Prognostic Factor In Breast Cancer Research Articles

Lymphovascular invasion is an independent prognostic factor in breast cancer irrespective of axillary node metastasis and molecular subtypes.

Lymphovascular invasion (LVI) is a well-known poor prognostic factor for early breast cancer. However, the effect of LVI on breast cancer subtype and node status remains unknown. In this study, we aimed to evaluate the clinical significance of LVI on the recurrence and long-term survival of patients with early breast cancer by comparing groups according to the subtype and node status. We retrospectively reviewed the medical records of 4554 patients with breast cancer who underwent breast cancer surgery between January 2010 and December 2017. The primary endpoints were disease-free survival (DFS) and overall survival (OS). Univariate and multivariate analyses were performed to identify prognostic factors related to the DFS and OS according to the nodal status and breast cancer subtype. During a follow-up period of 94 months, the median OS and DFS were 92 and 90 months, respectively. The LVI expression rate was 8.4%. LVI had a negative impact on the DFS and OS, regardless of the lymph node status. LVI was associated with higher recurrence and lower survival in the luminal A, human epidermal growth factor receptor 2-positive, and triple-negative breast cancer subtypes. The Cox proportional hazards model showed that LVI was a significant prognostic factor for both DFS and OS. No correlation has been observed between LVI and the Oncotype Dx results in terms of prognostic value in early breast cancer. LVI is an independent poor prognostic factor in patients with early breast cancer, regardless of the node status and molecular subtype. Therefore, the LVI status should be considered when making treatment decisions for patients with early stage breast cancer; however, further prospective studies are warranted.

The Impact of Being Underweight on the Prognosis of Older Patients With Early Breast Cancer.

The number of older patients with breast cancer has been increasing and a major challenge is to develop optimal treatment strategies for these patients, who often have comorbidities. Obesity is reportedly a poor prognostic factor in breast cancer, however there is limited research on underweight patients. Clarifying the relationship between physique and prognosis may contribute to the establishment of optimal treatment strategies for older patients with breast cancer. This retrospective study examined clinicopathological data from a multicenter collaborative database on 1,076 patients aged 70 years or older who had undergone curative surgery. According to the body mass index (BMI), patient physique was defined as underweight (<18.5 kg/m2), normal (18.5-24.9 kg/m2) or obese (≥25 kg/m2). In this study, we explored the relationship between the physique of patients with breast cancer and outcomes. Underweight patients had a significantly lower rate of chemotherapy administration (p=0.017) and a higher rate of presence of other cancer (p=0.022). During the observation period (median of 75.2 months), 133 patients (12%) developed recurrent disease and 131 patients (12%) died. Age, BMI, tumor size, progesterone receptor and the presence of other cancer were independent factors relating to overall survival (p<0.001, p=0.027, p=0.002, p=0.008 and p=0.005, respectively). Patients with a low BMI had a significantly shorter overall survival, but there was no association with disease-free survival in this subset of patients. Overall survival was shorter in underweight older patients with breast cancer. Our data indicate that being underweight should be considered both in treatment decisions and in future studies of outcomes for older patients with breast cancer.

Assessing the relationship between tumor proliferation and prognosis in breast cancer patients: A pathological analysis

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.

Predicting diagnosis and survival of bone metastasis in breast cancer using machine learning

