Luminal breast cancer: from biology to treatment. Nat Rev Clin Oncol. 2013;10:494-506. [PMID: 23881035 DOI: 10.1038/nrclinonc.2013.124]

Increased prevalence of hybrid epithelial/mesenchymal state and enhanced phenotypic heterogeneity in basal breast cancer

Intra-tumoral phenotypic heterogeneity promotes tumor relapse and therapeutic resistance and remains an unsolved clinical challenge. Decoding the interconnections among different biological axes of plasticity is crucial to understand the molecular origins of phenotypic heterogeneity. Here, we use multi-modal transcriptomic data-bulk, single-cell, and spatial transcriptomics-from breast cancer cell lines and primary tumor samples, to identify associations between epithelial-mesenchymal transition (EMT) and luminal-basal plasticity-two key processes that enable heterogeneity. We show that luminal breast cancer strongly associates with an epithelial cell state, but basal breast cancer is associated with hybrid epithelial/mesenchymal phenotype(s) and higher phenotypic heterogeneity. Mathematical modeling of core underlying gene regulatory networks representative of the crosstalk between the luminal-basal and epithelial-mesenchymal axes elucidate mechanistic underpinnings of the observed associations from transcriptomic data. Our systems-based approach integrating multi-modal data analysis with mechanism-based modeling offers a predictive framework to characterize intra-tumor heterogeneity and identify interventions to restrict it.

ESF1 and MIPEP proteins promote estrogen receptor-positive breast cancer proliferation and are associated with patient prognosis

BACKGROUND

Estrogen receptor-positive (ER+) breast cancer accounts for two-thirds of all breast cancers, and its early and late recurrences still threaten patients' long-term survival and quality of life. Finding candidate tumor antigens and potential therapeutic targets is critical to addressing these unmet needs.

METHOD

The isobaric tags for relative and absolute quantitation (iTRAQ) proteomic analysis was employed to identify the differentially expressed proteins (DEPs) between ER + breast cancer and corresponding adjacent normal tissue. Candidate DEPs were screened by bioinformatic analyses, and their expression was confirmed by immunohistochemical (IHC) staining and western blot. A series of in vitro experiments, including wound healing assay, colony formation, and cell cycle assay, were performed to reveal the functions of selected DEPs. Additionally, their clinical significances were further analyzed.

RESULT

A total of 369 DEPs (fold change ≥ 2.0 or ≤ 0.66, P < 0.05) were discovered. Compared with normal tissue, 358 proteins were up-regulated and 11 proteins were down-regulated in ER + breast cancer. GO and KEGG enrichment analysis showed that DEPs were closely associated with RNA regulation and metabolic pathways. STRING analysis found ESF1 and MIPEP were the hub genes in breast cancer, whose increased expressions were verified by the IHC staining and western blot. Knocking down ESF1 and MIPEP inhibited colony formation and increased cell apoptosis. Besides, knocking down ESF1 inhibited wound healing but not MIPEP. In addition, ESF1 and MIPEP expression were negatively associated with patient prognosis.

CONCLUSION

The upregulation of ESF1 and MIPEP promoted ER + breast cancer proliferation, which might provide novel targets for the development of new therapies.

Polymorphic variants of the hOGG1, APEX1, XPD, SOD2, and CAT genes involved in DNA repair processes and antioxidant defense and their association with breast cancer risk

Breast cancer is one of the leading causes of mortality among women. The most frequently encountered tumors are luminal tumors. Associations of polymorphisms in the hOGG1 (rs1052133), APEX1 (rs1130409), XPD (rs13181), SOD2 (rs4880), and CAT (rs1001179) genes were studied in 313 nonsmoking postmenopausal patients with luminal B subtype breast cancer. The control group consisted of 233 healthy nonsmoking postmenopausal women. Statistically significant associations of the XPD and APEX1 gene polymorphisms with the risk of developing luminal B Her2-negative subtype of breast cancer were observed in a log-additive inheritance model, while the CAT gene polymorphism showed an association in a dominant inheritance model (OR = 1.41; CI 95 %: 1.08-1.85; Padj.= 0.011; OR = 1.39; CI 95 %: 1.07-1.81; Padj = 0.013 и OR = 1.70; CI 95 %: 1.19-2.43; Padj = 0.004, respectively). In the group of elderly women (aged 60-74 years), an association of the CAT gene polymorphism with the risk of developing luminal B subtype of breast cancer was found in a log-additive inheritance model (OR = 1.87; 95 % CI: 1.22-2.85; Padj = 0.0024). Using MDR analysis, the most optimal statistically significant 3-locus model of gene-gene interactions in the development of luminal B Her2-negative subtype breast cancer was found. MDR analysis also showed a close interaction and mutual enhancement of effects between the APEX1 and SOD2 loci and the independence of the effects of these loci from the CAT locus in the formation of luminal B subtype breast cancer.

Clinical, pathological and gene expression profiling of estrogen receptor discordance in breast cancer

BACKGROUND

Breast cancer (BC) is the world's largest tumor species in which hormone receptor-positive patients have relatively good prognosis. However, majority of patients will develop late resistance, one of the important factors is due to the loss of the original estrogen receptor (ER) expression.

METHODS

We conducted this study in 115 patients with BC who experienced second biopsy at Jiangsu Province Hospital (JSPH) and divided patients into two subgroups ER + to - and ER + to + . First, clinicopathological characteristics between two groups were evaluated. Second, we explored candidate genes related to BC ER intratumor heterogeneity by applying next-generation sequencing (NGS) in 42 patients. Multi-omics integrative analysis of tumor transcriptomic, cancer-related pathway, diagnostic and prognostic value and immune profile were conducted. Besides, preliminary assay were also used to evaluate the correlation between KMT2C and ERα (ESR1) expression. The CCK-8, 5-Ethynyl-2'-deoxyuridine (EdU) assays, Transwell assays and the wound scratch tests were applied to explore the cellular interactions between KMT2C and BC.

RESULTS

We find the histological type (p = 0.008) and disease-free survival (DFS) (p = 0.004) were significantly different in two subgroups. In Cox survival analysis, metastasis (Hazard ratio (HR) > 1, p = 0.007) and neo-adjuvant (HR < 1, p < 0.001) are independent prognostic factors of DFS. Besides, by analyzing NGS results, we found four genes KMT2C, FGFR19, FGF1 and FGF4 were highly mutated genes in ER + to - subgroup. Furthermore, the gene KMT2C displayed significant diagnostic value and prognostic value in BC and pan-cancer. In addition, a positive correlation between KMT2C expression and immune infiltrating levels of T cell CD4 + , macrophage and neutrophil was found. In the end, Western blot and RT-qPCR assay were used and found KMT2C and ERα (ESR1) expressions are strongly positive correlated in mRNA and protein level. Inhibition of KMT2C significantly reduced proliferation, invasion, and migration of MCF7 cells.

CONCLUSION

People in two cohorts from JSPH presented different clinical characteristics and prognosis. The gene KMT2C may affect the progression of BC by regulating the molecular, epigenetic activity and immune infiltration. It may also serve as a novel prognostic biomarker for BC patients who underwent ER status converted from positive to negative.

Estrogen α and β Receptor Expression in the Various Regions of Resected Glioblastoma Multiforme Tumors and in an In Vitro Model

Glioblastoma multiforme (GBM) is a malignant tumor with a higher prevalence in men and a higher survival rate in transmenopausal women. It exhibits distinct areas influenced by changing environmental conditions. This study examines how these areas differ in the levels of estrogen receptors (ERs) which play an important role in the development and progression of many cancers, and whose expression levels are often correlated with patient survival. This study utilized two research models: an in vitro model employing the U87 cell line and a second model involving tumors resected from patients (including tumor core, enhancing tumor region, and peritumoral area). ER expression was assessed at both gene and protein levels, with the results validated using confocal microscopy and immunohistochemistry. Under hypoxic conditions, the U87 line displayed a decrease in ERβ mRNA expression and an increase in ERα mRNA expression. In patient samples, ERβ mRNA expression was lower in the tumor core compared to the enhancing tumor region (only in males when the study group was divided by sex). In addition, ERβ protein expression was lower in the tumor core than in the peritumoral area (only in women when the study group was divided by sex). Immunohistochemical analysis indicated the highest ERβ protein expression in the enhancing tumor area, followed by the peritumoral area, and the lowest in the tumor core. The findings suggest that ER expression may significantly influence the development of GBM, exhibiting variability under the influence of conditions present in different tumor areas.

Molecular Research and Treatment of Breast Cancer 2.0

Breast cancer is the primary contributor to cancer-related deaths among women [...].

