Different Subtypes Of Breast Cancer Research Articles

Study on the mechanism of heterogeneous tumor-associated macrophages in three subtypes of breast cancer through the integration of single-cell RNA sequencing and in vitro experiments.

Tumor-associated macrophages (TAM) exert a significant influence on the progression and heterogeneity of various subtypes of breast cancer (BRCA). However, the roles of heterogeneous TAM within BRCA subtypes remain unclear. Therefore, this study sought to elucidate the role of TAM across the following three BRCA subtypes: triple-negative breast cancer, luminal, and HER2. This investigation aimed to delineate the variations in marker genes, drug sensitivity, and cellular communication among TAM across the three BRCA subtypes. We identified specific ligand-receptor (L-R) pairs and downstream mechanisms regulated by VEGFA-VEGFR1, SPP1-CD44, and SPP1-ITGB1 L-R pairs. Experimental verification of these pairs was conducted by co-culturing macrophages with three subtypes of BRCA cells. Our findings reveal the heterogeneity of macrophages within the three BRCA subtypes, evidenced by variations in marker gene expression, composition, and functional characteristics. Notably, heterogeneous TAM were found to promote invasive migration and epithelial-mesenchymal transition (EMT) in MDA-MB-231, MCF-7, and SKBR3 cells, activating NF-κB pathway via P38 MAPK, TGF-β1, and AKT, respectively, through distinct VEGFA-VEGFR1, SPP1-CD44, and SPP1-ITGB1 L-R pairs. Inhibition of these specific L-R pairs effectively reversed EMT, migration, and invasion of each cancer cells. Furthermore, we observed a correlation between ligand gene expression and TAM sensitivity to anticancer drugs, suggesting a potential strategy for optimizing personalized treatment guidance. Our study highlights the capacity of heterogeneous TAM to modulate biological functions via distinct pathways mediated by specific L-R pairs within diverse BRCA subtypes. This study might provide insights into precision immunotherapy of different subtypes of BRCA.

Demographics and survival outcomes of stage IV male breast cancer: A retrospective analysis of SEER database.

11142 Background: Male Breast Cancer (MBC) is a rare malignancy accounting for <1% of all breast cancer cases in the United States. It is often lately diagnosed due to lack of awareness leading to substantial morbidity and mortality. Previous studies revealed higher risk of death among males compared to females across all stages, but little known about the impact of Hormone Receptor (HR) and Human Epidermal growth factor Receptor 2(HER 2) statuses on prognosis and survival among MBC patients. So, we aim to study the survival outcomes of stage IV MBC patients using SEER (Surveillance, Epidemiology, and End Results) data. Methods: A retrospective analysis was conducted using a SEER database and identified stage IV MBC cases (Any T, Any N, M1) diagnosed between 2010-2015. The selection of these years is based on the reporting of HER2 status on SEER database starting from 2010 and to ensure a current period and a minimum of 5 years of follow-up. Patient demographics, tumor HR/HER 2 status and survival data were extracted and analyzed. Subgroup analyses were performed to show the correlation between HR/HER 2 status and survival. Results: The study included 144 patients. 59.7%(86/144) were above 60 years of age. Majority were Caucasians up to 68.1%(98/144) followed by African Americans 18.7% (27/144), Hispanics 6.9%(10/144) and Asians/Pacific Islanders 6.2%(9/144). Among the subtypes, the most common was HR+/HER2- consisting of 69.4%(100/144) followed by HR+/HER2+ 19.4%(28/144), HR-/HER2- 9.7%(14/144), HR-/HER2+ 1.4%(2/144). The median overall survival varied among different subtypes of breast cancer and was noted to be 31.5 months, 25 months, 4.5 months and 10 months among HR+/HER2-, HR+/HER2+, HR-/HER2- and HR-/HER2+ respectively (Table). In the comparison between HR+/HER2+ and HR-/HER2-, the risk of death differed significantly, as indicated by a hazard ratio of 0.26 (95% CI 0.12-0.56, p = 0.001), highlighting a poor survival of HR-/HER2-. Conclusions: This retrospective analysis provides valuable insights into the demographics and survival outcomes of stage IV MBC patients. Triple negative (HR-/HER2-) subtype continues to have poor outcomes in males as well, emphasizing the need to explore novel treatment strategies to improve outcomes for this unique patient population. Although, treatment regimens for MBC are extrapolated from women, the disparity in survival across all subtypes requires the need to get more men on breast cancer clinical trials when feasible. [Table: see text]

