome and the tumor genome, and the existence of this association is not accidental and could change the landscape of tumor research. [ABSTRACT FROM AUTHOR]

Background: For many years, the role of the microbiome in tumor progression, particularly the tumor microbiome, was largely overlooked. The connection between the tumor microbiome and the tumor genome still requires further investigation. Methods: The TCGA microbiome and genome data were obtained from Haziza et al.'s article and UCSC Xena database, respectively. Separate WGCNA networks were constructed for the tumor microbiome and genomic data after filtering the datasets. Correlation analysis between the microbial and mRNA modules was conducted to identify oncogenome associated microbiome module (OAM) modules, with three microbial modules selected for each tumor type. Reactome analysis was used to enrich biological processes. Machine learning techniques were implemented to explore the tumor type-specific enrichment and prognostic value of OAM, as well as the ability of the tumor microbiome to differentiate TP53 mutations. Results: We constructed a total of 182 tumor microbiome and 570 mRNA WGCNA modules. Our results show that there is a correlation between tumor microbiome and tumor genome. Gene enrichment analysis results suggest that the genes in the mRNA module with the highest correlation with the tumor microbiome group are mainly enriched in infection, transcriptional regulation by TP53 and antigen presentation. The correlation analysis of OAM with CD8+ T cells or TAM1 cells suggests the existence of many microbiota that may be involved in tumor immune suppression or promotion, such as Williamsia in breast cancer, Biostraticola in stomach cancer, Megasphaera in cervical cancer and Lottiidibacillus in ovarian cancer. In addition, the results show that the microbiome-genome prognostic model has good predictive value for short-term prognosis. The analysis of tumor TP53 mutations shows that tumor microbiota has a certain ability to distinguish TP53 mutations, with an AUROC value of 0.755. The tumor microbiota with high importance scores are Corallococcus, Bacillus and Saezia. Finally, we identified a potential anti-cancer microbiota, Tissierella, which has been shown to be associated with improved prognosis in tumors including breast cancer, lung adenocarcinoma and gastric cancer. Conclusion: There is an association between the tumor microbiome and the tumor genome, and the existence of this association is not accidental and could change the landscape of tumor research. [ABSTRACT FROM AUTHOR]

Background: Tumor proliferation is a key prognostic factor in breast cancer, but the relationship between tumor proliferation and prognosis remains unclear. Aims and Objectives: To investigate the association between tumor proliferation and prognosis in breast cancer patients using a pathological analysis. Materials and Methods: A retrospective cohort study was conducted, including 100 breast cancer patients who underwent surgical resection between January 2021 and December 2022.Tumor proliferation was assessed using Ki-67 immunostaining and evaluated patient prognosis based on disease-free survival (DFS) and overall survival (OS). We performed statistical analyses to examine the association between tumor proliferation and prognosis. Results: Our results showed a significant correlation between tumor proliferation and prognosis in breast cancer patients. High Ki-67 expression was associated with shorter DFS and OS, while low Ki-67 expression was associated with longer DFS and OS. The difference in DFS and OS between high and low Ki-67 expression groups was statistically significant. Conclusion: Tumor proliferation is a valuable prognostic marker in breast cancer and could be used to guide treatment decisions. Our findings suggest that patients with high Ki-67 expression may benefit from more aggressive treatment options, while patients with low Ki-67 expression may be able to avoid unnecessary treatment and its associated side effects. The accurate assessment of tumor proliferation using Ki-67 immunostaining could potentially improve patient outcomes and reduce the burden of breast cancer treatment. [ABSTRACT FROM AUTHOR]

Background: Despite suggesting many genetic risk markers as the outcome of Genome-wide association studies (GWAS) for breast cancer, replicating the results in different populations has remained the main issue. In this regard, this study assessed the association of two variations in Zinc Finger 365 (ZNF365) in an Iranian population. Methods: In a case-control study conducted at Mashhad University of Medical Sciences, Mashhad, Iran, between 2017 and 2020, ZNF365-rs10822013 and rsl0995190 were genotyped using Allele-Specific PCR (AS-PCR). Breast density was assessed using mammography images. PHASE software module version 2 and SPSS version 16.0 were used for haplotype and statistical analyses. Quantitative and qualitative variables were compared between groups using independent t tests and Chi square tests, respectively. Binary logistic regression analysis was performed to calculate odds ratios. Multivariate analysis was then undertaken for the baseline variables, with a P<0.05 in the univariate analysis. The survival analysis was performed using the Kaplan-Meier method and the log-rank test. Results: In this survey, 732 females, including 342 breast cancer patients and 390 healthy subjects, were enrolled. rs10822013-T allele (P=0.014), rs10995190-G allele (P=0.003), and TG haplotype (P=0.002) were significantly associated with the increased risk of breast cancer. Moreover, rs10995190-GG genotype (P=0.042) and C-G haplotype (P=0.019) revealed a significant association with better overall survival. However, considered polymorphisms and their haplotypes indicated no association with breast density and clinical features of breast cancer. Conclusion: ZNF365 variants might be a potential risk marker of breast cancer in the Iranian population. The interaction between alleles in haplotypes may modulate the amount of the risk conferred by these variants. Further studies on different ethnic groups can validate these results. [ABSTRACT FROM AUTHOR]

Simple Summary: This review provides a comprehensive overview of mammary Paget disease (MPD) from its historical origins to the current diagnostic and treatment strategies while also exploring promising avenues for future advancements in the field. With improved understanding and ongoing research efforts, we aim to enhance the prognosis and quality of life for individuals affected by this relatively uncommon condition. Mammary Paget disease (MPD) is a rare condition primarily affecting adult women, characterized by unilateral skin changes in the nipple–areolar complex (NAC) and frequently associated with underlying breast carcinoma. Histologically, MPD is identified by large intraepidermal epithelial cells (Paget cells) with distinct characteristics. Immunohistochemical profiles aid in distinguishing MPD from other skin conditions. Clinical evaluation and imaging techniques, including magnetic resonance imaging (MRI), are recommended if MPD is suspected, although definitive diagnosis always requires histological examination. This review delves into the historical context, epidemiology, pathogenesis, clinical manifestations, and diagnosis of MPD, emphasizing the need for early detection. The classification of MPD based on pathogenesis is explored, shedding light on its varied presentations. Treatment options, including mastectomy and breast-conserving surgery, are discussed with clear guidelines for different scenarios. Adjuvant therapies are considered, particularly in cases with underlying breast cancer. Prognostic factors are outlined, underlining the importance of early intervention. Looking to the future, emerging techniques, like liquid biopsy, new immunohistochemical and molecular markers, and artificial intelligence-based image analysis, hold the potential to transform MPD diagnosis and treatment. These innovations offer hope for early detection and improved patient care, though validation through large-scale clinical trials is needed. [ABSTRACT FROM AUTHOR]