A deep learning based holistic diagnosis system for immunohistochemistry interpretation and molecular subtyping

BACKGROUND

Breast cancer in different molecular subtypes, which is determined by the overexpression rates of human epidermal growth factor receptor 2 (HER2), estrogen receptor (ER), progesterone receptor (PR), and Ki67, exhibit distinct symptom characteristics and sensitivity to different treatment. The immunohistochemical method, one of the most common detecting tools for tumour markers, is heavily relied on artificial judgment and in clinical practice, with an inherent limitation in interpreting stability and operating efficiency. Here, a holistic intelligent breast tumour diagnosis system has been developed for tumour-markeromic analysis, combining the automatic interpretation and clinical suggestion.

METHODS

The holistic intelligent breast tumour diagnosis system included two main modules. The interpreting modules were constructed based on convolutional neural network, for comprehensively extracting and analyzing the multi-features of immunostaining. Referring to the clinical classification criteria, the interpreting results were encoded in a low-dimensional feature representation in the subtyping module, to efficiently output a holistic detecting result of the critical tumour-markeromic with diagnosis suggestions on molecular subtypes.

RESULTS

The overexpression rates of HER2, ER, PR, and Ki67, as well as an effective determination of molecular subtypes were successfully obtained by this diagnosis system, with an average sensitivity of 97.6 % and an average specificity of 96.1 %, among those, the sensitivity and specificity for interpreting HER2 were up to 99.8 % and 96.9 %.

CONCLUSION

The holistic intelligent breast tumour diagnosis system shows improved performance in the interpretation of immunohistochemical images over pathologist-level, which can be expected to overcome the limitations of conventional manual interpretation in efficiency, precision, and repeatability.

p66ShcA promotes malignant breast cancer phenotypes by alleviating energetic and oxidative stress

Significant efforts have focused on identifying targetable genetic drivers that support the growth of solid tumors and/or increase metastatic ability. During tumor development and progression to metastatic disease, physiological and pharmacological selective pressures influence parallel adaptive strategies within cancer cell sub-populations. Such adaptations allow cancer cells to withstand these stressful microenvironments. This Darwinian model of stress adaptation often prevents durable clinical responses and influences the emergence of aggressive cancers with increased metastatic fitness. However, the mechanisms contributing to such adaptive stress responses are poorly understood. We now demonstrate that the p66ShcA redox protein, itself a ROS inducer, is essential for survival in response to physiological stressors, including anchorage independence and nutrient deprivation, in the context of poor outcome breast cancers. Mechanistically, we show that p66ShcA promotes both glucose and glutamine metabolic reprogramming in breast cancer cells, to increase their capacity to engage catabolic metabolism and support glutathione synthesis. In doing so, chronic p66ShcA exposure contributes to adaptive stress responses, providing breast cancer cells with sufficient ATP and redox balance needed to withstand such transient stressed states. Our studies demonstrate that p66ShcA functionally contributes to the maintenance of aggressive phenotypes and the emergence of metastatic disease by forcing breast tumors to adapt to chronic and moderately elevated levels of oxidative stress.

Invasive papillary carcinoma of the breast

Invasive papillary carcinoma is a rare form of breast cancer that is more likely to occur in postmenopausal women. Previous studies have been limited to case reports and small retrospective studies, leading to low awareness of this type of tumor and difficult clinical management. According to the available literature, invasive papillary carcinoma exhibits unique pathological features and biological behaviors. Invasive papillary carcinoma is mostly luminal type, with a low rate of lymph node metastasis, which underlies its favorable prognosis. The effectiveness of adjuvant therapy in reducing tumor burden and improving prognosis in patients with invasive papillary carcinoma remains uncertain. Due to the rarity of the lesion, conducting prospective clinical trials is impractical. The use of biological models, such as organoids, can help alleviate the impact of the scarcity of this condition on research. In addition, invasive papillary carcinoma is affected by specific genomic events, and more extensive studies of gene expression profiling may provide molecular-level insights to make optimal therapeutic decisions.

Mechanical effects modulate drug resistance in MCF-7-derived organoids: Insights into the wnt/β-catenin pathway

Addressing drug resistance poses a significant challenge in cancer treatment, as cancer cells develop diverse mechanisms to evade chemotherapy drugs, leading to treatment failure and disease relapse. Three-dimensional (3D) cell culture has emerged as a valuable model for studying drug resistance, although the underlying mechanisms remain elusive. By obtaining a better understanding of drug resistance within the 3D culture environment, we can develop more effective strategies to overcome it and improve the success of cancer treatments. Notably, the physical structure undergoes notable changes in 3D culture, with mechanical effects believed to play a pivotal role in drug resistance. Hence, our study aimed to explore the influence of mechanical effects on drug resistance by analyzing data related to "drug resistance" and "mechanobiology". Through this analysis, we identified β-catenin and JNK1 as potential factors, which were further examined in MCF-7 cells cultivated under both 2D and 3D culture conditions. Our findings demonstrate that β-catenin is activated through canonical and non-canonical pathways and associated with the drug resistance, particularly in organoids obtained under 3D culture.

Targeting the Tumor Microenvironment in Breast Cancer: Prognostic and Predictive Significance and Therapeutic Opportunities

Breast cancer is one of the most prevalent tumors among women. Its prognosis and treatment outcomes depend on factors related to tumor cell biology. However, recent studies have revealed the critical role of the tumor microenvironment (TME) in the development, progression, and treatment response of breast cancer. In this review, we explore the different components of the TME and their relevance as prognostic and predictive biomarkers in breast cancer. In addition, techniques for assessing the tumor microenvironment, such as immunohistochemistry or gene expression profiling, and their clinical utility in therapeutic decision-making are examined. Finally, therapeutic strategies targeting the TME are reviewed, highlighting their potential clinical benefits. Overall, this review emphasizes the importance of the TME in breast cancer and its potential as a clinical tool for better patient stratification and the design of personalized therapies.

AI-enabled routine H&E image based prognostic marker for early-stage luminal breast cancer

Breast cancer (BC) grade is a well-established subjective prognostic indicator of tumour aggressiveness. Tumour heterogeneity and subjective assessment result in high degree of variability among observers in BC grading. Here we propose an objective Haematoxylin & Eosin (H&E) image-based prognostic marker for early-stage luminal/Her2-negative BReAst CancEr that we term as the BRACE marker. The proposed BRACE marker is derived from AI based assessment of heterogeneity in BC at a detailed level using the power of deep learning. The prognostic ability of the marker is validated in two well-annotated cohorts (Cohort-A/Nottingham: n = 2122 and Cohort-B/Coventry: n = 311) on early-stage luminal/HER2-negative BC patients treated with endocrine therapy and with long-term follow-up. The BRACE marker is able to stratify patients for both distant metastasis free survival (p = 0.001, C-index: 0.73) and BC specific survival (p < 0.0001, C-index: 0.84) showing comparable prediction accuracy to Nottingham Prognostic Index and Magee scores, which are both derived from manual histopathological assessment, to identify luminal BC patients that may be likely to benefit from adjuvant chemotherapy.

Oncogenic PIK3CA recruits myeloid-derived suppressor cells to shape the immunosuppressive tumour microenvironment in luminal breast cancer through the 5-lipoxygenase-dependent arachidonic acid pathway

BACKGROUND

Oncogenic PIK3CA mutations (PIK3CAmut ) frequently occur in a higher proportion in luminal breast cancer (LBC), especially in refractory advanced cases, and are associated with changes in tumour cellular metabolism. Nevertheless, its effect on the progression of the immune microenvironment (TIME) within tumours and vital molecular events remains veiled.

METHODS

Multiplex immunohistochemistry (mIHC) and single-cell mass cytometry (CyTOF) was used to describe the landscape of TIME in PIK3CAmut LBC. The PIK3CA mutant cell lines were established using CRISPER/Cas9 system. The gene expression levels, protein secretion and activity of signaling pathways were measured by real-time RT-PCR, ELISA, immunofluorescence staining or western blotting. GSEA analysis, transwell chemotaxis assay, live cell imaging, flow cytometry metabolite analysis targeting arachidonic acid, Dual-luciferase reporter assay, and Chromatin immunoprecipitation assay were used to investigate the underlying function and mechanism of the PI3K/5-LOX/LTB4 axis.

RESULTS

PIK3CAmut LBC cells can induce an immunosuppressive TIME by recruiting myeloid-derived suppressor cells (MDSCs) and excluding cytotoxic T cells via the arachidonic acid (AA) metabolism pathway. Mechanistically, PIK3CAmut activates the transcription of 5-lipoxygenase (5-LOX) in a STAT3-dependent manner, which in turn directly results in high LTB4 production, binding to BLT2 on MDSCs and promoting their infiltration. Since a suppressive TIME is a critical barrier for the success of cancer immunotherapy, the strategies that can convert "cold" tumours into "hot" tumours were compared. Targeted therapy against the PI3K/5-LOX/LTB4 axis synergizing with immune checkpoint blockade (ICB) therapy achieved dramatic shrinkage in vivo.