Preliminary exploration of Trop2 ADC in combination with immune checkpoint inhibitors in the different molecular subtypes of invasive breast carcinoma.

e12558 Background: Human trophoblastic cell surface antigen 2 (Trop2) is a transmembrane protein overexpressed in breast cancer tissues. However, it is present at minimal levels in adult somatic tissues, making it an ideal target for treatment with antibody-drug conjugates (ADCs). Sacituzumab govitecan, an anti-Trop2 ADC, has been approved for the treatment of triple-negative breast cancer and urothelial cancer. Recent studies have demonstrated that human cytotoxic T lymphocytes can recognize Trop2. Accordingly, we aimed to assess the role of Trop2 in the tumor immune activity of different subtypes of breast cancer, and laying the foundation for further studies on the efficacy of the combination of Trop2 ADC and immune checkpoint inhibitors in breast cancer. Methods: We retrospectively retrieved tissues from 152 invasive breast carcinoma of no special type and 111 benign breast tumor tissues and undergoing surgical resection at our institution from 2018 to 2023. Immunohistochemistry was used to detect Trop2 and PD-L1 expression and lymphatic invasion in patients, and their correlations with clinicopathological factors were analyzed. Trop2 expression was evaluated using the H-score. The median as the cut-off value, a score of 0–240 indicated low expression, and 240–300 indicated high expression. Cases with CPS ≥ 1% were considered positive for PD-L1. Results: The expression was Trop2 in breast cancer tissues than in benign tumor tissues (P<0.0001). Immune infiltration analysis suggested that Trop2 expression was correlated with immune cell infiltration and the abundance (P<0.001). Kaplan–Meier plotter analysis demonstrated that high Trop2 expression was related to poor prognosis in patients with triple-negative breast cancer (overall survival: HR=1.53, P=0.029; relapse-free survival: HR=1.26, P=0.045). In contrast, Trop2 expression was not significantly associated with prognosis in other breast cancer subtypes. However, there was no statistically significant correlation found between PD-L1 expression and Trop-2 expression in breast cancer. Conclusions: The findings suggest that Trop2 correlates with poor prognosis and immune cell infiltration in breast cancer. This indicates the role of Trop2 as a potential prognostic biomarker, laying the foundation for further research focusing on the immune regulatory role of Trop2. [Table: see text]

Abstract PO2-08-02: Evaluation of predictive and prognostic value of androgen receptorexpression in breast cancer subtypes treated with neoadjuvantchemotherapy

Abstract Background Neoadjuvant chemotherapy is the standard treatment for local advanced breast cancer administered to shrink tumors and destroy undetected metastatic cells, thereby facilitating subsequent surgery. Previous studies have shown that AR may be used as a prognostic predictor in breast cancers, but its role in neoadjuvant therapy and the relationship with prognosis of different molecular subtypes of breast cancer need to be further explored. Methods We retrospectively evaluated 1231 breast cancer patients with complete medical records at Tianjin Medical University Cancer Institute and Hospital who were treated with neoadjuvant chemotherapy between January 2018 to December 2021. All the patients were selected for prognostic analysis. The follow-up time ranged from 12 to 60 months. We first analyzed the AR expression in different subtypes of breast cancer and its correlation with clinicopathological features. Meanwhile, the association of AR expression and pCR of different breast cancer subtypes was investigated. Finally, the effect of AR status on the prognosis of different subtypes of breast cancer after neoadjuvant therapy was analyzed. Results The positive rates of AR expression in HR +/HER2-, HR +/HER2 +, HR-/HER2 + and TNBC subtypes were 82.5%, 86.9%, 72.2% and 34.6%, respectively. Histological grade III (P = 0.014, OR = 1.862, 95% CI 1.137 to 2.562), ER positive expression (P = 0.002, OR = 0.381, 95% CI 0.102 to 0.754) and HER2 positive expression (P = 0.006, OR = 0.542, 95% CI 0.227 to 0.836) were independent related factors for AR positive expression. AR expression status was associated with pCR rate after neoadjuvant therapy only in subtype of TNBC. AR positive expression was independent protective factor for recurrence and metastasis in HR +/HER2- (P = 0.033, HR = 0.653, 95% CI 0.237 to 0.986) and HR +/HER2 + breast cancer (P = 0.012, HR = 0.803, 95% CI 0.167 to 0.959), but was independent risk factors for recurrence and metastasis in TNBC (P = 0.015, HR = 4.551, 95% CI 2.668 to 8.063). AR positive expression is not an independent predictor of HR-/HER2 + breast cancer. Conclusions AR expressed the lowest in TNBC, but it could be a potential marker for the prediction of pCR in neoadjuvant therapy. AR negative patients had a higher pCR rate. AR positive expression was an independent risk factor for pCR in TNBC after neoadjuvant therapy (P = 0.017, OR = 2.758, 95% CI 1.564 to 4.013). In HR +/HER2- subtype and in HR +/HER2 + subtype, the DFS rate in AR positive patients and AR negative patients was 96.2% vs 89.0% (P = 0.001, HR = 0.330, 95% CI 0.106 to 1.034) and was 96.0% vs 85.7% (P= 0.002, HR = 0.278, 95% CI 0.082 to 0.940), respectively. However, in HR-/HER2 + and TNBC subtypes, the DFS rate in AR positive patients and AR negative patients was 89.0% vs 95.9% (P = 0.102, HR = 3.211, 95% CI 1.117 to 9.224) and 75.0% vs 93.4% (P < 0.001, HR = 3.706, 95% CI 1.681 to 8.171), respectively. In HR +/HER2- and HR +/HER2 + breast cancer, AR positive patients had a better prognosis, however in TNBC, AR-positive patients have a poor prognosis Citation Format: Jin Zhang. Evaluation of predictive and prognostic value of androgen receptorexpression in breast cancer subtypes treated with neoadjuvantchemotherapy [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO2-08-02.