The primary aim of this study is to critically evaluate and comment on the research presented in the article titled "A Novel Super-Enhancer-Related Gene Signature Predicts Prognosis and Immune Microenvironment for Breast Cancer" by Wu et al. Our specific objectives include assessing the methodology employed by the authors, particularly in regard to the utilization of a super-enhancer-related gene signature for breast cancer prognosis prediction. We propose the necessity of subgroup analysis to effectively address the heterogeneity in breast cancer subtypes, which is crucial for the applicability of the SERGs across diverse breast cancer cases. Additionally, we suggest conducting a more comprehensive immune panel study to deepen the understanding of how the immune microenvironment impacts breast cancer prognosis. Our commentary seeks to provide valuable insights into the strengths and weaknesses of the study, contributing to a more comprehensive understanding of its findings and potential clinical implications. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study is to compare and analyze the clinicopathological characteristics and prognosis of patients with invasive ductal carcinoma coexisting with ductal carcinoma in situ (IDC-DCIS) and invasive ductal carcinoma (IDC) in triple-negative breast cancer (TNBC), and to explore the factors affecting the prognosis, so as to provide new ideas for clinical diagnosis and treatment of these patients. Methods: The patients with TNBC underwent surgery in the Department of Breast Surgery of Harbin Medical University Cancer Hospital from October 2012 to December 2018 were retrospectively analyzed and divided into IDC-DCIS group and IDC group. The clinicopathological characteristics and prognosis of the two groups were compared. P < 0.05 was considered statistically significant. Results: A total of 358 patients were enrolled. There were significant differences in age (P = 0.002), family history (P = 0.016), menopausal status (P = 0.003), KI-67% (P < 0.001), lymphovascular invasion (P = 0.010), histologic grade of IDC (P < 0.001) and multifocal (P < 0.001) between the two groups. The disease-free survival (DFS) of the IDC-DCIS group was better than that of the IDC group (the 5-year DFS was 87.9% vs. 82.6%, P = 0.045), but the overall survival (OS) of the two groups was not statistically significant (the 5-year OS was 96.2% vs. 96.0%, P = 0.573). In addition, the coexistence of DCIS (P = 0.030), lymph node pathologic stage (P = 0.001), tumor location (P = 0.011), and adjuvant chemotherapy (P < 0.001) were independent prognostic factors for DFS. Conclusion: In TNBC, the IDC-DCIS group had less invasive biological characteristics. The DFS of the IDC-DCIS group was better than that of the IDC group, but there was no statistical difference in OS between the two groups. In addition, the coexistence of DCIS, lymph node stage, tumor location and adjuvant chemotherapy may be independent prognostic factors for DFS. [ABSTRACT FROM AUTHOR]

Simple Summary: A new subgroup of breast cancer patients with different survival outcomes, even before new treatment options have been approved, which can be easily differentiated immunohistochemically, has recently received great attention. The approval of trastuzumab deruxtecan in August 2022 by the Food and Drug Administration (FDA) for patients with HER2-low-positive metastatic pretreated breast cancer suggested a new breast cancer subtype; this implied new cohorts of patients with different overall survival outcomes and therefore different treatment needs and chances. Therefore, in our study, we examined whether we could retrospectively differentiate HER-0 and HER2-low-positive breast cancer patients treated with neoadjuvant chemotherapy in a long-term follow-up over 20 years. We observed the overall survival, disease-free survival, and pathological complete response rate. In our study, we observed the long-term survival outcomes investigated for HER2-0 and HER2-low-positive breast cancer patients who received neoadjuvant chemotherapy. Between 1998 and 2020, 10,333 patients with primary breast cancer were treated, including 1373 patients with HER2-0 or HER2-low-positive disease with neoadjuvant chemotherapy. Descriptive analyses were performed, and logistic regression models and survival analyses were calculated for disease-free survival (DFS) and overall survival (OS). Among the 1373 patients, 930 (67.73%) had HER2-low-positive and 443 (32.27%) had HER2-0 tumors. Patients with HER2-0 tumors had a significantly better pathological complete response, 29.25% vs. 20.09%, and pathological complete response/in situ, 31.97% vs. 24.08%, than patients with HER2-low-positive tumors (p < 0.001; p = 0.003), regardless of the hormone receptor (HR) status. No statistically significant differences were observed for the HR-positive (p = 0.315; p = 0.43) or HR-negative subgroups (p = 0.573; p = 0.931). DFS and OS were significantly longer for HR-positive, HER2-low-positive patients (log-rank p = 0.02; p = 0.012). OS was significantly longer for HR-negative, HER2-0 patients (log-rank p = 0.032). No significant DFS differences were found for the HR-negative cohort (log-rank p = 0.232). For the overall cohort, no significant differences were noted between HER2-low-positive and HER2-0 patients, either for DFS (log-rank p = 0.220) or OS (log-rank p = 0.403). These results show different survival outcomes for HER2-0 and HER2-low-positive tumors relative to HR status. These different cohorts can be identified using standardized immunohistochemistry, even retrospectively. [ABSTRACT FROM AUTHOR]