CONCLUSIONS

The results emphasize that PIK3CAmut can induce immune evasion by recruiting MDSCs through the 5-LOX-dependent AA pathway, and combination targeted therapy with ICB may provide a promising treatment option for refractory advanced LBC patients.

Evaluation of tumour infiltrating lymphocytes in luminal breast cancer using artificial intelligence

BACKGROUND

Tumour infiltrating lymphocytes (TILs) are a prognostic parameter in triple-negative and human epidermal growth factor receptor 2 (HER2)-positive breast cancer (BC). However, their role in luminal (oestrogen receptor positive and HER2 negative (ER + /HER2-)) BC remains unclear. In this study, we used artificial intelligence (AI) to assess the prognostic significance of TILs in a large well-characterised cohort of luminal BC.

METHODS

Supervised deep learning model analysis of Haematoxylin and Eosin (H&E)-stained whole slide images (WSI) was applied to a cohort of 2231 luminal early-stage BC patients with long-term follow-up. Stromal TILs (sTILs) and intratumoural TILs (tTILs) were quantified and their spatial distribution within tumour tissue, as well as the proportion of stroma involved by sTILs were assessed. The association of TILs with clinicopathological parameters and patient outcome was determined.

RESULTS

A strong positive linear correlation was observed between sTILs and tTILs. High sTILs and tTILs counts, as well as their proximity to stromal and tumour cells (co-occurrence) were associated with poor clinical outcomes and unfavourable clinicopathological parameters including high tumour grade, lymph node metastasis, large tumour size, and young age. AI-based assessment of the proportion of stroma composed of sTILs (as assessed visually in routine practice) was not predictive of patient outcome. tTILs was an independent predictor of worse patient outcome in multivariate Cox Regression analysis.

CONCLUSION

AI-based detection of TILs counts, and their spatial distribution provides prognostic value in luminal early-stage BC patients. The utilisation of AI algorithms could provide a comprehensive assessment of TILs as a morphological variable in WSIs beyond eyeballing assessment.

Ki-67 index after neoadjuvant endocrine therapy as a prognostic biomarker in patients with ER-positive/HER2-negative early breast cancer: a systematic review and meta-analysis

BACKGROUND

Neoadjuvant treatment discriminates responders, but pathologic complete response is uncommon in oestrogen receptor (ER)-positive/HER2-negative early breast cancer. We aimed to assess the prognostic value of Ki-67 index after neoadjuvant endocrine therapy (NET).

METHODS

We conducted a systematic literature search of PubMed, Embase, CENTRAL, and conference proceedings up to 22nd August 2023 to identify studies reporting the association of Ki-67 index after NET with recurrence-free survival (RFS) and/or overall survival (OS) in women with ER-positive/HER2-negative early breast cancer. We combined RFS and OS hazard ratios (HRs) with 95% confidence intervals (CIs).

RESULTS

Twelve studies including 7897 patients were analysed. Most studies were clinical trials (n = 7547) including only postmenopausal women (n = 3953) treated with aromatase inhibitor (n = 3359). Three studies evaluated Ki-67 in a preplanned core biopsy at 2-4 weeks of NET (n = 3348), while nine evaluated Ki-67 in the surgical specimen (n = 4549) after 2-24 weeks of NET. Median follow-up ranged between 37 and 95 months for RFS and 62-84 months for OS. High Ki-67 index after NET was significantly associated with worse RFS (HR 2.48, 95% CI 1.86-3.30) and OS (HR 2.66, 95% CI 1.65-4.28). A sensitivity analysis including three studies that measured Ki-67 in a preplanned core biopsy showed similar association with RFS (HR 2.41, 95% CI 1.77-3.30).

CONCLUSIONS

High Ki-67 after NET is associated with worse survival outcomes, even after a short course of NET, emphasising the prognostic value of this biomarker in women with ER-positive/HER2-negative early breast cancer.

'Social' versus 'asocial' cells-dynamic competition flux balance analysis

In multicellular organisms cells compete for resources or growth factors. If any one cell type wins, the co-existence of diverse cell types disappears. Existing dynamic Flux Balance Analysis (dFBA) does not accommodate changes in cell density caused by competition. Therefore we here develop 'dynamic competition Flux Balance Analysis' (dcFBA). With total biomass synthesis as objective, lower-growth-yield cells were outcompeted even when cells synthesized mutually required nutrients. Signal transduction between cells established co-existence, which suggests that such 'socialness' is required for multicellularity. Whilst mutants with increased specific growth rate did not outgrow the other cell types, loss of social characteristics did enable a mutant to outgrow the other cells. We discuss that 'asocialness' rather than enhanced growth rates, i.e., a reduced sensitivity to regulatory factors rather than enhanced growth rates, may characterize cancer cells and organisms causing ecological blooms. Therapies reinforcing cross-regulation may therefore be more effective than those targeting replication rates.

Tailoring Potential Natural Compounds for the Treatment of Luminal Breast Cancer

Breast cancer (BC) is the most diagnosed cancer worldwide, mainly affecting the epithelial cells from the mammary glands. When it expresses the estrogen receptor (ER), the tumor is called luminal BC, which is eligible for endocrine therapy with hormone signaling blockade. Hormone therapy is essential for the survival of patients, but therapeutic resistance has been shown to be worrying, significantly compromising the prognosis. In this context, the need to explore new compounds emerges, especially compounds of plant origin, since they are biologically active and particularly promising. Natural products are being continuously screened for treating cancer due to their chemical diversity, reduced toxicity, lower side effects, and low price. This review summarizes natural compounds for the treatment of luminal BC, emphasizing the activities of these compounds in ER-positive cells. Moreover, their potential as an alternative to endocrine resistance is explored, opening new opportunities for the design of optimized therapies.

Multi-modal transcriptomic analysis unravels enrichment of hybrid epithelial/mesenchymal state and enhanced phenotypic heterogeneity in basal breast cancer

Intra-tumoral phenotypic heterogeneity promotes tumor relapse and therapeutic resistance and remains an unsolved clinical challenge. It manifests along multiple phenotypic axes and decoding the interconnections among these different axes is crucial to understand its molecular origins and to develop novel therapeutic strategies to control it. Here, we use multi-modal transcriptomic data analysis - bulk, single-cell and spatial transcriptomics - from breast cancer cell lines and primary tumor samples, to identify associations between epithelial-mesenchymal transition (EMT) and luminal-basal plasticity - two key processes that enable heterogeneity. We show that luminal breast cancer strongly associates with an epithelial cell state, but basal breast cancer is associated with hybrid epithelial/mesenchymal phenotype(s) and higher phenotypic heterogeneity. These patterns were inherent in methylation profiles, suggesting an epigenetic crosstalk between EMT and lineage plasticity in breast cancer. Mathematical modelling of core underlying gene regulatory networks representative of the crosstalk between the luminal-basal and epithelial-mesenchymal axes recapitulate and thus elucidate mechanistic underpinnings of the observed associations from transcriptomic data. Our systems-based approach integrating multi-modal data analysis with mechanism-based modeling offers a predictive framework to characterize intra-tumor heterogeneity and to identify possible interventions to restrict it.

Involvement of the AKT Pathway in Resistance to Erlotinib and Cabozantinib in Triple-Negative Breast Cancer Cell Lines

Resistance to protein tyrosine kinase inhibitors (TKIs) presents a significant challenge in therapeutic target development for cancers such as triple-negative breast cancer (TNBC), where conventional therapies are ineffective at combatting systemic disease. Due to increased expression, the receptor tyrosine kinases EGFR (epidermal growth factor receptor) and c-Met are potential targets for treatment. However, targeted anti-EGFR and anti-c-Met therapies have faced mixed results in clinical trials due to acquired resistance. We hypothesize that adaptive responses in regulatory kinase networks within the EGFR and c-Met signaling axes contribute to the development of acquired erlotinib and cabozantinib resistance. To test this, we developed two separate models for cabozantinib and erlotinib resistance using the MDA-MB-231 and MDA-MB-468 cell lines, respectively. We observed that erlotinib- or cabozantinib-resistant cell lines demonstrate enhanced cell proliferation, migration, invasion, and activation of EGFR or c-Met downstream signaling (respectively). Using a SILAC (Stable Isotope Labeling of Amino acids in Cell Culture)-labeled quantitative mass spectrometry proteomics approach, we assessed the effects of erlotinib or cabozantinib resistance on the phosphoproteome, proteome, and kinome. Using this integrated proteomics approach, we identified several potential kinase mediators of cabozantinib resistance and confirmed the contribution of AKT1 to erlotinib resistance in TNBC-resistant cell lines.