This study aimed at establishing more accurate predictive models based on novel machine learning algorithms, with the overarching goal of providing clinicians with effective decision-making assistance. We retrospectively analyzed the breast cancer patients recorded in the Surveillance, Epidemiology, and End Results (SEER) database from 2010 to 2016. Multivariable logistic regression analyses were used to identify risk factors for bone metastases in breast cancer, whereas Cox proportional hazards regression analyses were used to identify prognostic factors for breast cancer with bone metastasis (BCBM). Based on the identified risk and prognostic factors, we developed diagnostic and prognostic models that incorporate six machine learning classifiers. We then used the area under the receiver operating characteristic (ROC) curve (AUC), learning curve, precision curve, calibration plot, and decision curve analysis to evaluate performance of the machine learning models. Univariable and multivariable logistic regression analyses showed that bone metastases were significantly associated with age, race, sex, grade, T stage, N stage, surgery, radiotherapy, chemotherapy, tumor size, brain metastasis, liver metastasis, lung metastasis, breast subtype, and PR. Univariate and multivariate Cox regression analyses revealed that age, race, marital status, grade, surgery, radiotherapy, chemotherapy, brain metastasis, liver metastasis, lung metastasis, breast subtype, ER, and PR were closely associated with the prognosis of BCBM. Among the six machine learning models, the XGBoost algorithm predicted the most accurate results (Diagnostic model AUC = 0.98; Prognostic model AUC = 0.88). According to the Shapley additive explanations (SHAP), the most critical feature of the diagnostic model was surgery, followed by N stage. Interestingly, surgery was also the most critical feature of prognostic model, followed by liver metastasis. Based on the XGBoost algorithm, we could effectively predict the diagnosis and survival of bone metastasis in breast cancer and provide targeted references for the treatment of BCBM patients.

Circulating neutrophils from patients with early breast cancer have distinct subtype-dependent phenotypes

PurposeAn elevated number of circulating neutrophils is a poor prognostic factor for breast cancer, where evidence of bone marrow cancer-dependent priming is found. However, how early this priming is detectable remains unclear.Patients and methodsHere, we investigate changes in circulating neutrophils from newly diagnosed breast cancer patients before any therapeutic interventions. To do this, we assessed their lifespan and their broader intracellular kinase network activation states by using the Pamgene Kinome assay which measures the activity of neutrophil kinases.ResultsWe found sub-type specific L-selectin (CD62L) changes in circulating neutrophils as well as perturbations in their overall global kinase activity. Strikingly, breast cancer patients of different subtypes (HR+, HER2+, triple negative) exhibited distinct neutrophil kinase activity patterns indicating that quantifiable perturbations can be detected in circulating neutrophils from early breast cancer patients, that are sensitive to both hormonal and HER-2 status. We also detected an increase in neutrophils lifespan in cancer patients, independently of tumour subtype.ConclusionsOur results suggest that the tumour-specific kinase activation patterns in circulating neutrophils may be used in conjunction with other markers to identify patients with cancer from those harbouring only benign lesions of the breast. Given the important role neutrophil in breast cancer progression, the significance of this sub-type of specific priming warrants further investigation.

Our house believes that: The clipped lymph node is the true sentinel node after neoadjuvant chemotherapy in N+ patients

Axillary staging is an important prognostic factor in breast cancer, being sentinel lymph node biopsy (SLNB) the gold standard staging method in early stages. However, in clinically node positive (cN+) patients who converted to clinically node-negative (cN0) after primary systemic therapy (PST) the axillary staging method during surgery remains controversial. There are at least three validated methods: SLNB, targeted axillary dissection (TAD) and marking axillary nodes with radioactive iodine seeds (MARI) procedure. Our house believe that the biopsied and clipped lymph node could predict response to systemic treatment.

Evaluation Factors Affecting on Recurrence, Metastasis, and Survival of Breast Cancer in Iranian Women by Multi-State Model Approach.

We used the multistate model to investigate how prognostic factors of breast cancer are seen to affect the disease process. This cohort study was conducted at Motamed Cancer Institute of Tehran, Iran on 2363 breast cancer patients admitted from 1978 to 2017, and they were followed up until 2018. We applied the multistate models, including four states: diagnosis, recurrence, metastasis, and final absorbing mortality state. Age over 50 years, positive lymph nodes and tumor size intensified the hazard of transition from diagnosis to metastasis (P=0.002, P<0.001 and P=0.001 respectively) and they also intensified the hazard of transition from diagnosis to mortality (P=0.010, P<0.001 and P<0.001 respectively). At the same time, the educational level decreased the hazard of mentioned transitions (P<0.001). Positive estrogen receptors reduced the hazard of transition from diagnosis to metastasis (P=0.007) and positive lymph nodes also intensified the hazard of transition from metastasis to mortality (P=0.040). Tumor size had an increasing role in the transitions from diagnosis to recurrence, recurrence to metastasis, and metastasis to mortality (P=0.014, P=0.018 and P=0.002 respectively). Multistate model presented the detailed effects of prognostic factors on progression of breast cancer. Implementing early diagnosis strategies and providing informational programs, especially in younger ages and lower educational level patients may be helpful in reducing the hazard of transition to higher states of breast cancer and increasing the survival of Iranian women with breast cancer by controlling tumor size growth, lymph nodes involvements and estrogen receptor status.