Introduction: Low serum selenium and altered tumour RNA expression of certain selenoproteins are associated with a poor breast cancer prognosis. Selenoprotein expression stringently depends on selenium availability, hence circulating selenium may interact with tumour selenoprotein expression. However, there is no matched analysis to date. Methods: This study included 1453 patients with newly diagnosed breast cancer from the multicentric prospective Sweden Cancerome Analysis Network – Breast study. Total serum selenium, selenoprotein P and glutathione peroxidase 3 were analysed at time of diagnosis. Bulk RNA-sequencing was conducted in matched tumour tissues. Fully adjusted Cox regression models with an interaction term were employed to detect dose-dependent interactions of circulating selenium with the associations of tumour selenoprotein mRNA expression and mortality. Results: 237 deaths were recorded within ~ 9 years follow-up. All three serum selenium biomarkers correlated positively (p < 0.001). All selenoproteins except for GPX6 were expressed in tumour tissues. Single cell RNA-sequencing revealed a heterogeneous expression pattern in the tumour microenvironment. Circulating selenium correlated positively with tumour SELENOW and SELENON expression (p < 0.001). In fully adjusted models, the associations of DIO1, DIO3 and SELENOM with mortality were dose-dependently modified by serum selenium (p < 0.001, p = 0.020, p = 0.038, respectively). With increasing selenium, DIO1 and SELENOM associated with lower, whereas DIO3 expression associated with higher mortality. Association of DIO1 with lower mortality was only apparent in patients with high selenium [above median (70.36 µg/L)], and the HR (95%CI) for one-unit increase in log(FPKM + 1) was 0.70 (0.50–0.98). Conclusions: This first unbiased analysis of serum selenium with the breast cancer selenotranscriptome identified an effect-modification of selenium on the associations of DIO1, SELENOM, and DIO3 with prognosis. Selenium substitution in patients with DIO1-expressing tumours merits consideration to improve survival. [ABSTRACT FROM AUTHOR]

Background: Breast cancers with 1–10% cell staining for estrogen receptor (ER) present particular clinical features. The clinical data of estrogen receptor expression level and treatment effect are limited, particularly regarding chemotherapy benefit. We evaluated the pathologic response to neoadjuvant chemotherapy (NAC) in ER low positive tumors (ER staining 1-10%) and compared it with ER > 10% positive tumors (ER staining > 10%) and ER-negative tumors. We further explored the differences in recurrence and survival with respect to the ER expression level. Method: Patients with stages II and III HER2-negative primary breast cancer who received neoadjuvant chemotherapy followed by definitive surgery were categorized according to their ER percentages into three groups: ER-negative, ER low positive, and ER > 10% positive. Logistic regression models were used to assess the association between each variable and pathologic complete response (pCR). Kaplan‒Meier analysis was used to estimate survival outcomes. Cox models were used to adjust for patient and tumor characteristics. Results: A total of 241 patients were analyzed. Of all patients included, 22 (9.1%) had ER low positive tumors, 159 (66.0%) had ER > 10% positive tumors, and 60 (24.9%) were ER-negative. Low ER positivity was significantly associated with a higher pCR rate than ER > 10% positivity (OR, 0.249; 95% CI, 0.067–0.923; P = 0.038). After a median follow-up time of 32 months, the disease-free survival (DFS) and overall survival (OS) of the patients with ER low positive tumors were significantly worse than those of the patients with ER > 10% positive tumors but similar to those with ER-negative tumors. After adjustment for covariates, ER low positive tumors were significantly associated with worse DFS than ER > 10% positive tumors. Conclusion: Our results indicated that ER low positive breast cancer presents a better response to neoadjuvant chemotherapy and significantly worse prognosis for patients than those with ER > 10% positive tumors, but similar to the ER-negative group. These data support that this category of patients behaves clinically like patients with ER-negative breast cancer and should be treated differently from patients with ER > 10% positive tumors. Further prospective study is needed. [ABSTRACT FROM AUTHOR]

Despite the advancements in breast cancer (BrC) diagnosis and treatment, a considerable proportion of patients with early-stage disease still experience local recurrence or metastasis. This study aimed to assess the levels of specific angiogenic parameters in the EDTA plasma of BrC patients before and after treatment and to explore their clinical and prognostic significance. The levels of vascular endothelial growth factor A (VEGF-A), soluble form of vascular endothelial growth factor receptor type 1 (sVEGFR1), and soluble form of vascular endothelial growth factor receptor type 2 (sVEGFR2) were measured in 84 early BrC patients, both prior to surgery and within a median time of nine months post-treatment. Prognostic significance was evaluated using Kaplan-Meier survival and Cox regression analyses. Linear regression models were employed to examine the independent impact of selected angiogenic factors on DFS in breast cancer patients. The results of uni- and multivariate analyses indicated that a pre-treatment concentration of sVEGFR1 above 30.99 pg/mL was associated with improved disease-free survival (DFS) (p < 0.0001 for both analyses), while a pre-treatment concentration of sVEGFR2 above 9475.67 pg/mL was associated with an increased risk of BrC relapse (p < 0.0001 for both analyses). Additionally, a post-treatment concentration of sVEGFR2 above 7361.71 pg/mL was associated with better overall survival (OS) based on the Kaplan-Meier survival analysis (p = 0.0141). Furthermore, linear regression models revealed a significant inverse association between pre-treatment levels of sVEGFR1 and the risk of relapse (standardized β −0.2578, p = 0.0499) and a significant positive association of VEGF-A levels with the risk of recurrence (standardized β 0.2958, p = 0.0308). In conclusion, the findings suggest that both pre- and post-treatment levels of sVEGFR1 and sVEGFR2 may hold promise as potential prognostic markers for BrC patients. [ABSTRACT FROM AUTHOR]

Background: Results of previous studies about the prognostic roles of histone H4 lysine 16 acetylation (H4K16ac) and histone H4 lysine 20 trimethylation (H4K20me3) in breast cancer were inconsistent. Cellular experiments revealed the interplays between H4K16ac and H4K20me3, but no population study explored the interaction between them on the prognosis. Methods: H4K16ac and H4K20me3 levels in tumors were evaluated by immunohistochemistry for 958 breast cancer patients. Hazard ratios for overall survival (OS) and progression-free survival (PFS) were estimated using Cox regression models. Interaction was assessed on multiplicative scale. Concordance index (C-index) was calculated to verify the predictive performance. Results: The prognostic roles of the low level of H4K16ac or H4K20me3 were significant only in patients with the low level of another marker and their interactions were significant. Moreover, compared with joint high levels of both them, only the combined low levels of both them was associated with a poor prognosis but not the low level of single one. The C-index of the clinicopathological model combined the joint expression of H4K16ac and H4K20me3 [0.739 for OS; 0.672 for PFS] was significantly larger than that of the single clinicopathological model [0.699 for OS, P < 0.001; 0.642 for PFS, P = 0.003] or the model combined with the single H4K16ac [0.712 for OS, P < 0.001; 0.646 for PFS, P < 0.001] or H4K20me3 [0.724 for OS, P = 0.031; 0.662 for PFS, P = 0.006]. Conclusions: There was an interaction between H4K16ac and H4K20me3 on the prognosis of breast cancer and the combination of them was a superior prognostic marker compared to the single one. [ABSTRACT FROM AUTHOR]