In Silico Analysis of the Effect of Hydrastis canadensis on Controlling Breast Cancer

Background and Objectives: Breast cancer is a significant type of cancer among women worldwide. Studies have reported the anti-carcinogenic activity of Hydrastis Canadensis (Goldenseal) in cancer cell lines. Hydrastis Canadensis could help eliminate toxic substances due to its anti-cancer, anti-inflammatory, and other properties. The design phase includes the identification of potential and effective molecules through modern computational techniques. Objective: This work aims to study Hydrastis Canadensis's effect in controlling hormone-independent breast cancer through in-silico analysis. Materials and Methods: The preliminary screening of reported phytochemicals includes biomolecular networking. Identifying functionally relevant phytochemicals and the respective target mutations/genes leads to selecting 3D proteins of the desired mutations being considered the target. Interaction studies have been conducted using docking. The kinetic and thermodynamic stability of complexes was studied through molecular dynamic simulation and MM-PBSA/GBSA analysis. Pharmacodynamic and pharmacokinetic features have been predicted. The mechanism-wise screening, functional enrichment, and interactional studies suggest that canadaline and Riboflavin effectively interact with the target proteins. Results: Hydrastis Canadensis has been identified as the effective formulation containing all these constituents. The phytoconstituents; Riboflavin and Canadensis showed good interaction with the targets of hormone-independent breast cancer. The complexes were found to be kinetically and thermodynamically stable. Conclusions: Hydrastis Canadensis has been identified as effective in controlling 'hormone-independent or basal-like breast cancer' followed by 'hormone-dependent breast cancer: Luminal A' and Luminal B.

A three-gene signature marks the time to locoregional recurrence in luminal-like breast cancer

BACKGROUND

Gene expression profiling (GEP)-based prognostic signatures are being rapidly integrated into clinical decision making for systemic management of breast cancer patients. However, GEP remains relatively underdeveloped for locoregional risk assessment. Yet, locoregional recurrence (LRR), especially early after surgery, is associated with poor survival.

PATIENTS AND METHODS

GEP was carried out on two independent luminal-like breast cancer cohorts of patients developing early (≤5 years after surgery) or late (>5 years) LRR and used, by a training and testing approach, to build a gene signature able to intercept women at risk of developing early LRR. The GEP data of two in silico datasets and of a third independent cohort were used to explore its prognostic value.

RESULTS

Analysis of the first two cohorts led to the identification of three genes, CSTB, CCDC91 and ITGB1, whose expression, derived by principal component analysis, generated a three-gene signature significantly associated with early LRR in both cohorts (P value <0.001 and 0.005, respectively), overcoming the discriminatory capability of age, hormone receptor status and therapy. Remarkably, the integration of the signature with these clinical variables led to an area under the curve of 0.878 [95% confidence interval (CI) 0.810-0.945]. In in silico datasets we found that the three-gene signature retained its association, showing higher values in the early relapsed patients. Moreover, in the third additional cohort, the signature significantly associated with relapse-free survival (hazard ratio 1.56, 95% CI 1.04-2.35).

CONCLUSIONS

Our three-gene signature represents a new exploitable tool to aid treatment choice in patients with luminal-like breast cancer at risk of developing early recurrence.

Deep learning radiopathomics based on preoperative US images and biopsy whole slide images can distinguish between luminal and non-luminal tumors in early-stage breast cancers

BACKGROUND

For patients with early-stage breast cancers, neoadjuvant treatment is recommended for non-luminal tumors instead of luminal tumors. Preoperative distinguish between luminal and non-luminal cancers at early stages will facilitate treatment decisions making. However, the molecular immunohistochemical subtypes based on biopsy specimens are not always consistent with final results based on surgical specimens due to the high intra-tumoral heterogeneity. Given that, we aimed to develop and validate a deep learning radiopathomics (DLRP) model to preoperatively distinguish between luminal and non-luminal breast cancers at early stages based on preoperative ultrasound (US) images, and hematoxylin and eosin (H&E)-stained biopsy slides.

METHODS

This multicentre study included three cohorts from a prospective study conducted by our team and registered on the Chinese Clinical Trial Registry (ChiCTR1900027497). Between January 2019 and August 2021, 1809 US images and 603 H&E-stained whole slide images (WSIs) from 603 patients with early-stage breast cancers were obtained. A Resnet18 model pre-trained on ImageNet and a multi-instance learning based attention model were used to extract the features of US and WSIs, respectively. An US-guided Co-Attention module (UCA) was designed for feature fusion of US and WSIs. The DLRP model was constructed based on these three feature sets including deep learning US feature, deep learning WSIs feature and UCA-fused feature from a training cohort (1467 US images and 489 WSIs from 489 patients). The DLRP model's diagnostic performance was validated in an internal validation cohort (342 US images and 114 WSIs from 114 patients) and an external test cohort (270 US images and 90 WSIs from 90 patients). We also compared diagnostic efficacy of the DLRP model with that of deep learning radiomics model and deep learning pathomics model in the external test cohort.

FINDINGS

The DLRP yielded high performance with area under the curve (AUC) values of 0.929 (95% CI 0.865-0.968) in the internal validation cohort, and 0.900 (95% CI 0.819-0.953) in the external test cohort. The DLRP also outperformed deep learning radiomics model based on US images only (AUC 0.815 [0.719-0.889], p = 0.027) and deep learning pathomics model based on WSIs only (AUC 0.802 [0.704-0.878], p = 0.013) in the external test cohort.

INTERPRETATION

The DLRP can effectively distinguish between luminal and non-luminal breast cancers at early stages before surgery based on pretherapeutic US images and biopsy H&E-stained WSIs, providing a tool to facilitate treatment decision making in early-stage breast cancers.

FUNDING

Natural Science Foundation of Guangdong Province (No. 2023A1515011564), and National Natural Science Foundation of China (No. 91959127; No. 81971631).

Hypoxia-driven ncRNAs in breast cancer

Low oxygen tension, or hypoxia is the driving force behind tumor aggressiveness, leading to therapy resistance, metastasis, and stemness in solid cancers including breast cancer, which now stands as the leading cause of cancer-related mortality in women. With the great advancements in exploring the regulatory roles of the non-coding genome in recent years, the wide spectrum of hypoxia-responsive genome is not limited to just protein-coding genes but also includes multiple types of non-coding RNAs, such as micro RNAs, long non-coding RNAs, and circular RNAs. Over the years, these hypoxia-responsive non-coding molecules have been greatly implicated in breast cancer. Hypoxia drives the expression of these non-coding RNAs as upstream modulators and downstream effectors of hypoxia inducible factor signaling in the favor of breast cancer through a myriad of molecular mechanisms. These non-coding RNAs then contribute in orchestrating aggressive hypoxic tumor environment and regulate cancer associated cellular processes such as proliferation, evasion of apoptotic death, extracellular matrix remodeling, angiogenesis, migration, invasion, epithelial-to-mesenchymal transition, metastasis, therapy resistance, stemness, and evasion of the immune system in breast cancer. In addition, the interplay between hypoxia-driven non-coding RNAs as well as feedback and feedforward loops between these ncRNAs and HIFs further contribute to breast cancer progression. Although the current clinical implications of hypoxia-driven non-coding RNAs are limited to prognostics and diagnostics in breast cancer, extensive explorations have established some of these hypoxia-driven non-coding RNAs as promising targets to treat aggressive breast cancers, and future scientific endeavors hold great promise in targeting hypoxia-driven ncRNAs at clinics to treat breast cancer and limit global cancer burden.

ZNF703 mRNA-Targeting Antisense Oligonucleotide Blocks Cell Proliferation and Induces Apoptosis in Breast Cancer Cell Lines

The luminal B molecular subtype of breast cancers (BC) accounts for more than a third of BCs and is associated with aggressive clinical behavior and poor prognosis. The use of endocrine therapy in BC treatment has significantly contributed to the decrease in the number of deaths in recent years. However, most BC patients with prolonged exposure to estrogen receptor (ER) selective modulators such as tamoxifen develop resistance and become non-responsive over time. Recent studies have implicated overexpression of the ZNF703 gene in BC resistance to endocrine drugs, thereby highlighting ZNF703 inhibition as an attractive modality in BC treatment, especially luminal B BCs. However, there is no known inhibitor of ZNF703 due to its nuclear association and non-enzymatic activity. Here, we have developed an antisense oligonucleotide (ASO) against ZNF703 mRNA and shown that it downregulates ZNF703 protein expression. ZNF703 inhibition decreased cell proliferation and induced apoptosis. Combined with cisplatin, the anti-cancer effects of ZNF703-ASO9 were improved. Moreover, our work shows that ASO technology may be used to increase the number of targetable cancer genes.