Apolipoprotein A-1 downregulation promotes basal-like breast cancer cell proliferation and migration associated with DNA methylation.

Apolipoprotein A-I (APOA1) performs different roles in different subtypes of breast cancer. It is hypothesized to function as a tumor suppressor in basal-like breast cancer (BLBC). However, the specific role of APOA1 in BLBC and its underlying mechanisms remain unknown. The findings of the present study demonstrated a positive correlation between the expression level of APOA1 and the overall survival of patients with BLBC. Ectopic expression of APOA1 effectively inhibits the proliferation and metastasis of BLBC cells in vitro, and these effects are closely related to DNA methylation. To the best of our knowledge, the present study is the first to report increased methylation of the promoter region and decreased methylation of the structural genes of APOA1 in BLBC cells. These alterations resulted in the downregulation of APOA1 expression and suppression of BLBC tumor growth. Collectively, the results of the present study suggested that APOA1 mRNA expression is negatively regulated by DNA methylation in BLBC. Therefore, low expression of APOA1 may be a potential risk biomarker to predict survival in patients with BLBC.

Breast Cancer in Patients with Previous Endometriosis Showed Low Aggressive Subtype.

Background and Objectives: The association between endometriosis and breast cancer still remains controversial. The aim of this study was to investigate the different subtypes of breast cancer, immunohistochemical markers, hormone receptors, and ki67 proliferation indexes in patients with and without endometriosis and/or adenomyosis. Materials and Methods: All patients with endometriosis and breast cancer were enrolled. Women with endometriosis and breast cancer (Group BC+EN+) were compared to patients with breast cancer without endometriosis (group BC+EN-) and those with endometriosis without breast cancer (group BC-EN+). General population characteristics and histological and immunohistochemical subtypes of breast cancer were compared between groups. Results: Our study included 41 cases affected by both endometriosis and/or adenomyosis and breast cancer (Group BC+EN+) that were matched (1:2) with 82 patients affected only by breast cancer (group BC+EN-) and 82 patients affected only by endometriosis and/or adenomyosis (group BC-EN+). Group BC+EN+ presented a higher percentage of ER receptor expression (83% vs. 70%, p = 0.02), as well as lower values of Ki 67% (15% vs. 24%, p < 0.0001) and HER2+ (9.8% vs. 28%, p = 0.022). These findings were more evident when comparing patients with premenopausal status, while in postmenopausal patients, this difference was no longer significant. Regarding endometriosis, no statistical differences were observed in type or specific localization of the disease among the groups with and without breast cancer. Conclusions: Patients with endometriosis presented lower aggressive breast cancer rates with higher values of ER% and lower values of Ki 67 and HER2neu+. The type and severity of endometriotic diseases seemed not to influence breast cancer occurrence.

CAR-based immunotherapy for breast cancer: peculiarities, ongoing investigations, and future strategies.