Objectives: The study aimed to analyze the poor prognosis of microcalcification in breast cancer (BC), including the pathological complete response (pCR) to neoadjuvant chemotherapy (NACT) and the risk of bone metastases. Materials and methods: 313 breast cancer patients received NACT to evaluate pCR and 1182 patients from a multicenter database to assess bone metastases were retrospectively included. Two groups were divided according to the presence or absence of mammography microcalcification. Clinical data, image characteristics, neoadjuvant treatment response, bone involvement, and follow-up information were recorded. The pCR and bone metastases were compared between subgroups using the Mann–Whitney and χ2 tests and logistic regression, respectively. Results: Mammographic microcalcification was associated with a lower pCR than uncalcified BC in the NACT cohort (20.6% vs 31.6%, P = 0.029). Univariate and multivariate analysis suggested that calcification was a risk factor for poor NACT response [OR = 1.780, 95%CI (1.065–2.974), P = 0.028], [OR = 2.352, 95%CI (1.186–4.667), P = 0.014]. Microcalcification was more likely to be necrosis on MRI than those without microcalcification (53.0% vs 31.7%, P < 0.001), multivariate analysis indicated that tumor necrosis was also a risk factor for poor NACT response [OR = 2.325, 95%CI (1.100–4.911), P = 0.027]. Age, menopausal status, breast density, mass, molecular, and pathology type were not significantly associated with non-pCR risk assessment. In a multicenter cohort of 1182 patients with pathologically confirmed BC, those with microcalcifications had a higher proportion of bone metastases compared to non-calcified BC (11.6% vs 4.9%, P < 0.001). Univariate and multivariate analysis showed that microcalcification was an independent risk factor for bone metastasis [OR = 2.550, 95%CI (1.620–4.012), P < 0.001], [OR = 2.268(1.263–4.071), P = 0.006)]. Osteolytic bone metastases predominated but there was no statistical difference between the two groups (78.9% vs 60.7%, P = 0.099). Calcified BC was mainly involved in axial bone, but was more likely to involve the whole-body bone than non-calcified BC (33.8% vs 10.7%, P = 0.021). Conclusion: This study provides important insights into the poor prognosis of microcalcification, not only in terms of poor response to NACT but also the risk factor of bone metastases. [ABSTRACT FROM AUTHOR]

Background: The prognostic role of either forkhead box A1 (FOXA1) or anterior gradient 2 (AGR2) in breast cancer has been found separately. Considering that there were interplays between them depending on ER status, we aimed to assess the statistical interaction between AGR2 and FOXA1 on breast cancer prognosis and examine the prognostic role of the combination of them by ER status. Methods: AGR2 and FOXA1 expression in tumor tissues were evaluated with tissue microarrays by immunohistochemistry in 915 breast cancer patients with follow up data. The expression levels of these two markers were treated as binary variables, and many different cutoff values were tried for each marker. Survival and Cox proportional hazard analyses were used to evaluate the relationship between AGR2, FOXA1 and prognosis, and the statistical interaction between them on the prognosis was assessed on multiplicative scale. Results: Statistical interaction between AGR2 and FOXA1 on the PFS was significant with all the cutoff points in ER-positive breast cancer patients but not ER-negative ones. Among ER-positive patients, the poor prognostic role of the high level of FOXA1 was significant only in patients with the low level of AGR2, and vice versa. When AGR2 and FOXA1 were considered together, patients with low levels of both markers had significantly longer PFS compared with all other groups. Conclusions: There was a statistical interaction between AGR2 and FOXA1 on the prognosis of ER-positive breast cancer. The combination of AGR2 and FOXA1 was a more useful marker for the prognosis of ER-positive breast cancer patients. [ABSTRACT FROM AUTHOR]

Background: For many years, the role of the microbiome in tumor progression, particularly the tumor microbiome, was largely overlooked. The connection between the tumor microbiome and the tumor genome still requires further investigation. Methods: The TCGA microbiome and genome data were obtained from Haziza et al.'s article and UCSC Xena database, respectively. Separate WGCNA networks were constructed for the tumor microbiome and genomic data after filtering the datasets. Correlation analysis between the microbial and mRNA modules was conducted to identify oncogenome associated microbiome module (OAM) modules, with three microbial modules selected for each tumor type. Reactome analysis was used to enrich biological processes. Machine learning techniques were implemented to explore the tumor type-specific enrichment and prognostic value of OAM, as well as the ability of the tumor microbiome to differentiate TP53 mutations. Results: We constructed a total of 182 tumor microbiome and 570 mRNA WGCNA modules. Our results show that there is a correlation between tumor microbiome and tumor genome. Gene enrichment analysis results suggest that the genes in the mRNA module with the highest correlation with the tumor microbiome group are mainly enriched in infection, transcriptional regulation by TP53 and antigen presentation. The correlation analysis of OAM with CD8+ T cells or TAM1 cells suggests the existence of many microbiota that may be involved in tumor immune suppression or promotion, such as Williamsia in breast cancer, Biostraticola in stomach cancer, Megasphaera in cervical cancer and Lottiidibacillus in ovarian cancer. In addition, the results show that the microbiome-genome prognostic model has good predictive value for short-term prognosis. The analysis of tumor TP53 mutations shows that tumor microbiota has a certain ability to distinguish TP53 mutations, with an AUROC value of 0.755. The tumor microbiota with high importance scores are Corallococcus, Bacillus and Saezia. Finally, we identified a potential anti-cancer microbiota, Tissierella, which has been shown to be associated with improved prognosis in tumors including breast cancer, lung adenocarcinoma and gastric cancer. Conclusion: There is an association between the tumor microbiome and the tumor genome, and the existence of this association is not accidental and could change the landscape of tumor research. [ABSTRACT FROM AUTHOR]