LINC00426 is a potential immune phenotype-related biomarker and an overall survival predictor in PAM50 luminal B breast cancer

Background: Breast cancer (BRCA) represents the most frequent diagnosed malignancy in women worldwide. Despite treatment advances, BRCAs eventually develop resistance to targeted therapies, resulting in poor prognosis. The identification of new biomarkers, like immune-related long non-coding RNAs (lncRNAs), could contribute to the clinical management of BRCA patients. In this report, we evaluated the LINC00426 expression in PAM50 BRCA subtypes from two clinical independent cohorts (BRCA-TCGA and GEO-GSE96058 datasets). Methods and results: Using Cox regression models and Kaplan-Meier survival analyses, we identified that LINC00426 expression was a consistent overall survival (OS) predictor in luminal B (LB) BRCA patients. Subsequently, differential gene expression and gene set enrichment analyses identified that LINC00426 expression was associated with different immune-related and cancer-related pathways and processes in LB BRCA. Additionally, the LINC00426 expression was correlated with the infiltration level of diverse immune cell populations, alongside immune checkpoint and cytolytic activity-related gene expression. Conclusion: This evidence suggests that LINC00426 is a potential biomarker of immune phenotype and an OS predictor in PAM50 LB BRCA.

Selective Estrogen receptor degraders (SERDs) for the treatment of breast cancer: An overview

Discovery of SERDs has changed the direction of anticancer research, as more than 70% of breast cancer cases are estrogen receptor positive (ER+). Therapies such as selective estrogen receptor modulators (SERM) and aromatase inhibitors (AI's) have been effective, but due to endocrine resistance, SERDs are now considered essential therapeutics for the treatment of ER+ breast cancer. The present review deliberates the pathophysiology of SERDs from the literature covering various molecules in clinical trials. Estrogen receptors active sites distinguishing characteristics and interactions with currently available FDA-approved drugs have also been discussed. Designing strategy of previously reported SERDs, their SAR analysis, in silico, and the biological efficacy have also been summarized along with appropriate examples.

Preoperative prediction of Ki-67 status in invasive breast carcinoma using dynamic contrast-enhanced MRI, diffusion-weighted imaging and diffusion tensor imaging

Background

The Ki-67 is a beneficial marker of tumor aggressiveness. It is proliferation index that has been used to distinguish luminal B from luminal A breast cancers. By fast progress in quantitative radiology modalities, tumor biology and genetics can be assessed in a more accurate, predictive, and cost-effective method. The aim of this study was to assess the role of dynamic contrast-enhanced magnetic resonance imaging, diffusion-weighted imaging and diffusion tensor imaging in prediction of Ki-67 status in patients with invasive breast carcinoma estimate cut off values between breast cancer with high Ki-67 status and those with low Ki-67 status.

Results

Cut off ADC (apparent diffusion co-efficient) value of 0.657 mm2/s had 96.4% sensitivity, 75% specificity and 93.8% accuracy in differentiating cases with high Ki67 from those with low Ki67. Cut off maximum enhancement value of 1715 had 96.4% sensitivity, 75% specificity and 93.8% accuracy in differentiating cases with high Ki67 from those with low Ki67. Cut off washout rate of 0.73 I/S had 60.7% sensitivity, 75% specificity and 62.5% accuracy in differentiating cases with high Ki67 from those with low Ki67. Cut off time to peak value of 304 had 71.4% sensitivity, 75% specificity and 71.9% accuracy in differentiating cases with high Ki67 from those with low Ki67.

Conclusions

ADC, time to peak and maximum enhancement values had high sensitivity, specificity and accuracy in differentiating breast cancer with high Ki-67 status from those with low Ki-67 status.

Epigenetic-Metabolic Interplay in the DNA Damage Response and Therapeutic Resistance of Breast Cancer

Therapy resistance is imposing a daunting challenge on effective clinical management of breast cancer. Although the development of resistance to drugs is multifaceted, reprogramming of energy metabolism pathways is emerging as a central but heterogenous regulator of this therapeutic challenge. Metabolic heterogeneity in cancer cells is intricately associated with alterations of different signaling networks and activation of DNA damage response pathways. Here we consider how the dynamic metabolic milieu of cancer cells regulates their DNA damage repair ability to ultimately contribute to development of therapy resistance. Diverse epigenetic regulators are crucial in remodeling the metabolic landscape of cancer. This epigenetic-metabolic interplay profoundly affects genomic stability of the cancer cells as well as their resistance to genotoxic therapies. These observations identify defining mechanisms of cancer epigenetics-metabolism-DNA repair axis that can be critical for devising novel, targeted therapeutic approaches that could sensitize cancer cells to conventional treatment strategies.

Long-term adherence to healthful and unhealthful plant-based diets and breast cancer risk overall and by hormone receptor and histologic subtypes among postmenopausal females

BACKGROUND

Epidemiological studies assessing the influence of vegetarian diets on breast cancer (BC) risk have produced inconsistent results. Few studies have assessed how the incremental decrease in animal foods and the quality of plant foods are linked with BC.

OBJECTIVES

Disentangle the influence of plant-based diet quality on BC risk between postmenopausal females.

METHODS

Total of 65,574 participants from the E3N (Etude Epidémiologique auprès de femmes de la Mutuelle Générale de l'Education Nationale) cohort were followed from 1993-2014. Incident BC cases were confirmed through pathological reports and classified into subtypes. Cumulative average scores for healthful (hPDI) and unhealthful (uPDI) plant-based diet indices were developed using self-reported dietary intakes at baseline (1993) and follow-up (2005) and divided into quintiles. Cox proportional hazards models were used to estimate adjusted HR and 95% CI.

RESULTS

During a mean follow-up of 21 y, 3968 incident postmenopausal BC cases were identified. There was a nonlinear association between adherence to hPDI and BC risk (Pnonlinear < 0.01). Compared to participants with low adherence to hPDI, those with high adherence had a lower BC risk [HRQ3 compared withQ1 (95% CI): 0.79 (0.71, 0.87) and HRQ4 compared with Q1 (95% CI): 0.78 (0.70, 0.86)]. In contrast, higher adherence to unhealthful was associated with a linear increase in BC risk [Pnonlinear = 0.18; HRQ5 compared with Q1 (95% CI): 1.20 (1.08, 1.33); Ptrend < 0.01]. Associations were similar according to BC subtypes (Pheterogeneity > 0.05 for all).

CONCLUSIONS

Long-term adherence to healthful plant foods with some intake of unhealthy plant and animal foods may reduce BC risk with an optimal risk reduction in the moderate intake range. Adherence to an unhealthful plant-based diet may increase BC risk. These results emphasize the importance of the quality of plant foods for cancer prevention. This trial was registered at clinicaltrials.gov (NCT03285230).

The role of the NDRG1 in the pathogenesis and treatment of breast cancer

Breast cancer (BC) is the leading cause of cancer death in women. This disease is heterogeneous, with clinical subtypes being estrogen receptor-α (ER-α) positive, having human epidermal growth factor receptor 2 (HER2) overexpression, or being triple-negative for ER-α, progesterone receptor, and HER2 (TNBC). The ER-α positive and HER2 overexpressing tumors can be treated with agents targeting these proteins, including tamoxifen and pertuzumab, respectively. Despite these treatments, resistance and metastasis are problematic, while TNBC is challenging to treat due to the lack of suitable targets. Many studies examining BC and other tumors indicate a role for N-myc downstream-regulated gene-1 (NDRG1) as a metastasis suppressor. The ability of NDRG1 to inhibit metastasis is due, in part, to the inhibition of the initial step in metastasis, namely the epithelial-to-mesenchymal transition. Paradoxically, there are also reports of NDRG1 playing a pro-oncogenic role in BC pathogenesis. The oncogenic effects of NDRG1 in BC have been reported to relate to lipid metabolism or the mTOR signaling pathway. The molecular mechanism(s) of how NDRG1 regulates the activity of multiple signaling pathways remains unclear. Therapeutic strategies that up-regulate NDRG1 have been developed and include agents of the di-2-pyridylketone thiosemicarbazone class. These compounds target oncogenic drivers in BC cells, suppressing the expression of multiple key hormone receptors including ER-α, progesterone receptor, androgen receptor, and prolactin receptor, and can also overcome tamoxifen resistance. Considering the varying role of NDRG1 in BC pathogenesis, further studies are required to examine what subset of BC patients would benefit from pharmacopeia that up-regulate NDRG1.