Ki-67 Index and Its Correlation with Clinical and Pathological Variables in Breast Cancer.

The role of the Ki-67 index as a prognostic marker in breast cancer is controversial. This study was undertaken to assess the association of Ki-67 index with other clinicopathological factors in breast cancer. The prospectively conducted study included 127 female patients with clinical tumor stage 1-3 and nodal stage 0 or 1 treated between March 2015 and March 2017. Ki-67 index was correlated with age, tumor size, lymph node status, histological grade, ER, PR, HER2, and molecular subtypes using Chi-square or Fisher's exact test. Mean age of the patients was 53.28 years (range, 25-86 years). Mean Ki-67 index was 33.59 (range, 2.5-95). Ki-67 index showed a positive correlation with pathological stage (p=0.025), grade (p=0.0001), and molecular subtype (p=0.0001) of the tumor. It was inversely associated with ER (p=0.0001) and PR status (p=0.0001). Its association with pathological nodal status (p=0.06) and size (p=0.08) of the tumor was not statistically significant. There was no correlation with age (p=0.892) and HER2 status (p=0.287). Association of the Ki-67 index with common prognostic factors such as grade, stage, ER, PR, and molecular subtype suggests its role as a prognostic factor in breast cancer.

SAMHD1 expression is a surrogate marker of immune infiltration and determines prognosis after neoadjuvant chemotherapy in early breast cancer.

The lack of validated surrogate biomarkers is still an unmet clinical need in the management of early breast cancer cases that do not achieve complete pathological response after neoadjuvant chemotherapy (NACT). Here, we describe and validate the use of SAMHD1 expression as a prognostic biomarker in residual disease in vivo and in vitro. SAMHD1 expression was evaluated in a clinical cohort of early breast cancer patients with stage II-III treated with NACT. Heterotypic 3D cultures including tumor and immune cells were used to investigate the molecular mechanisms responsible of SAMHD1 depletion through whole transcriptomic profiling, immune infiltration capacity and subsequent delineation of dysregulated immune signaling pathways. SAMHD1 expression was associated to increased risk of recurrence and higher Ki67 levels in post-NACT tumor biopsies of breast cancer patients with residual disease. Survival analysis showed that SAMHD1-expressing tumors presented shorter time-to-progression and overall survival than SAMHD1 negative cases, suggesting that SAMHD1 expression is a relevant prognostic factor in breast cancer. Whole-transcriptomic profiling of SAMHD1-depleted tumors identified downregulation of IL-12 signaling pathway as the molecular mechanism determining breast cancer prognosis. The reduced interleukin signaling upon SAMHD1 depletion induced changes in immune cell infiltration capacity in 3D heterotypic in vitro culture models, confirming the role of the SAMHD1 as a regulator of breast cancer prognosis through the induction of changes in immune response and tumor microenvironment. SAMHD1 expression is a novel prognostic biomarker in early breast cancer that impacts immune-mediated signaling and differentially regulates inflammatory intra-tumoral response.

Validation of PREDICT Version 2.2 in a Retrospective Cohort of Indian Women With Operable Breast Cancer.