Introduction: Invasive breast cancer prognosis has significantly improved over time; however, there are few data about the long-term survival. Materials and methods: We analysed the data on female breast cancer incident during 2004–2005 in the area of the Tuscan Cancer Registry, distinguishing them in five subtypes, according to ER, PgR, HER2, and Ki67 expression: luminal A, luminal B, luminal B/HER2 + , triple-negative, and HER2 +. Effects of subtypes and age on 10 years breast cancer specific survival were analysed by Kaplan–Meier and multivariate Cox analysis. Results: The majority of breast cancer were luminal B (57%), and 45% of them were diagnosed at pathological stage I. The 10-year survival rates (p < 0.001) were higher among luminal A (90.2%) and lower among HER-2 + patients (70.3%). Prognostic effect of age was statistically significant (p < 0.0004): the 10-year cancer specific survival rates were higher among 40–59 years of age patients (88.5%), lower among 0–39 (75.8%). Luminal A breast cancer patients had a constant low risk throughout 10 years of follow up, while luminal B/HER2 + and triple negative tumours showed a peak 5 years after the diagnosis and then declined. Discussion: Our study confirmed the prognostic effect of biological subtype also in a long term follow up study; moreover, age at diagnosis showed to influence the outcome, other than stage at diagnosis and treatment. The long term follow up showed a constant risk of death for luminal A and B tumours, whereas for non-luminal cancer a peak 5 years after the diagnosis was found. [ABSTRACT FROM AUTHOR]

Simple Summary: There is evidence of a link between breast cancer and thyroid disease. Patients with thyroid dysfunction have an increased incidence of breast cancer compared to healthy women. Therefore, the aim of this study was to evaluate the relevant prognostic value of nuclear and cytoplasmic thyroid receptor (TR) alpha expression and its α1 and α2 isoforms in breast cancer. TRα expression was found to play a contradictory role in BC prognosis depending on its intracellular localization: our results show that TRα and TRα2 expression play different prognostic roles depending on their subcellular localization. Cytoplasmic TRα was a negative prognosticator, whereas nuclear TRα2 expression was positively associated with overall survival. This study highlights the need to further investigate the behavior of TR depending on their intracellular localization. The significance of their subcellular expression and interaction with other members of the nuclear receptor family needs to be elucidated to find new treatment options for breast cancer in the future. The aim of this retrospective study was to assess the respective prognostic values of cytoplasmic and nuclear TRα, TRα1, and TRα2 expression in breast cancer (BC) tissue samples and correlate the results with clinico-pathological parameters. In 249 BC patients, the expression patterns of general TRα and the α1 and α2 isoforms were evaluated via immuno-histochemistry. Prognosis-determining aspects were calculated via univariate, as well as multivariate, analysis. Univariate Cox-regression analysis revealed no association between nuclear TRα expression and overall survival (OS) (p = 0.126), whereas cytoplasmic TRα expression was significantly correlated with a poor outcome for both OS (p = 0.034) and ten-year survival (p = 0.009). Strengthening these results, cytoplasmic TRα was found to be an independent marker of OS (p = 0.010) when adjusted to fit clinico-pathological parameters. Analyses of the TRα-subgroups revealed that TRα1 had no prognostic relevance, whereas nuclear TRα2 expression was positively associated with OS (p = 0.014), ten-year survival (p = 0.029), and DFS (p = 0.043). Additionally, nuclear TRα2 expression was found to be an independent positive prognosticator (p = 0.030) when adjusted to fit clinico-pathological parameters. Overall, our results support the hypothesis that subcellular localization of TRα and its isoforms plays an important role in the carcinogenesis and prognosis of breast cancer. Cytoplasmic TRα expression correlates with more aggressive disease progression, whereas nuclear TRα2 expression appears to be a protective factor. These data may help us to prioritize high-risk BC subgroups for possible targeted tumor therapy. [ABSTRACT FROM AUTHOR]

Background: Breast cancer brain metastases (BCBM) are highly heterogenous with widely differing survival. The prognosis of the oligometastatic breast cancer (BC) patients with brain metastases (BM) has not been well studied. We aimed to investigate the prognosis of BCBM patients with limited intracranial and extracranial metastatic lesions. Methods: Four hundred and forty-five BCBM patients treated between 1st January 2008 and 31st December 2018 at our institute were included. Clinical characteristics and treatment information were obtained from patient's medical records. The updated breast Graded Prognostic Assessment (Breast GPA) was calculated. Results: The median OS after diagnosis of BM were 15.9 months. Median OS for patients with GPA 0–1.0, 1.5–2, 2.5–3 and 3.5–4 were 6.9, 14.2, 21.8, 42.6 months respectively. The total number of intracranial and extracranial metastatic lesions, in addition to the Breast GPA, salvage local therapy and systemic therapy (anti-HER2 therapy, chemotherapy and endocrine therapy) were demonstrated to be associated with prognosis. One hundred and thirteen patients (25.4%) had 1–5 total metastatic lesions at BM diagnosis. Patients with 1–5 total metastatic lesions had a significantly longer median OS of 24.3 months compared to those with greater than 5 total metastatic lesions with a median OS of 12.2 months (P < 0.001; multivariate HR 0.55, 95% CI, 0.43–0.72). Among the patients with 1–5 metastatic lesions, median OS for GPA 0–1.0 was 9.8 months, compared to 22.8, 28.8 and 71.0 for GPA 1.5–2.0, 2.5–3.0 and 3.5–4.0 respectively, which is much longer than the corresponding patients with greater than 5 total metastatic lesions, with medium OS of 6.8, 11.6, 18.6 and 42.6 months respectively for GPA 0–1.0, 1.5–2.0, 2.5–3.0 and 3.5–4.0. Conclusions: The patients with 1–5 total metastatic lesions demonstrated better OS. The prognostic value of the Breast GPA and the survival benefit of salvage local therapy and continuation of systemic therapy after BM were confirmed. [ABSTRACT FROM AUTHOR]

Background: Breast cancer is the most common cancer, and abnormal lipid metabolism is associated with cancer. APOD expression is negatively correlated with various cancers related to tumor prognosis. DNA methylation may affect APOD expression. Therefore, this paper aims to investigate the significance of APOD expression and APOD DNA methylation in breast cancer. Methods: This study utilized comprehensive bioinformatics analysis of APOD using Gene Expression database of Normal and Tumor tissues 2, UCSC Xena, etc. Clinical and survival information obtained from the The Cancer Genome Atlas and Gene Expression Omnibus datasets were extracted for data mining. Results: The correlation between APOD and breast cancer was examined, along with the connection between APOD DNA methylation and APOD expression. In the The Cancer Genome Atlas cohort, as well as GSE31448 and GSE65194 datasets, APOD expression decreased in breast cancer (P < 0.0001). Clinical feature analysis results showed that APOD expression was correlated with the PAM50 subtype, with the lowest expression in the Basal subtype (P < 0.0001). High APOD expression is a good prognostic marker for breast cancer (HR = 0.71, P = 0.037). APOD methylation level was significantly negatively correlated with expression level (R = -0.4770, P < 0.001), and cg15231202, cg23720929, and cg05624196 were important regulatory targets. High APOD expression was associated with higher metabolism and extracellular matrix scores. Conclusion: APOD is an independent prognostic marker for breast cancer and is regulated by DNA methylation to modulate mRNA expression. [ABSTRACT FROM AUTHOR]