Surgery, chemotherapy, and endocrine therapy have improved the overall survival and postoperative recurrence rates of Luminal A, Luminal B, and HER2-positive breast cancers but treatment modalities for triple-negative breast cancer (TNBC) with poor prognosis remain limited. The effective application of the rapidly developing chimeric antigen receptor (CAR)-T cell therapy in hematological tumors provides new ideas for the treatment of breast cancer. Choosing suitable and specific targets is crucial for applying CAR-T therapy for breast cancer treatment. In this paper, we summarize CAR-T therapy's effective targets and potential targets in different subtypes based on the existing research progress, especially for TNBC. CAR-based immunotherapy has resulted in advancements in the treatment of breast cancer. CAR-macrophages, CAR-NK cells, and CAR-mesenchymal stem cells (MSCs) may be more effective and safer for treating solid tumors, such as breast cancer. However, the tumor microenvironment (TME) of breast tumors and the side effects of CAR-T therapy pose challenges to CAR-based immunotherapy. CAR-T cells and CAR-NK cells-derived exosomes are advantageous in tumor therapy. Exosomes carrying CAR for breast cancer immunotherapy are of immense research value and may provide a treatment modality with good treatment effects. In this review, we provide an overview of the development and challenges of CAR-based immunotherapy in treating different subtypes of breast cancer and discuss the progress of CAR-expressing exosomes for breast cancer treatment. We elaborate on the development of CAR-T cells in TNBC therapy and the prospects of using CAR-macrophages, CAR-NK cells, and CAR-MSCs for treating breast cancer.

Advances in the study of tertiary lymphoid structures in the immunotherapy of breast cancer.

Breast cancer, as one of the most common malignancies in women, exhibits complex and heterogeneous pathological characteristics across different subtypes. Triple-negative breast cancer (TNBC) and HER2-positive breast cancer are two common and highly invasive subtypes within breast cancer. The stability of the breast microbiota is closely intertwined with the immune environment, and immunotherapy is a common approach for treating breast cancer.Tertiary lymphoid structures (TLSs), recently discovered immune cell aggregates surrounding breast cancer, resemble secondary lymphoid organs (SLOs) and are associated with the prognosis and survival of some breast cancer patients, offering new avenues for immunotherapy. Machine learning, as a form of artificial intelligence, has increasingly been used for detecting biomarkers and constructing tumor prognosis models. This article systematically reviews the latest research progress on TLSs in breast cancer and the application of machine learning in the detection of TLSs and the study of breast cancer prognosis. The insights provided contribute valuable perspectives for further exploring the biological differences among different subtypes of breast cancer and formulating personalized treatment strategies.

Abstract 2330: CTD2 "Connects the Dots" to capture disease genes in complex networks and its application on the Cancer Genomics Cloud

Abstract We have developed CTD2 (an algorithm to "Connect the Dots") to capture biological signals and identify candidate genes in complex networks. CTD2 extends the functionality of its predecessor CTD by providing ranked lists of genes that are “guilty by association” and significantly linked to other genes of interest. With the explosion of large scale multi-omics studies in the cancer field, novel approaches are needed to interpret these valuable datasets. Both CTD and CTD2 are information-theoretic algorithms that allow identification of highly connected sets of genes in complex networks without the need for permutation testing. CTD has been previously used to interpret perturbations in different subtypes of breast cancer. Additionally CTD has been used to identify biomarkers of chemotherapy response in Triple Negative Breast Cancer (TNBC) murine PDX models to both platinum and taxane agents. These small multigene biomarkers of response were shown to be informative for the response of both patients and PDXs. CTD2 was developed to expand the utility of the CTD package by also capturing genes that are "guilty by association". These genes are significantly connected to genes of interest (such as disease genes), and are ranked by their connectedness to these informative gene sets. To demonstrate its utility, we investigated if CTD2 could identify known breast cancer genes. Using TCGA breast cancer expression data, we built case/control graphs over 5,000 variable genes for each subtype of breast cancer. Genes previously associated with breast cancer were identified with DisGeNET and split into a training set discovered pre-2015 and test set discovered post-2015. The genes that were discovered pre-2015 that overlapped with our networks (n = 680) were then used as an input for CTD2 along with the case/control graphs. We then ranked the connectedness of all the genes in these graphs to the training set and found that the test set of breast cancer genes that were discovered post-2015 were significantly enriched in these ranked lists.We have shown that CTD2 and CTD can be utilized to discover biologically informative signals in complex networks. Furthermore we have deployed these tools on the Cancer Genomics Cloud to make them easily accessible for users without a bioinformatics background. The democratization of these in silico tools will allow for their adaptation by a wider audience and aid in the interpretation of large multi-omic datasets. Citation Format: Varduhi Petrosyan, Vladimir Kovacevic, Predrag Obradovic, Cera Fisher, Zelia Worman, Divya Sain, Jack DiGiovanna, Brandi Davis-Dusenberry, Aleksandar Milosavljevic. CTD2 "Connects the Dots" to capture disease genes in complex networks and its application on the Cancer Genomics Cloud [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2330.