Online prediction models that use known prognostic factors in breast cancer (BC) are routinely used to assist in decisions for adjuvant therapy. PREDICT Version 2.2 (P2.2) is one such online tool, which uses tumor size, lymph node involvement, grade, age, hormone receptor status, human epidermal growth factor receptor 2 (HER2) status, and Ki67. We performed an external validation in a retrospective cohort of patients treated at a tertiary center in India. Women with operable BC between 2008 and 2016 with nonmetastatic, T1-T2 invasive, and HER2 receptor-negative BC and with available 5-year overall survival (OS) data were selected. Median predicted 5-year OS rates were used to calculate predicted events for the whole cohort and subgroups. The chi-square test was used to evaluate the goodness of fit of the tool. Of 11,760 cases registered between 2008 and 2016, 2,783 (23.66%) eligible patients with a median age of 50 (26-70) years and a median pT size of 2.5 (0.1-5) cm, 2,037 (73.19%) with grade 3 tumors, 1,172 (42.11%) with node-positive disease, 817 (29.35%) with triple-negative breast cancer, and 1,966 (70.64%) with HR-positive BC were included in the analysis. The observed 5-year OS and predicted 5-year OS in the whole cohort were 94.8% and 90.00%, respectively, with an absolute difference of 4.8% (95% CI, 3.417 to 6.198, P < .001). The observed 5-year OS and predicted 5-year OS were also different in various subgroups. PREDICT version 2.2 overestimated the number of deaths, with lower predicted 5-year OS compared with the observed value, in this retrospective Indian cohort. The reasons for this discrepancy could be differing biologic characteristics and possible selection bias in our cohort. We recommend a prospective validation of PREDICT in Indian patients and advocate caution in its use until such validation is achieved.

Lateral interactions between CD276 and CD147 are essential for stemness in breast cancer: a novel insight from proximal proteome analysis

Oncogenic cell-surface membrane proteins contribute to the phenotypic and functional characteristics of cancer stem cells (CSCs). We employed a proximity-labeling proteomic approach to quantitatively analyze the cell-surface membrane proteins in close proximity to CD147 in CSCs. Furthermore, we compared CSCs to non-CSCs to identify CSC-specific cell-surface membrane proteins that are closely interact with CD147 and revealed that lateral interaction between CD147 and CD276 concealed within the lipid raft microdomain in CSCs, confers resistance to docetaxel, a commonly used chemotherapy agent for various cancer types, including metastatic breast cancer. Moreover, we investigated the clinical relevance of CD147 and CD276 co-expression in HER2+ breast cancer (BC) and triple-negative breast cancer patients who underwent chemotherapy. We observed poor disease-free survival and Overall survival rates in patients of CD147 and CD276 (p = 0.04 and 0.08, respectively). Subsequent immunohistochemical analysis in independent cohorts of HER2+ BC support for the association between co-expression of CD147 and CD276 and a poor response to chemotherapy. Collectively, our study suggests that the lateral interaction between CD147 and its proximal partners, such as CD276, may serve as a poor prognostic factor in BC and a predictive marker for the critical phenotypic determinant of BC stemness.

Exploring the most appropriate lymph node staging system for node-positive breast cancer patients and constructing corresponding survival nomograms.

The lymph node (LN) status is a crucial prognostic factor for breast cancer (BC) patients. Our study aimed to compare the predictive capabilities of three different LN staging systems in node-positive BC patients and develop nomograms to predict overall survival (OS). We enrolled 71,213 eligible patients from the SEER database, and 667 cases from our hospital were used for external validation. All patients were divided into two groups based on the number of removed lymph nodes (RLNs). The prognostic abilities of pN stage, positive LN ratio (LNR), and log odds of positive LN (LODDS) were compared using the C-indexes and AUC values. LASSO regression was performed to identify significant factors associated with prognosis and develop corresponding nomogram models. Our study found that LNR had superior predictive performance compared to pN and LODDS among patients with RLNs < 10, while pN performed better in patients with RLNs ≥ 10. In the training set, the nomogram models exhibited excellent clinical applicability, as evidenced by the C-indexes, ROC curves, calibration plots, and decision curve analysis curves. Moreover, the nomogram classification accurately differentiated risk subgroups and improved discrimination. These results were externally validated in the validation cohort. Physicians should select different LN staging systems based on the number of RLNs. Our novel nomograms demonstrated excellent performance in both internal and external validations, which may assist in patient counseling and guide treatment decision-making.