Background and purpose: Human epidermal growth factor receptor 2 (HER2) is one of the main markers affecting the prognosis of breast cancer patients and the most important reference factor for the pathological classification of breast cancer. This study aimed to investigate the clinicopathological features of breast cancer with low expression of HER2 and its correlation with therapeutic effect and prognosis in neoadjuvant chemotherapy. Methods: The patients with HER2-negative breast cancer who received neoadjuvant chemotherapy in Fudan University Shanghai Cancer Center from 2009 to 2018 were retrospectively included. Clinicopathological information was collected, and the patients were divided into groups with low expression of HER2 (HER2-low) and no expression of HER2 (HER2-0), and their characteristic differences were analyzed. The independent influencing factors of pathological complete response (pCR) after neoadjuvant chemotherapy were evaluated by univariate and multifactorial methods, and the prognostic differences among different HER2 expression groups were evaluated by Kaplan-Meier curve. Results: In the 772 patients enrolled in this study, the proportion of HER2-low was significantly higher in hormonal receptor (HR) positive patients than in HR negative patients. Multivariate analysis of logistic regression model showed that tumor size (P＜0.001), HR (P=0.026) and HER2 expression (P=0.018) were independent predictors of pCR. Subgroup analysis indicated that there was no significant difference in pCR rates between HER2-0 and HER2-low triple-negative breast cancer (TNBC) (P=0.598). In Luminal breast cancer, the pCR rate of HER2-low patients was 9.4%, which was significantly lower compared with HER2-0 patients (19.3%, P=0.003). In the survival analysis of non-pCR patients, the prognosis of HER2-low patients was significantly better compared with HER2-0 patients (P＜0.001), and the 5-year survival rate was 72.2%, while the 5-year survival rate of HER2-0 patients was only 56.0%. Conclusion: HER2-negative patients with different expressions of HER2 protein have different clinicopathological characteristics, which are related to the chemotherapy sensitivity and prognosis of patients. [ABSTRACT FROM AUTHOR]

Simple Summary: YY1 and CP2c is a transcription factor that regulates epigenetic pathways and protein modifications among several kinds of cancer. However, it is still unknown whether YY1 expression has any prognostic significance in patients with breast cancer. Thus, we investigated YY1 expression in association with CP2c in breast cancer patients and their prognostic implications. In this study, quantitative analysis of YY1 and CP2c expression in tumors revealed a negative correlation between them. Patients with YY1-high/CP2c-low expression showed the most favorable survival outcomes. YY1 overexpression was found to be significantly associated with a better prognosis after multivariate analysis. Our study provides novel findings about the association between YY1 and CP2c and its prognostic implication in breast cancer through quantitative analysis at the transcriptome and protein levels. Yin Yang 1 (YY1) is a transcription factor that regulates epigenetic pathways and protein modifications. CP2c is a transcription factor that functions as an oncogene to regulate cell proliferation. YY1 is known to interact with CP2c to suppress CP2c's transcriptional activity. This study aimed to investigate YY1 and CP2c expression in breast cancer and prognostic implications. In this study, YY1 and CP2c expression was evaluated using immunohistochemical staining, Western blot and RT-PCR assays. Of 491 patients with primary breast cancer, 138 patients showed YY1 overexpression. Luminal subtype and early stage were associated with overexpression (p < 0.001). After a median follow-up of 68 months, YY1 overexpression was found to be associated with a better prognosis (disease-free survival rates of 92.0% vs. 79.2%, p = 0.014). In Cox proportional hazards model, YY1 overexpression functioned as an independent prognostic factor after adjustment of hormone receptor/HER2 status and tumor size (hazard ratio of 0.50, 95% CI 0.26–0.98, p = 0.042). Quantitative analysis of YY1 and CP2c protein expression in tumors revealed a negative correlation between them. In conclusion, YY1 overexpression is a favorable prognostic biomarker in patients with breast cancer, and it has a negative correlation with CP2c at the protein level. [ABSTRACT FROM AUTHOR]

Triple-negative breast cancer (TNBC) is a subtype of breast cancer with poor prognosis. Therefore, there is an urgent need to identify prognostic markers to improve current treatment and therapeutic strategies. The transcriptional factor ZNF503 has been reported to promote aggressive breast cancer development through the down-regulation of GATA3 expression and has been identified as a candidate predictive marker. In this study, we explored whether ZNF503 and GATA3 could serve as prognostic markers independently or in combination. We performed a survival analysis of 989 breast cancer patients from The Cancer Genome Atlas (TCGA), and validated the findings in 202 breast cancer patients from tissue microarray (TMA). In TCGA database, the mRNA expression of GATA3 and ZNF503 could not predict TNBC prognosis alone, though the ratio index, ZNF503/GATA3 could be a novel prognostic biomarker in TNBC patients. In TMA database, we detected the protein expression of ZNF503 and GATA3 and found that the combination of the two genes, ZNF503-GATA3, significantly improved the predictive ability of clinical outcomes. The results indicated that the binding index of ZNF503 and GATA3 could be used as a prognostic biomarker in TNBC. [ABSTRACT FROM AUTHOR]

Background: Breast cancer is a malignant tumour that seriously threatens women's life and health and exhibits high inter-individual heterogeneity, emphasising the need for more in-depth research on its pathogenesis. While internal 7-methylguanosine (m7G) modifications affect RNA processing and function and are believed to be involved in human diseases, little is currently known about the role of m7G modification in breast cancer. Methods and Results: We elucidated the expression, copy number variation incidence and prognostic value of 24 m7G-related genes (m7GRGs) in breast cancer. Subsequently, based on the expression of these 24 m7GRGs, consensus clustering was used to divide tumour samples from the TCGA-BRCA dataset into four subtypes based on significant differences in their immune cell infiltration and stromal scores. Differentially expressed genes between subtypes were mainly enriched in immune-related pathways such as 'Ribosome', 'TNF signalling pathway' and 'Salmonella infection'. Support vector machines and multivariate Cox regression analysis were applied based on these 24 m7GRGs, and four m7GRGs—AGO2, EIF4E3, DPCS and EIF4E—were identified for constructing the prediction model. An ROC curve indicated that a nomogram model based on the risk model and clinical factors had strong ability to predict the prognosis of breast cancer. The prognoses of patients in the high- and low-TMB groups were significantly different (p = 0.03). Moreover, the four-gene signature was able to predict the response to chemotherapy. Conclusions: In conclusion, we identified four different subtypes of breast cancer with significant differences in the immune microenvironment and pathways. We elucidated prognostic biomarkers associated with breast cancer and constructed a prognostic model involving four m7GRGs. In addition, we predicted the candidate drugs related to breast cancer based on the prognosis model. [ABSTRACT FROM AUTHOR]