Relationship between pathological response and molecular subtypes in locally advanced breast cancer patients receiving neoadjuvant chemotherapy

Majority of patients with breast cancer were diagnosed with locally advanced stages of the disease (54%). This study aimed to explain the pathological response received to neoadjuvant chemotherapy (NACT) according to the molecular classification of breast cancer in patients with locally advanced tumors. One hundred and one patients with locally advanced breast cancer treated with neoadjuvant chemotherapy were analyzed. Patients were classified into five molecular subtypes based on the profile of the estrogen receptor, progesterone receptor, HER2, and Ki-67. We determined associations between complete pathological response (no invasive tumor after neoadjuvant chemotherapy) and molecular subgroups. Most patients had luminal A tumors (n: 28, 27.7%). The overall rate of complete pathological response (pCR) was 34.7% (n:35). Tumors that presented with the highest rate of pCR were pure HER2-positive, at 60% (n:6; OR, 3.2; 95% CI, 0.8-12.2). According to logistic regression analysis, the factors affecting pCR were HER2 positivity and clinically positive axilla before NACT. Luminal A tumors had a significantly lower pCR rate. (7.1%,p: 0.001). Despite the low pCR rate, Luminal A tumor had the best survival rate in the subgroups (p < 0.001). However, there was no difference between EFS and OS according to pCR in any molecular subgroups. Pathological complete response is directly related to the subtypes of breast cancer. A high complete pathological response rate is observed in the pure HER2-positive group. However, EFS and OS were not statistically significant in patients with and without pCR.

lncRNA HCG11 suppresses cell proliferation in hormone receptor-positive breast cancer via SRSF1/β-catenin

Hormone receptor positive (HR-positive) breast cancer (BC) is the most common subtype of breast cancer. Despite adjuvant endocrine therapy and chemotherapy-based treatment, the therapeutic response is often not satisfactory in HR-positive BC patients. Therefore, elucidating the mechanisms that regulate the progression of HR-positive BC is urgently required to identify new therapeutic targets. Previously, HLA Complex Group 11 (HCG11), located on the major histocompatibility complex (MHC) region, was found to be abnormally expressed in a variety of tumor cells. However, the role of HCG11 in HR-positive BC cells has not been explored to date. In the current study, we found that HCG11 is downregulated in HR-positive BC tissues and cell lines. Both in vitro and in vivo, HCG11 acts as a tumor suppressor in HR-positive BC cells. Furthermore, the mechanistic details unraveled that HCG11 recruits Serine/arginine-rich splicing factor 1 (SRSF1) to target β-catenin mRNA for promoting the translation of β-catenin. Our study emphasizes the potential of HCG11 as a novel intervention target for HR-positive BC treatment.

Breast carcinogenesis induced by organophosphorous pesticides

Breast cancer is a major health threat to women worldwide and the leading cause of cancer-related death. The use of organophosphorous pesticides has increased in agricultural environments and urban settings, and there is evidence that estrogen may increase breast cancer risk in women. The mammary gland is an excellent model for examining its susceptibility to different carcinogenic agents due to its high cell proliferation capabilities associated with the topography of the mammary parenchyma and specific stages of gland development. Several experimental cellular models are presented here, in which the animals were exposed to chemical compounds such as pesticides, and endogenous substances such as estrogens that exert a significant effect on normal breast cell processes at different levels. Such models were developed by the effect of malathion, parathion, and eserine, influenced by estrogen demonstrating features of cancer initiation in vivo as tumor formation in rodents; and in vitro in the immortalized normal breast cell line MCF-10F, that when transformed showed signs of carcinogenesis such as increased cell proliferation, anchorage independence, invasive capabilities, modulation of receptors and genomic instability. The role of acetylcholine was also demonstrated in the MCF-10F, suggesting a role not only as a neurotransmitter but also with other functions, such as induction of cell proliferation, playing an important role in cancer. Of note, this is a unique experimental approach that identifies mechanistic signs that link organophosphorous pesticides with breast carcinogenesis.

FDXR drives primary and endocrine-resistant tumor cell growth in ER+ breast cancer via CPT1A-mediated fatty acid oxidation

Background

The majority of breast cancers (BCs) expressing estrogen receptor (ER) have shown endocrine resistance. Our previous study demonstrated that ferredoxin reductase (FDXR) promoted mitochondrial function and ER+ breast tumorigenesis. But the underlying mechanism is not clear.

Methods

Liquid chromatography (LC) tandem mass spectrometry (MS/MS)-based metabolite profiling was utilized to reveal the metabolites regulated by FDXR. RNA microarray was utilized to determine the potential downstream targets of FDXR. Seahorse XF24 analyzer was performed to analyze the FAO-mediated oxygen consumption rate (OCR). Q-PCR and western blotting assays were used to measure expression levels of FDXR and CPT1A. MTS, 2D colony formation and anchorage-independent growth assays were used to evaluate the effects of FDXR or drug treatments on tumor cell growth of primary or endocrine-resistant breast cancer cells.

Results

We found that depletion of FDXR inhibited fatty acid oxidation (FAO) by suppressing CPT1A expression. Endocrine treatment increased the expression levels of both FDXR and CPT1A. Further, we showed that depletion of FDXR or FAO inhibitor etomoxir treatment reduced primary and endocrine-resistant breast cancer cell growth. Therapeutically, combining endocrine therapy with FAO inhibitor etomoxir synergistically inhibits primary and endocrine-resistant breast cancer cell growth.

Discussion

We reveal that the FDXR-CPT1A-FAO signaling axis is essential for primary and endocrine-resistant breast cancer cell growth, thus providing a potential combinatory therapy against endocrine resistance in ER+ breast cancer.

Timed hazard networks: Incorporating temporal difference for oncogenetic analysis

Oncogenetic graphical models are crucial for understanding cancer progression by analyzing the accumulation of genetic events. These models are used to identify statistical dependencies and temporal order of genetic events, which helps design targeted therapies. However, existing algorithms do not account for temporal differences between samples in oncogenetic analysis. This paper introduces Timed Hazard Networks (TimedHN), a new statistical model that uses temporal differences to improve accuracy and reliability. TimedHN models the accumulation process as a continuous-time Markov chain and includes an efficient gradient computation algorithm for optimization. Our simulation experiments demonstrate that TimedHN outperforms current state-of-the-art graph reconstruction methods. We also compare TimedHN with existing methods on a luminal breast cancer dataset, highlighting its potential utility. The Matlab implementation and data are available at https://github.com/puar-playground/TimedHN.

Role of STING protein in breast cancer: mechanisms and therapeutic implications

Breast cancer is one of the most frequent causes of cancer related death worldwide, and despite the significant advances in therapeutic approaches, a significant proportion of patients succumb to metastasis and tumor recurrence. Breast cancer is an immunogenic cancer, and therefore, immunotherapy is considered a major therapeutic strategy. The survival rate has been increased significantly in HER2+ breast cancers after immunotherapy by monoclonal antibodies alone, or combined with chemical anti-cancer agents. Moreover, in triple negative breast cancer (TNBC), a number of novel agents called immune checkpoint inhibitors have shown optimal efficacy. The major hindrance in cancer immunotherapy is frequent development of resistance and cancer remission. cGAS-STING pathway has a key role in anti-cancer immunity as its downstream signals especially type I interferon (IFN) acts as a link between innate and adaptive immunity. Considering the roles of type I IFN in enhancing dendritic cells activity, promoting the functions of CD8⁺ T cells, and protecting the effector cells against apoptosis, the induction of cGAS-STING pathway demonstrated promising therapeutic effects against breast cancer, especially in triple negative breast cancers. In this review, we discuss the latest findings and the recent advances regarding the role of cGAS-STING pathway and its activation in breast cancer.

High SURF4 expression is associated with poor prognosis of breast cancer

SURF4 has been suggested as an oncogene in cancer. However, the role of SURF4 in breast cancer has not been demonstrated yet. The data were obtained from TCGA database and 1104 patients were analyzed using bioinformatics analysis. SURF4 is significantly (P < 0.001) highly expressed in tumor. High expression of SURF4 was observed in T4, infiltrating ductal carcinoma, ER negative, PR negative, and HER2 positive, female, patients without lymph node metastasis, HER2 overexpression type, and deceased patients. As for characteristics correlated with high expression of SURF4, gender, histological type, molecular subtype, ER, PR, HER2, and vital status exhibited significant differences. The age (HR: 2.317, P < 0.001), stage (HR: 2.090, P < 0.001), and SURF4 expression (HR: 1.958, P = 0.005) exhibited independent prognostic value for overall survival (OS). Patients with high SURF4 expression, higher age, equivocal HER2, higher stages, or positive margin status had shorter OS. The stage (HR: 1.579, P < 0.001), and margin status (HR: 1.463, P = 0.006) exhibited independent prognostic value for relapse-free survival of breast cancer. High expression of SURF4 was first found in breast cancer. High SURF4 expression was observed in breast cancer tissue and cell. SURF4 promoted the proliferation and migration of 4T1 cells. SURF4 may be a biomarker in diagnosis and prognosis of breast cancer.