Molecular characterization of breast cancer cell pools with normal or reduced ability to respond to progesterone: a study based on RNA-seq

BackgroundAbout one-third of patients with estrogen receptor alpha (ERα)-positive breast cancer have tumors which are progesterone receptor (PR) negative. PR is an important prognostic factor in breast cancer. Patients with ERα-positive/PR-negative tumors have shorter disease-free and overall survival than patients with ERα-positive/PR-positive tumors. New evidence has shown that progesterone (P4) has an anti-proliferative effect in ERα-positive breast cancer cells. However, the role of PR in breast cancer is only poorly understood. MethodsWe disrupted the PR gene (PGR) in ERα-positive/PR-positive T-47D cells using the CRISPR/Cas9 system. This resulted in cell pools we termed PR-low as P4 mediated effects were inhibited or blocked compared to control T-47D cells. We analyzed the gene expression profiles of PR-low and control T-47D cells in the absence of hormone and upon treatment with P4 alone or P4 together with estradiol (E2). Differentially expressed (DE) genes between experimental groups were characterized based on RNA-seq and Gene Ontology (GO) enrichment analyses. ResultsThe overall gene expression pattern was very similar between untreated PR-low and untreated control T-47D cells. More than 6000 genes were DE in control T-47D cells upon stimulation with P4 or P4 plus E2. When PR-low pools were subjected to the same hormonal treatment, up- or downregulation was either blocked/absent or consistently lower. We identified more than 3000 genes that were DE between hormone-treated PR-low and control T-47D cells. GO analysis revealed seven significantly enriched biological processes affected by PR and associated with G protein-coupled receptor (GPCR) pathways which have been described to support growth, invasiveness, and metastasis in breast cancer cells. ConclusionsThe present study provides new insights into the complex role of PR in ERα-positive/PR-positive breast cancer cells. Many of the genes affected by PR are part of central biological processes of tumorigenesis.

Overexpression of ferritin light chain as a poor prognostic factor for breast cancer.

Ferritin light chain (FTL) is involved in tumor progression, but the specific molecular processes by which FTL affects the development of breast cancer (BRCA) have remained unknown. In this research, the clinicopathological significance of FTL overexpression in BRCA was investigated. To investigate the role of FTL in BRCA, we utilized multiple online databases to analyse FTL expression levels in BRCA. Next, we reviewed the expression and localization of the FTL protein in BRCA by immunohistochemistry (IHC), Western blot (WB) and immunofluorescence (IF) staining. To assess the impact of FTL on patient prognosis, we conducted Kaplan‒Meier, univariate and multivariate survival analyses. The relationship between FTL and immune infiltration in BRCA was also analysed in the TISCH and SangerBox databases. MTT, malondialdehyde (MDA) and reactive oxygen species (ROS) assays were carried out to investigate the molecular mechanisms of FTL action in BRCA cells. FTL was significantly upregulated in BRCA compared to normal tissues. Its expression significantly linked to histological grade (P = 0.038), PR expression (P = 0.021), Her2 expression (P = 0.012) and Ki-67 expression (P = 0.040) in patients with BRCA. Furthermore, the expression of the FTL protein was higher in the BRCA cell lines than in the normal breast cells and mainly localized in the cytoplasm. Compared to patients with a low level of FTL expression, patients with a high level of FTL expression showed lower overall survival (OS). More convincingly, univariate and multivariate statistical analyses revealed that FTL expression (P = 0.000), ER expression (P = 0.036) and Her2 expression (P = 0.028) were meaningful independent prognostic factors in patients with BRCA. FTL was associated with immune infiltration in BRCA. Functional experiments further revealed that FTL knockdown inhibited the capacity of proliferation and increased the level of oxidative stress in BRCA cells. Overexpression of FTL was associated with the progression of BRCA. FTL overexpression may become a biomarker for the evaluation of poor prognosis in patients with BRCA.

Comprehensive Analysis of SLC35A2 in Pan-Cancer and Validation of Its Role in Breast Cancer.