Simple Summary: The Oncotype DX recurrence score is widely used to help clinicians treat patients with early-stage breast cancer. However, the threshold at which the Oncotype DX score is used to guide chemotherapy treatment may vary for different patient groups, and the present study describes a machine learning method to quantitatively determine the optimal chemotherapy sensitivity threshold. Utilizing publicly available breast cancer survival data, we demonstrated that 2.05–2.72x more lymph-node-negative and 2.08–5.02x more lymph-node-positive patients may benefit from receiving chemotherapy at a lower Oncotype DX score than current guidelines (RS > 25 or RS > 30) suggest. Additionally, our models indicate a racial difference in chemotherapy benefit that may help physicians provide tailored treatment to specific patients. Specifically, white, black, and Asian women with early-stage ER+/HER2−/LN− tumors may benefit from chemotherapy when their Oncotype DX scores are greater than 19.9, 37.2, and 18.0, respectively. Background: Oncotype DX assay, a multigene molecular test, has been widely used to stratify relapse risk and guide chemotherapy treatment in breast cancer. However, the optimal threshold of the Oncotype DX score in predicting chemotherapy benefit and its racial variation has not been investigated. Methods: In this study, we apply a random forest survival model to the SEER-Oncotype cohort data (Surveillance, Epidemiology, and End Results with Oncotype DX test information for breast cancer patients) and determine chemotherapy benefit thresholds in early-stage, estrogen-receptor-positive (ER+), and HER2-negative (HER2−) patients of different races. Results: Our results indicate that early-stage ER+, HER2−, and LN−/LN+ patients may benefit from receiving chemotherapy at a lower Oncotype DX score than current guidelines (Recurrence Score, RS > 25 or RS > 30) suggest. According to the estimated chemotherapy sensitivity thresholds from our models, 2.05–2.72-fold more lymph-node-negative (LN−) and 2.08–5.02-fold more lymph-node-positive (LN+) patients who may not currently be recommended for chemotherapy by their Oncotype DX test result may actually have the potential to benefit from chemotherapy. Furthermore, our models indicate a racial difference in chemotherapy benefit: white, black, and Asian women with early-stage ER+/LN− tumors benefit from chemotherapy when their Oncotype DX scores are greater than 19.9, 37.2, and 18.0, respectively. Conclusions: Our study provides a method for calibrating multigene molecular tests to help guide treatment decisions in racially and ethnically diverse patients with cancer. Specifically, we identify key chemotherapy sensitivity thresholds for the Oncotype DX recurrence score test in breast cancer patients and provide evidence that certain patients may benefit from receiving chemotherapy at a lower threshold than the current clinical guidelines suggest. [ABSTRACT FROM AUTHOR]

Simple Summary: We have previously shown that the glucocorticoid receptor (GCR) protein was reduced in invasive breast carcinoma compared to normal breast tissue. Here, we evaluated the level of serum/glucocorticoid-regulated kinase 1 (SGK1) and B-cell lymphoma 2 (Bcl-2) levels in the corresponding primary breast cancer tissue. SGK1 was higher and Bcl-2 was lower in breast cancer tissue compared to normal breast tissue. Similar to previous reports, we found that the expression of the Bcl-2 protein was associated with longer survival. We observed a correlation between the expression of the GCR and the Bcl-2 protein. The expression of the Bcl-2 protein was higher among cases who self-reported their race and ethnicity as non-Hispanic Black people. It is crucial to understand molecular alterations in breast cancer and how they relate to clinicopathologic factors. We have previously shown that the glucocorticoid receptor (GCR) protein expression was reduced in invasive breast carcinoma compared to normal breast tissue. Glucocorticoids, signaling through the GCR, regulate several cellular processes via downstream targets such as serum/glucocorticoid-regulated kinase 1 (SGK1) and B-cell lymphoma 2 (Bcl-2). We measured the expression of SGK1 and Bcl-2, in respective breast cancer tissue arrays, from a multiracial cohort of breast cancer patients. Higher cytoplasmic SGK1 staining was stronger in breast cancer tissue compared to normal tissue, especially in hormone receptor-negative cases. Conversely, the expression of cytoplasmic Bcl-2 was reduced in breast cancer compared to normal tissue, especially in hormone receptor-negative cases. Bcl-2 staining was associated with the self-reported racial/ethnic category, an earlier clinical stage, a lower histological grade, and a higher survival rate. Bcl-2 expression was associated with longer survival in models adjusted for age and race (HR = 0.32, 95% CI: 0.15, 0.65), and Bcl-2 expression remained strongly positively associated with protection from breast cancer death, with additional adjustments for ER/PR status (HR = 0.41, 95% CI: 0.2, 0.85). SGK1 and Bcl-2 may play biological roles in breast cancer development and/or progression. [ABSTRACT FROM AUTHOR]

Simple Summary: Currently, breast cancer diagnostics do not have readily available diagnostic and prognostic tools, especially in the early stages of the disease. Therefore, there is a constant need to search for tumor markers that can improve current diagnostics. One such molecule that may be a potential marker could be among a group of chemokines. In this work, we summarize reports that evaluate the expression and peripheral blood concentration of ELR-positive CXC chemokines as potential markers and prognostic factors for breast cancer. As the most common type of malignant lesison, breast cancer is a leading challenge for clinicians. Currently, diagnosis is based on self-examination and imaging studies that require confirmation by tissue biopsy. However, there are no easily accessible diagnostic tools that can serve as diagnostic and prognostic markers for breast cancer patients. One of the possible candidates for such markers is a group of chemokines that are closely implicated in each stage of tumorigenesis. Many researchers have noted the potential of this molecule group to become tumor markers and have tried to establish their clinical utility. In this work, we summarize the results obtained by scientists on the usefulness of the ELR-positive CXC group of chemokines in ancillary diagnosis of breast cancer. [ABSTRACT FROM AUTHOR]