Abstract 6931: Characterization of cancer evolution landscape based on accurate detection of somatic mutations in single tumor cells

Abstract Accurate detection of somatic mutations in single tumor cells is greatly desired as it allows us to quantify the single-cell mutation burden and construct the mutation-based phylogenetic tree. Here we developed scNanoSeq chemistry and profiled 842 single cells from 21 human breast cancer samples. The majority of the mutation-based phylogenetic trees comprise a characteristic stem evolution followed by the clonal sweep. We observed the subtype-dependent lengths in the stem evolution. To explain this phenomenon, we propose that the differences are related to different reprogramming required for different subtypes of breast cancer. Furthermore, we reason that the time that the tumor-initiating cell took to acquire the critical clonal-sweep-initiating mutation by random chance set the time limit for the reprogramming process. We refer to this model as a reprogramming and critical mutation co-timing (RCMC) subtype model. Next, in the sweeping clone, we observed that tumor cells undergo a branched evolution with rapidly decreasing selection. In the most recent clades, effectively neutral evolution has been reached, resulting in a substantially large number of mutational heterogeneities. Integrative analysis with 522-713X ultra-deep bulk whole genome sequencing (WGS) further validated this evolution mode. Mutation-based phylogenetic trees also allow us to identify the early branched cells in a few samples, whose phylogenetic trees support the gradual evolution of copy number variations (CNVs). Overall, the development of scNanoSeq allows us to unveil novel insights into breast cancer evolution. Citation Format: Muchun Niu, Yang Zhang, Jiayi Luo, Jefferson C. Sinson, Alastair M. Thompson, Chenghang Zong. Characterization of cancer evolution landscape based on accurate detection of somatic mutations in single tumor cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6931.

Analyses of hypoxia-related risk factors and clinical relevance in breast cancer.

Hypoxia plays an important role in the heterogeneity, relapse, metastasis, and drug resistance of breast cancer. In this study, we explored the hypoxia-related biological signatures in different subtypes of breast cancer and identified the key prognostic factors by bioinformatics methods. Based on The Cancer Genome Atlas (TCGA) Breast Cancer datasets, we divided the samples into immune-activated/suppressed populations by single-sample gene set enrichment analysis (ssGSEA) and then used hierarchical clustering to further identify hypoxic/non-hypoxic populations from the immune-suppressed samples. A hypoxia related risk model of breast cancer was constructed. Nuclear factor interleukin-3 regulated (NFIL3), serpin family E member 1 (SERPINE1), FOS, biglycan (BGN), epidermal growth factor receptor (EGFR), and sushi-repeat-containing protein, X-linked (SRPX) were identified as key hypoxia-related genes. Margin status, American Joint Committee on Cancer (AJCC) stage, hypoxia status, estrogen receptor/progesterone receptor (ER/PR) status, NFIL3, SERPINE1, EGFR, and risk score were identified as independent prognostic indicators for breast cancer patients. The 3- and 5-year survival curves of the model and immunohistochemical staining on the breast cancer microarray verified the statistical significance and feasibility of our model. Among the different molecular types of breast cancer, ER/PR+ and HER2+ patients might have higher hypoxia-related risk scores. ER/PR-negative samples demonstrated more activated immune-related pathways and better response to most anticancer agents. Our study revealed a novel risk model and potential feasible prognostic factors for breast cancer and might provide new perspectives for individual breast cancer treatment.

Breast Tumor Metastasis and Its Microenvironment: It Takes Both Seed and Soil to Grow a Tumor and Target It for Treatment.