Elucidation of the oncogenic role of SLC35A2 in human tumors and the potential function and clinical significance in breast cancer. Pan-cancer analysis was performed via various bioinformatics tools to explain the pathogenic role of SLC35A2. A prognostic nomogram was also developed based on the SLC35A2 expression and clinicopathological characteristics in breast cancer patients. In addition, the role of SLC35A2 was validated in breast cancer by in vivo and in vitro experiments. SLC35A2 expression is increased in 27 tumor types, and its high expression is substantially correlated with poor prognosis in patients with a variety of cancers. Receiver operating characteristic (ROC) curves showed that SLC35A2 expression levels could accurately distinguish most tumor tissues from normal tissues. High SLC35A2 expression was linked to increased immune infiltration in myeloid-derived suppressor cells (MDSC), as well as immune checkpoints, ferroptosis-related genes, tumor mutational burden (TMB), and microsatellite instability (MSI). SLC35A2 may be involved in tumorigenesis by regulating the glycosylation process. Furthermore, multivariate Cox analysis showed that SLC35A2 was an independent prognostic factor for breast cancer. And the nomogram model had good predictive accuracy for the prognosis of breast cancer patients. Meanwhile, cellular experiments demonstrated that knockdown of SLC35A2 could significantly inhibit the proliferation, migration and invasion of breast cancer cells, while increasing the protein level of E-cadherin and decreasing N-cadherin. A nude mouse xenograft model showed that inhibition of SLA35A2 expression could significantly inhibit tumor growth. SLC35A2 has good diagnostic and prognostic values in multiple cancers and is closely related to tumor immune infiltration. In addition, SLA35A2 as an oncogene in breast cancer may be involved in the progression of epithelial mesenchymal transition (EMT).

ASSOCIATION OF TOLL-LIKE RECEPTOR 9 EXPRESSION WITH PROGNOSIS IN BREAST CARCINOMA

Aim:&#x0D; Breast cancer (BC) is a common malignancy in women. Some molecules including TLR9 are still under investigation as potential prognostic factors in BC. In the present study, we aimed to determine the relation between TLR9 expression and clinicopathological prognostic parameters and survival in BC.&#x0D; &#x0D; Materials and methods:&#x0D; One hundred and thirty nine patients diagnosed as BC included the present study. Immuno-reactivity scoring (IRS) system was used to reveal the tissue TLR9 expression levels.&#x0D; &#x0D; Results:&#x0D; We found higher TLR9 expression in tumors diagnosed as invasive carcinoma NOS, grade 3 tumors, tumors with necrosis, ER negative and Her2 positive tumors and tripple negative molecular subtype. Furthermore, tumors with low TLR9 scores showed increased overall survival compared to tumors with high TLR9 scores.&#x0D; &#x0D; Conclusions:&#x0D; TLR9 overexpression in BC is associated with some prognostic parameters including histologic type, tumor grade, tumor necrosis, ER and Her2 status and molecular subtype as well as overall survival. Further studies with larger patient series are needed to shed light on the use of TLR9 as a clinical and therapeutic target in BC.

Effects of Hyaluronan on Breast Cancer Aggressiveness.

The expression of the estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) in breast cancer cells is critical for determining tumor aggressiveness and targeting therapies. The presence of such receptors allows for the use of antagonists that effectively reduce breast cancer growth and dissemination. However, the absence of such receptors in triple-negative breast cancer (TNBC) reduces the possibility of targeted therapy, making these tumors very aggressive with a poor outcome. Cancers are not solely composed of tumor cells, but also include several types of infiltrating cells, such as fibroblasts, macrophages, and other immune cells that have critical functions in regulating cancer cell behaviors. In addition to these cells, the extracellular matrix (ECM) has become an important player in many aspects of breast cancer biology, including cell growth, motility, metabolism, and chemoresistance. Hyaluronan (HA) is a key ECM component that promotes cell proliferation and migration in several malignancies. Notably, HA accumulation in the tumor stroma is a negative prognostic factor in breast cancer. HA metabolism depends on the fine balance between HA synthesis by HA synthases and degradation yielded by hyaluronidases. All the different cell types present in the tumor can release HA in the ECM, and in this review, we will describe the role of HA and HA metabolism in different breast cancer subtypes.