Traditional imaging techniques for breast cancer (BC) diagnosis and prediction, such as X-rays and magnetic resonance imaging (MRI), demonstrate varying sensitivity and specificity due to clinical and technological factors. Consequently, positron emission tomography (PET), capable of detecting abnormal metabolic activity, has emerged as a more effective tool, providing critical quantitative and qualitative tumor-related metabolic information. This study leverages a public clinical dataset of dynamic 18F-Fluorothymidine (FLT) PET scans from BC patients, extending conventional static radiomics methods to the time domain—termed as 'Dynomics'. Radiomic features were extracted from both static and dynamic PET images on lesion and reference tissue masks. The extracted features were used to train an XGBoost model for classifying tumor versus reference tissue and complete versus partial responders to neoadjuvant chemotherapy. The results underscored the superiority of dynamic and static radiomics over standard PET imaging, achieving accuracy of 94% in tumor tissue classification. Notably, in predicting BC prognosis, dynomics delivered the highest performance, achieving accuracy of 86%, thereby outperforming both static radiomics and standard PET data. This study illustrates the enhanced clinical utility of dynomics in yielding more precise and reliable information for BC diagnosis and prognosis, paving the way for improved treatment strategies. [ABSTRACT FROM AUTHOR]

Breast cancer is categorized as an aggressive disease, and it is one of the leading causes of death. Accurate survival predictions for both long-term and short-term survivors, when delivered on time, can help physicians make effective treatment decisions for their patients. Therefore, there is a dire need to design an efficient and rapid computational model for breast cancer prognosis. In this study, we propose an ensemble model for breast cancer survivability prediction (EBCSP) that utilizes multi-modal data and stacks the output of multiple neural networks. Specifically, we design a convolutional neural network (CNN) for clinical modalities, a deep neural network (DNN) for copy number variations (CNV), and a long short-term memory (LSTM) architecture for gene expression modalities to effectively handle multi-dimensional data. The independent models' results are then used for binary classification (long term > 5 years and short term < 5 years) based on survivability using the random forest method. The EBCSP model's successful application outperforms models that utilize a single data modality for prediction and existing benchmarks. [ABSTRACT FROM AUTHOR]

Background: The changes in prognostic factors and clinicopathological characteristics of residual disease following neoadjuvant therapy (NAT) for breast cancer are important references for postoperative adjuvant therapy. The analyses of the relationship between the clinicopathological characteristics of residual diseases and the prognosis were not comprehensive in most previous studies. This study aimed to determine how prognostic factors changed following NAT and the impact of clinicopathological characteristics of residual disease on the prognosis of human epidermal growth factor receptor 2 (HER2)-positive breast cancer. Methods: The study comprised 350 consecutive patients with HER2-positive breast cancer who had residual disease after surgery following NAT. The independent risk factors affecting the prognosis of HER2-positive breast cancer were analyzed using univariate and multivariate Cox regression analyses. Chi-square test and binary logistic regression were used to analyze the influencing factors of HER2 loss following NAT. Results: The expression of prognostic factors changed significantly following NAT. A total of 44 patients (12.6%) had HER2 loss. HER2 status (immunohistochemistry (IHC) 3+ vs. IHC 2+/FISH+, p < 0.001) at baseline was associated with HER2 loss. In this investigation, the HER2 loss did not affect the prognosis. In univariate analysis, the decrease in Ki-67 (p < 0.001) after NAT was associated with improved prognosis, but this influence was lost in the Cox proportional hazards model. The ypN stage (p < 0.001), postoperative ER status (p = 0.020), Miller-Payne grade (p = 0.007), and targeted therapy (p = 0.003) were all independent prognostic factors. Conclusions: ER, PR, HER2, and Ki-67 changed significantly after NAT, but no impact of these changes on DFS was observed in this study. Postoperative N stage, postoperative ER status, MP grade, and targeted therapy were independent prognostic factors in patients with HER2-positive breast cancer after NAT. [ABSTRACT FROM AUTHOR]

Simple Summary: Breast cancer is one of the most common malignant tumors in women, and metastatic breast cancer usually has a poor prognosis. Hence, it is urgent to identify new biomarkers to promote precise medication in breast cancer. LHX2 has been reported to promote the proliferation of numerous solid tumors, but its role in breast cancer has not been elucidated. Our study explored the prognostic value and the immune cell infiltration of breast cancer related to LHX2. We found that LHX2 can serve as an independent prognostic factor in breast cancer. In vitro and in vivo experiments confirmed that LHX2 promoted cell proliferation, migration ability, and invasive ability but inhibited apoptosis in breast cancer. Immunohistochemistry and immunofluorescence experiments were conducted to investigate LHX2-related immune infiltration in breast cancer tissues. A Western blot assay proved that LHX2 activated the PI3K/AKT/mTOR pathway and the apoptosis pathway. Worldwide, breast cancer is the most common malignancy. LHX2, a member of the LIM homeobox gene family and a transcription factor, plays a crucial role in numerous tumors, but the function of LHX2 in breast cancer progression remains unknown. In this study, we show that LHX2 is upregulated in breast cancer tissues and positively correlated with breast cancer progression. Meanwhile, the clinical characteristics of breast cancer and LHX2 expression showed a strong correlation. GSEA showed that a high LHX2 expression may activate the T-cell activation pathway, PI3K/AKT/mTOR signaling pathway, and apoptosis pathway. Moreover, ssGSEA showed that Th1 cells and Th2 cells had a positive correlation with LHX2 expression in breast cancer. Experiments showed that LHX2 promotes the proliferation, colony formation, migration, and invasion of breast cancer cells. Immunohistochemistry and immunofluorescence assays helped to analyze LHX2-associated immune infiltration in breast cancer. A Western blot assay proved that LHX2 activated the PI3K/AKT/mTOR pathway and the apoptosis pathway. A TUNEL assay confirmed that LHX2 inhibited apoptosis. Taken together, LHX2 plays a vital role in breast cancer's progression and prognosis and could be an immune infiltration biomarker for breast cancer, and LHX2 activates the PI3K/AKT/mTOR pathway and apoptosis pathway in breast cancer. [ABSTRACT FROM AUTHOR]