Metastasis remains a major challenge in treating breast cancer. Breast tumors metastasize to organ-specific locations such as the brain, lungs, and bone, but why some organs are favored over others remains unclear. Breast tumors also show heterogeneity, plasticity, and distinct microenvironments. This contributes to treatment failure and relapse. The interaction of breast cancer cells with their metastatic microenvironment has led to the concept that primary breast cancer cells act as seeds, whereas the metastatic tissue microenvironment (TME) is the soil. Improving our understanding of this interaction could lead to better treatment strategies for metastatic breast cancer. Targeted treatments for different subtypes of breast cancers have improved overall patient survival, even with metastasis. However, these targeted treatments are based upon the biology of the primary tumor and often these patients' relapse, after therapy, with metastatic tumors. The advent of immunotherapy allowed the immune system to target metastatic tumors. Unfortunately, immunotherapy has not been as effective in metastatic breast cancer relative to other cancers with metastases, such as melanoma. This review will describe the heterogeneic nature of breast cancer cells and their microenvironments. The distinct properties of metastatic breast cancer cells and their microenvironments that allow interactions, especially in bone and brain metastasis, will also be described. Finally, we will review immunotherapy approaches to treat metastatic breast tumors and discuss future therapeutic approaches to improve treatments for metastatic breast cancer.

Cyclin-dependent kinase 7 (CDK7) inhibitors as a novel therapeutic strategy for different molecular types of breast cancer.

Cyclin-dependent kinase (CDK) 7 is aberrantly overexpressed in many types of cancer and is an attractive target for cancer therapy due to its dual role in transcription and cell cycle progression. Moreover, CDK7 can directly modulate the activities of estrogen receptor (ER), which is a major driver in breast cancer. Breast cancer cells have exhibited high sensitivity to CDK7 inhibition in pre-clinical studies. In this review, we provide a comprehensive summary of the latest insights into CDK7 biology and recent advancements in CDK7 inhibitor development for breast cancer treatment. We also discuss the current application of CDK7 inhibitors in different molecular types of breast cancer to provide potential strategies for the treatment of breast cancer. Significant progress has been made in the development of selective CDK7 inhibitors, which show efficacy in both triple-negative breast cancer (TNBC) and hormone receptor-positive breast cancer (HR+). Moreover, combined with other agents, CDK7 inhibitors may provide synergistic effects for endocrine therapy and chemotherapy. Thus, high-quality studies for developing potent CDK7 inhibitors and investigating their applications in breast cancer therapy are rapidly emerging. CDK7 inhibitors have emerged as a promising therapeutic strategy and have demonstrated significant anti-cancer activity in different subtypes of breast cancer, especially those that have been resistant to current therapies.

Superbinder based phosphoproteomic landscape revealed PRKCD_pY313 mediates the activation of Src and p38 MAPK to promote TNBC progression

Phosphorylation proteomics is the basis for the study of abnormally activated kinase signaling pathways in breast cancer, which facilitates the discovery of new oncogenic agents and drives the discovery of potential targets for early diagnosis and therapy of breast cancer. In this study, we have explored the aberrantly active kinases in breast cancer development and to elucidate the role of PRKCD_pY313 in triple negative breast cancer (TNBC) progression. We collected 47 pairs of breast cancer and paired far-cancer normal tissues and analyzed phosphorylated tyrosine (pY) peptides by Superbinder resin and further enriched the phosphorylated serine/threonine (pS/pT) peptides using TiO2 columns. We mapped the kinases activity of different subtypes of breast cancer and identified PRKCD_pY313 was upregulated in TNBC cell lines. Gain-of-function assay revealed that PRKCD_pY313 facilitated the proliferation, enhanced invasion, accelerated metastasis, increased the mitochondrial membrane potential and reduced ROS level of TNBC cell lines, while Y313F mutation and low PRKCD_pY313 reversed these effects. Furthermore, PRKCD_pY313 significantly upregulated Src_pY419 and p38_pT180/pY182, while low PRKCD_pY313 and PRKCD_Y313F had opposite effects. Dasatinib significantly inhibited the growth of PRKCD_pY313 overexpression cells, and this effect could be enhanced by Adezmapimod. In nude mice xenograft model, PRKCD_pY313 significantly promoted tumor progression, accompanied by increased levels of Ki-67, Bcl-xl and Vimentin, and decreased levels of Bad, cleaved caspase 3 and ZO1, which was opposite to the trend of Y313F group. Collectively, the heterogeneity of phosphorylation exists in different molecular subtypes of breast cancer. PRKCD_pY313 activates Src and accelerates TNBC progression, which could be inhibited by Dasatinib.