Clinical importance and PI3K/Akt pathway-dependent anti-proliferative role of PALMD and DPT in breast cancer

This study aimed to identify novel differentially expressed genes in breast cancer and to explore the clinical value and the anti-tumor or oncogenic effects of the identified genes using bioinformatics analysis and in vitro experiments. The differentially expressed genes in breast cancer patients were identified using Gene Expression Omnibus (GEO) database with the cut-off criteria p < 0.05 and |logFC| > 1. The expression levels of palmdelphin (PALMD) and dermatopontin (DPT) in normal tissues and breast cancer tissues were evaluated based on GEPIA and UALCAN databases. PALMD and DPT expression levels in clinical subgroups of patients with breast cancer were analyzed to assess the association of PALMD and DPT expression with clinical characteristics. The prognostic and diagnostic values of PALMD and DPT in breast cancer were evaluated from Kaplan-Meier (K-M) survival curves and receiver operating characteristic (ROC) curves. Pearson’s correlation coefficient was performed using LinkedOmics. KEGG pathway enrichment analysis was performed using DAVID. The protein levels were evaluated using western blot analysis. Cell proliferation was assessed using MTT and EdU assays. Two important genes, PALMD and DPT, were identified in breast cancer. The expression levels of PALMD and DPT were significantly lower in breast cancer tissues. The expression levels of PALMD were closely related to age, histological type, and T stage of breast cancer patients. The expression levels of DPT were closely related to age, histological type, T stage, N stage, estrogen receptor status, and progesterone receptor status of breast cancer patients. The K-M survival curves showed that PALMD or DPT was not an independent prognostic factor for breast cancer. The ROC curves showed that both PALMD and DPT had good diagnostic potential for breast cancer. KEGG pathway enrichment results showed that PI3K/Akt pathway was an important overlapping signaling for PALMD and DPT. Further studies proved that overexpression of PALMD and DPT inhibited proliferation in MCF-7 and MDA-MB-231 cells by suppressing the PI3K/Akt pathway. PALMD and DPT knockdown promoted proliferation in MCF-7 and MDA-MB-231 cells by activating the PI3K/Akt pathway. These results collectively suggested that PALMD and DPT might serve as potential diagnostic biomarkers and therapeutic targets for breast cancer.

Evaluation of breast cancer malignancy, prognostic factors and molecular subtypes using a continuous-time random-walk MR diffusion model

PurposeTo assess the continuous-time random-walk (CTRW) model’s diagnostic value in breast lesions and to explore the associations between the CTRW parameters and breast cancer pathologic factors. MethodThis retrospective study included 85 patients (70 malignant and 18 benign lesions) who underwent 3.0T MRI examinations. Diffusion-weighted images (DWI) were acquired with 16b-values to fit the CTRW model. Three parameters (Dm, α, and β) derived from CTRW and apparent diffusion coefficient (ADC) from DWI were compared among the benign/malignant lesions, molecular prognostic factors, and molecular subtypes by Mann-Whitney U test. Spearman correlation was used to evaluate the associations between the parameters and prognostic factors. The diagnostic performance was assessed by the area under the receiver operating characteristic curve (AUC) based on the diffusion parameters. ResultsAll parameters, ADC, Dm, α, and β were significantly lower in the malignant than benign lesions (P < 0.05). The combination of all the CTRW parameters (Dm, α, and β) provided the highest AUC (0.833) and the best sensitivity (94.3%) in differentiating malignant status. And the positive status of estrogen receptor (ER) and progesterone receptor (PR) showed significantly lower β compared with the negative counterparts (P < 0.05). The high Ki-67 expression produced significantly lower Dm and ADC values (P < 0.05). Additionally, combining multiple CTRW parameters improved the performance of diagnosing molecular subtypes of breast cancer. Moreover, Spearman correlations analysis showed that β produced significant correlations with ER, PR and Ki-67 expression (P < 0.05). ConclusionsThe CTRW parameters could be used as non-invasive quantitative imaging markers to evaluate breast lesions.

Retracted: Correlation Analysis of Ultrasound Elastography Score with Invasive Breast Cancer and Biological Prognostic Factors.

[This retracts the article DOI: 10.1155/2022/1174541.].