Tamoxifen resistance-related ceRNA network for breast cancer

Background: Tamoxifen (TMX) is one of the most widely used drugs to treat breast cancer (BC). However, acquired drug resistance is still a major obstacle to its application, rendering it crucial to explore the mechanisms of TMX resistance in BC. This aims of this study were to identify the mechanisms of TMX resistance and construct ceRNA regulatory networks in breast cancer. Methods: GEO2R was used to screen for differentially expressed mRNAs (DEmRNAs) leading to drug resistance in BC cells. MiRTarbase and miRNet were used to predict miRNAs and lncRNAs upstream, and the competing endogenous RNA (ceRNA) regulatory network of BC cell resistance was constructed by starBase. We used the Kaplan-Meier plotter and Gene Expression Profiling Interactive Analysis (GEPIA) to analyze the expression and prognostic differences of genes in the ceRNA network with core axis, and qRT-PCR was used to further verify the above conclusions. Results: We found that 21 DEmRNAs were upregulated and 43 DEmRNA downregulated in drug-resistant BC cells. DEmRNAs were noticeably enriched in pathways relevant to cancer. We then constructed a protein-protein interaction (PPI) network based on the STRING database and defined 10 top-ranked hub genes among the upregulated and downregulated DEmRNAs. The 20 DEmRNAs were predicted to obtain 113 upstream miRNAs and 501 lncRNAs. Among them, 7 mRNAs, 22 lncRNAs, and 11 miRNAs were used to structure the ceRNA regulatory network of drug resistance in BC cells. 4 mRNAs, 4 lncRNAs, and 3 miRNAs were detected by GEPIA and the Kaplan-Meier plotter to be significantly associated with BC expression and prognosis. The differential expression of the genes in BC cells was confirmed by qRT-PCR. Conclusion: The ceRNA regulatory network of TMX-resistant BC was successfully constructed and confirmed. This will provide an important resource for finding therapeutic targets for TMX resistance, where the discovery of candidate conventional mechanisms can aid clinical decision-making. In addition, this resource will help discover the mechanisms behind this type of resistance.

Classification of Subgroups with Immune Characteristics Based on DNA Methylation in Luminal Breast Cancer

Luminal breast cancer (BC) accounts for a large proportion of patients in BC, with high heterogeneity. Determining the precise subtype and optimal selection of treatment options for luminal BC is a challenge. In this study, we proposed an MSBR framework that integrate DNA methylation profiles and transcriptomes to identify immune subgroups of luminal BC. MSBR was implemented both on a key module scoring algorithm and “Boruta” feature selection method by DNA methylation. Luminal A was divided into two subgroups and luminal B was divided into three subgroups using the MSBR. Furthermore, these subgroups were defined as different immune subgroups in luminal A and B respectively. The subgroups showed significant differences in DNA methylation levels, immune microenvironment (immune cell infiltration, immune checkpoint PD1/PD-L1 expression, immune cell cracking activity (CYT)) and pathology features (texture, eccentricity, intensity and tumor-infiltrating lymphocytes (TILs)). The results also showed that there is a subgroup in both luminal A and B that has the benefit from immunotherapy. This study proposed a classification of luminal BC from the perspective of epigenetics and immune characteristics, which provided individualized treatment decisions.

Breast MRI Segmentation and Ki-67 High- and Low-Expression Prediction Algorithm Based on Deep Learning

Background and Objective. Breast cancer is a common malignant tumor that seriously threatens the health of women in my country and even around the world. The proliferation marker Ki-67 has been utilized to distinguish luminal B from luminal A tumors and is a reliable indicator of more aggressive breast cancer growth. If a reliable prediction method for breast cancer patients to avoid invasive damage can be found to predict Ki-67 before pathological examination, it will be very beneficial for doctors to formulate later treatment plans and provide more useful treatment options. Methodology. This paper proposes a tumor segmentation and prediction framework based on the combination of improved attention U-Net and SVM. The framework first improves on attention U-Net by introducing coefficients for learning multidimensional attention. Make the attention mechanism more aware of the main situation in the segmentation process. At the same time, the segmented breast MRI results and corresponding labels were input into the SVM classifier to accurately predict the expression of Ki-67. Results. The DSC, PPV, and sensitivity of our combined model are 0.94, 0.93, and 0.94, respectively, with better segmentation performance. And we compare with the segmentation frameworks of other papers and find that our combined model can make accurate segmentation of breast tumors. Conclusion. Our method can adapt to the variability of breast tumors and segment breast tumors accurately and efficiently. In the future, it can be widely used in clinical practice, so as to help the clinic better formulate a reasonable diagnosis and treatment plan for breast cancer patients.

The False Dawn of Polygenic Risk Scores for Human Disease Prediction

Polygenic risk scores (PRSs) are being constructed for many diseases and are presented today as a promising avenue in the field of human genetics. These scores aim at predicting the risk of developing a disease by leveraging the many genome-wide association studies (GWAS) conducted during the two last decades. Important investments are being made to improve score estimates by increasing GWAS sample sizes, by developing more sophisticated methods, and by proposing different corrections for potential biases. PRSs have entered the market with direct-to-consumer companies proposing to compute them from saliva samples and even recently to help parents select the healthiest embryos. In this paper, we recall how PRSs arose and question the credit they are given by revisiting underlying assumptions in light of the history of human genetics and by comparing them with estimated breeding values (EBVs) used for selection in livestock.

RET signaling pathway and RET inhibitors in human cancer

Rearranged during transfection (RET) receptor tyrosine kinase was first identified over thirty years ago as a novel transforming gene. Since its discovery and subsequent pathway characterization, RET alterations have been identified in numerous cancer types and are most prevalent in thyroid carcinomas and non-small cell lung cancer (NSCLC). In other tumor types such as breast cancer and salivary gland carcinomas, RET alterations can be found at lower frequencies. Aberrant RET activity is associated with poor prognosis of thyroid and lung carcinoma patients, and is strongly correlated with increased risk of distant metastases. RET aberrations encompass a variety of genomic or proteomic alterations, most of which confer constitutive activation of RET. Activating RET alterations, such as point mutations or gene fusions, enhance activity of signaling pathways downstream of RET, namely PI3K/AKT, RAS/RAF, MAPK, and PLCγ pathways, to promote cell proliferation, growth, and survival. Given the important role that mutant RET plays in metastatic cancers, significant efforts have been made in developing inhibitors against RET kinase activity. These efforts have led to FDA approval of Selpercatinib and Pralsetinib for NSCLC, as well as, additional selective RET inhibitors in preclinical and clinical testing. This review covers the current biological understanding of RET signaling, the impact of RET hyperactivity on tumor progression in multiple tumor types, and RET inhibitors with promising preclinical and clinical efficacy.

Breast Cancer Stem Cells: Signaling Pathways, Cellular Interactions, and Therapeutic Implications

Breast cancer stem cells (BCSCs) constitute a small population of cells within breast cancer and are characterized by their ability to self-renew, differentiate, and recapitulate the heterogeneity of the tumor. Clinically, BCSCs have been correlated with cancer progression, metastasis, relapse, and drug resistance. The tumorigenic roles of BCSCs have been extensively reviewed and will not be the major focus of the current review. Here, we aim to highlight how the crucial intrinsic signaling pathways regulate the fate of BCSCs, including the Wnt, Notch, Hedgehog, and NF-κB signaling pathways, as well as how different cell populations crosstalk with BCSCs within the TME, including adipocytes, endothelial cells, fibroblasts, and immune cells. Based on the molecular and cellular activities of BCSCs, we will also summarize the targeting strategies for BCSCs and related clinical trials. This review will highlight that BCSC development in breast cancer is impacted by both BCSC endogenous signaling and external factors in the TME, which provides an insight into how to establish a comprehensively therapeutic strategy to target BCSCs for breast cancer treatments.

Novel Immune-Related Gene Signature for Risk Stratification and Prognosis of Survival in ER (+) and/or PR (+) and HER2 (-) Breast Cancer

Background: Although intrinsic molecular subtype has been widely used, there remains great clinical heterogeneity of prognosis in the estrogen receptor (ER)- and/or progesterone receptor (PR)-positive and human epidermal growth factor receptor 2 (HER2)-negative breast cancer (BC).