Integrative HLA typing of tumor and adjacent normal tissue can reveal insights into the tumor immune response

BackgroundThe HLA complex is the most polymorphic region of the human genome, and its improved characterization can help us understand the genetics of human disease as well as the interplay between cancer and the immune system. The main function of HLA genes is to recognize “non-self” antigens and to present them on the cell surface to T cells, which instigate an immune response toward infected or transformed cells. While sequence variation in the antigen-binding groove of HLA may modulate the repertoire of immunogenic antigens presented to T cells, alterations in HLA expression can significantly influence the immune response to pathogens and cancer.MethodsRNA sequencing was used here to accurately genotype the HLA region and quantify and compare the level of allele-specific HLA expression in tumors and patient-matched adjacent normal tissue. The computational approach utilized in the study types classical and non-classical Class I and Class II HLA alleles from RNA-seq while simultaneously quantifying allele-specific or personalized HLA expression. The strategy also uses RNA-seq data to infer immune cell infiltration into tumors and the corresponding immune cell composition of matched normal tissue, to reveal potential insights related to T cell and NK cell interactions with tumor HLA alleles.ResultsThe genotyping method outperforms existing RNA-seq-based HLA typing tools for Class II HLA genotyping. Further, we demonstrate its potential for studying tumor-immune interactions by applying the method to tumor samples from two different subtypes of breast cancer and their matched normal breast tissue controls.ConclusionsThe integrative RNA-seq-based HLA typing approach described in the study, coupled with HLA expression analysis, neoantigen prediction and immune cell infiltration, may help increase our understanding of the interplay between a patient’s tumor and immune system; and provide further insights into the immune mechanisms that determine a positive or negative outcome following treatment with immunotherapy such as checkpoint blockade.

An image analysis approach to characterize micronuclei differences in different subtypes of breast cancer

BackgroundMicronuclei (MN) have been used as screening, diagnostic and prognostic markers in multiple cancer types, including breast cancer (BC). However, the question that the MN present in all subtypes of BC are similar or different remains unanswered. We thus hypothesized that MN present in different subtypes of BC may differ in their contents which may be visible as differences in their morphologic and morphometric features. This study was thus carried out with the aim to identify the differences between MN morphometry, complexity, and texture in different subtypes of BC, such as estrogen and progesterone receptor-positive (ER+/PR+; MCF-7, T-47D), human epidermal growth factor receptor-positive (Her2 +;SKBR3) and triple-negative BC (TNBC; MDA-MB-231, MDA-MB-468) cell lines (CLs) by ImageJ software. MethodsFor analysis of MN dimensions, MN irregularity, and texture, we used morphometry and two mathematical computer-assisted algorithms, i.e., fractal dimension (FD) and grey level co-occurrence matrix (GLCM) of ImageJ software. ResultsMN area and perimeter values showed differences in the size of MN in different subtypes of BC, with the largest MN in TNBC CLs. GLCM parameters (entropy, angular second moment, inverse difference moment, contrast, and correlation) showed highly heterogenous texture in case of TNBC MN as compared to the others. FD analysis also revealed more complexity and irregularity in MN found in TNBC cells. ConclusionThe study for the first time showed morphometric, architectural and texture related differences amongst MN present in different subtypes of BC. The above may reflect differences in their composition and contents. Further, these differences may point towards the distinct mechanisms involved in the formation of MN in different subtypes of BC that need to be explored further.

Retracted: Effect of Previous Cancer History on Survival of Patients with Different Subtypes of Breast Cancer.

[This retracts the article DOI: 10.1155/2022/6116658.].

The prognostic implications and tumor-suppressive functions of CYR61 in estrogen receptor-positive breast cancer.

Due to the therapeutic resistance of endocrine therapy and the limited efficacy of immune checkpoint inhibitors in estrogen receptor (ER)-positive breast cancer (BRCA), there is an urgent need to develop novel prognostic markers and understand the regulation of the tumor immune microenvironment (TIME). As a matricellular protein, CYR61 has been shown to either promote or suppress cancer progression depending on cancer types. However, how CYR61 functions in ER-positive BRCA remains elusive. In this study, we comprehensively analyzed the expression of CYR61 in BRCA based on the TCGA and METABRIC databases. Our findings showed that the expression of CYR61 is downregulated in different subtypes of BRCA, which is associated with elevated promoter methylation levels and predicts bad clinical outcomes. By comparing the high or low CYR61 expression groups of ER-positive BRCA patients, we found that CYR61 is intimately linked to the expression of genes involved in tumor-suppressive pathways, such as the TGF-β and TNF signaling pathways, and genes related to cytokine-receptor interaction that may regulate cancer immunity. Moreover, reduced CYR61 expression is associated with an altered TIME that favors cancer progression. Finally, experimental analyses ascertained that CYR61 is downregulated in clinical BRCA tissues compared to matched normal breast tissues. Furthermore, CYR61 is able to impede the proliferation and colony formation of ER-positive BRCA cells. In summary, our study reveals that CYR61 could serve as a novel prognostic marker for ER-positive BRCA, and function as an inhibitor of cancer progression by both acting on cancer cells and remodeling the TIME.

A bioinformatic analysis found low expression and clinical significance of ATF4 in breast cancer

BackgroundActivating Transcription Factor 4 (ATF4) expression exhibits differential patterns across different types of tumors. Besides, the pathogenesis of breast cancer is complex, and the exact relationship between ATF4 and ATF4 remains uncertain. MethodsThe analysis of ATF4 expression was conducted by utilizing The Cancer Genome Atlas (TCGA) pan-cancer data, while the gene expression profile of breast cancer was checked by the comprehensive database-Gene Expression Omnibus database. In order to gain a more comprehensive understanding of the specific cell types that exhibit ATF4 expression within the microenvironment of breast cancer, we conducted a single-cell analysis of ATF4 using two distinct datasets of human breast cancer (GSE114717 and GSE11088, respectively). The spatial distribution of ATF4 within a tissue was demonstrated based on datasets obtained from the Human Protein Atlas (HPA) and SpatialDB. The clinical prognostic significance of ATF4 was assessed by analyzing clinical survival data obtained from TCGA, GSE4830, and GSE25055 datasets. We used the R package clusterProfiler to carry out an enrichment analysis of ATF4. We assessed how ATF4 impacts the growth and movement of breast cancer cell lines. We manipulated ATF4 levels using plasmid transfection techniques. ResultsThe expression of ATF4 was found to be suboptimal and demonstrated a significant correlation with enhanced disease-specific survival (p = 0.012) and overall survival (p = 0.032) in breast cancer as well as other malignancies. We conducted an analysis to investigate the interaction between the infiltration level of immune cells and the expression of ATF4, using samples obtained from TCGA with known immune cell infiltration scores. Furthermore, a notable positive correlation exists between the elevated expression of ATF4 and immune-related genomes, specifically those associated with chemokine as well as immunity. Subsequent examination revealed a notable augmentation in the cytodifferentiation of T cells into regulatory T (Treg) cells within tissues exhibiting elevated levels of ATF4 expression. ATF4 exhibits notable upregulation in the MDA-MB-231 cell, thereby exerting a substantial impact on cell proliferation and migration upon its knockdown. Conversely, the overexpression of ATF4 in the MCF7 Luminal A breast cancer cell line can also modulate cellular function. ConclusionsOur study suggests that ATF4 helps T cells differentiate into Treg cells in breast cancer. ATF4 can represent a clinically useful biomarker to predict the overall survival rate, especially in patients with different subtypes of breast cancer. Provide certain guidance value for the development of targeted drugs or inhibitors targeting ATF4.

Innovations in Positron Emission Tomography and State of the Art in the Evaluation of Breast Cancer Treatment Response.

The advent of hybrid Positron Emission Tomography/Computed Tomography (PET/CT) and PET/Magnetic Resonance Imaging (MRI) scanners resulted in an increased clinical relevance of nuclear medicine in oncology. The use of [18F]-Fluorodeoxyglucose ([18F]FDG) has also made it possible to study tumors (including breast cancer) from not only a dimensional perspective but also from a metabolic point of view. In particular, the use of [18F]FDG PET allowed early confirmation of the efficacy or failure of therapy. The purpose of this review was to assess the literature concerning the response to various therapies for different subtypes of breast cancer through PET. We start by summarizing studies that investigate the validation of PET/CT for the assessment of the response to therapy in breast cancer; then, we present studies that compare PET imaging (including PET devices dedicated to the breast) with CT and MRI, focusing on the identification of the most useful parameters obtainable from PET/CT. We also focus on novel non-FDG radiotracers, as they allow for the acquisition of information on specific aspects of the new therapies.