Methods: The transcriptome expression data of messenger RNA (mRNA) were downloaded from The Cancer Genome Atlas (TCGA), Molecular Taxonomy of Breast Cancer International Consortium (METABRIC), and the Gene Expression Omnibus (GEO) databases. Immune-related genes were acquired from the ImmPort database and additional literature search. Univariate Cox, LASSO regression, and multivariate Cox regression were used to screen prognostic immune-related genes and establish the risk signature. The correlation between the risk signature and clinical characteristics, the abundances of immune cells within the tumor microenvironment, and cancer phenotypes were further assessed.

Results: Of note, 102 immune-related prognostic genes were identified in the METABRIC dataset by univariate Cox analysis. Consecutively, 7 immune-related genes (SHMT2, AGA, COL17A1, FLT3, SLC7A2, ATP6AP1, and CCL19) were selected to establish the risk signature by LASSO regression and multivariate Cox analysis. Its performance was further verified in TCGA and GSE21653 datasets. Multivariate Cox analysis showed that the risk signature was an independent prognostic factor. The 7-gene signature showed a significant correlation with intrinsic molecular subtypes and 70-gene signature. Furthermore, the CD4⁺ memory T cells were significantly higher in the low-risk group while a significantly higher proportion of M0-type macrophages was found in the high-risk group in both METABRIC and TCGA cohorts, which may have an influence on the prognosis. Furthermore, we found that the low-risk group may be associated with the immune-related pathway and the high-risk group was with the cell cycle-related pathway, which also showed an impact on the prognosis.

Conclusion: These seven immune-related gene risk signatures provided an effective method for prognostic stratification in ER (+) and/or PR (+) and HER2 (−) BC.

Comparative analysis of the molecular subtype landscape in canine and human mammary gland tumors

Breast cancers in humans belong to one of several intrinsic molecular subtypes each with different tumor biology and different clinical impact. Mammary gland tumors in dogs are proposed as a relevant comparative model for human breast cancer; however, it is still unclear whether the intrinsic molecular subtypes have the same significance in dogs and humans. Using publicly available data, we analyzed gene expression and whole-exome sequencing data from 158 canine mammary gland tumors. We performed molecular subtyping using the PAM50 method followed by subtype-specific comparisons of gene expression characteristics, mutation patterns and copy number profiles between canine tumors and human breast tumors from The Cancer Genome Atlas (TCGA) breast cancer cohort (n = 1097). We found that luminal A canine tumors greatly resemble luminal A human tumors both in gene expression characteristics, mutations and copy number profiles. Also, the basal-like canine and human tumors were relatively similar, with low expression of luminal epithelial markers and high expression of genes involved in cell proliferation. There were, however, distinct differences in immune-related gene expression patterns in basal-like tumors between the two species. Characteristic HER2-enriched and luminal B subtypes were not present in the canine cohort, and we found no tumors with high-level ERBB2 amplifications. Benign and malignant canine tumors displayed similar PAM50 subtype characteristics. Our findings indicate that deeper understanding of the different molecular subtypes in canine mammary gland tumors will further improve the value of canines as comparative models for human breast cancer.

Microcalcifications and Peritumoral Edema Predict Survival Outcome in Luminal Breast Cancer Treated with Neoadjuvant Chemotherapy

Background Little is known regarding findings at imaging associated with survival in patients with luminal breast cancer treated with neoadjuvant chemotherapy (NAC). Purpose To determine the relationship between imaging (MRI, US, and mammography) and clinical-pathologic variables in predicting distant metastasis-free survival (DMFS) and overall survival (OS) in patients with luminal breast cancer treated with NAC. Materials and Methods In this retrospective study, consecutive women with luminal breast cancer who underwent NAC followed by surgery were identified from the breast cancer registries of two hospitals. Women from one hospital between January 2003 and July 2015 were classified into the development cohort, and women from the other hospital between January 2007 and July 2015 were classified into the validation cohort. MRI scans, US scans, and mammograms before and after NAC (hereafter, referred to as pre- and post-NAC, respectively) and clinical-pathologic data were reviewed. Peritumoral edema was defined as the water-like high signal intensity surrounding the tumor on T2-weighted MRI scans. The prediction model was developed in the development cohort by using Cox regression and then tested in the validation cohort. Results The development cohort consisted of 318 women (68 distant metastases, 54 deaths) and the validation cohort consisted of 165 women (37 distant metastases, 14 deaths) (median age, 46 years in both cohorts). Post-NAC MRI peritumoral edema, age younger than 40 years, clinical N2 or N3, and lymphovascular invasion were associated with worse DMFS (all, P < .05). Pre-NAC mammographic microcalcifications, post-NAC MRI peritumoral edema, age older than 60 years, and clinical T3 or T4 were associated with worse OS (all, P < .05). The prediction model showed good discrimination ability (C index, 0.67-0.75 for DMFS and 0.70-0.77 for OS) and stratified prognosis into low-risk and high-risk groups (10-year DMFS rates, 79% vs 21%, respectively; and 10-year OS rates, 95%-96% vs 63%-67%, respectively) in the validation cohort. Conclusion MRI features and clinical-pathologic variables were identified that were associated with prolonged survival of patients with luminal breast cancer treated with neoadjuvant chemotherapy. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Kataoka in this issue.

Association of Obesity and Luminal Subtypes in Prognosis and Adjuvant Endocrine Treatment Effectiveness Prediction in Chinese Breast Cancer Patients

Purpose

To evaluate the influence of obesity on clinicopathological characteristics of breast cancer; to explore the effect of obesity on the prognosis and performance of endocrine therapy in breast cancer patients.

Methods

Patients with luminal/HER2-negative early breast cancer were included and categorized into the non-obese (BMI<28kg/m²) and obese (BMI≥28kg/m²) groups according to body mass index (BMI). Clinicopathological characteristics and treatment modalities were compared between groups. Interaction of adjuvant endocrine therapy with obesity was analyzed.

Results

A total of 2,875 patients were included: 2,598 non-obese and 277 obese. A higher rate of patients with comorbidities (OR: 2.83, 95%CI 2.13-3.74, P<0.001) or PR-positive tumor (OR: 1.63, 95%CI 1.03-2.58, P=0.037) were identified in the obese group. Obesity was not associated with disease recurrence (P=0.839) or overall survival (P=0.140) in the whole population. Subgroup analysis did show an association with worse relapse-free survival (RFS, HR 3.48, 95%CI 1.31-9.22, P=0.012) and overall survival (OS, HR 4.67, 95%CI 1.28-16.95, P=0.019) in luminal A breast cancer. These results could not be reproduced in the luminal B subtype with a RFS (HR 0.78, 95%CI 0.41-1.49, P=0.454) or OS (HR 1.17, 95%CI 0.50-2.74, P=0.727). Furthermore, obesity did not impact endocrine therapy effectiveness in Tamoxifen or the aromatase inhibitor group (RFS: interact P=0.381; OS: interact P=0.888).

Conclusions

The impact of obesity on prognosis interacted with luminal subtype status in Chinese breast cancer patients which was not related with endocrine treatment modality.

Investigation of Molecular Features Involved in Clinical Responses and Survival in Advanced Endometrial Carcinoma Treated by Hormone Therapy

Hormone therapy (HT) is an effective treatment for metastatic endometrial carcinoma (mEC), with limited toxicity and low cost. We focused on molecular analysis of mECs treated by HT and, for the first time to date, we compared the genomic profiles of paired metastasis and primary ECs. The main objective was to identify predictive factors of the response to HT as well as specific altered signaling pathways driving mEC biology. From 1052 patients with EC treated by HT in two French cancer centers, 32 with endometrioid EC and 6 with high grade serous EC were included. We evaluated hormone receptors (HR) and mismatch repair proteins expression by immunohistochemistry and gene alterations by targeted next-generation sequencing and array-based comparative genomic hybridization. Several variables were tested in univariate and multivariate analyses to identify potential associations with (i) the clinical benefit of HT (CBHT) and (ii) a longer response (>18 months) (LRHT) and overall survival (OS). We compared the biological and genomic profiles of 11 primary/metastatic EC pairs. Thirty tumors (78.9%) were HR-positive and 6 (15.8%) showed microsatellite instability (MSI). The genomic profiles of 34 tumors showed an average altered genome of 3.26%, DNA repair homologous recombination deficiency in five tumors (14.7%), and 17 regions significantly targeted by amplification/deletion. Thirty-three tumors had 273 variants (158 genes, median of 7 mutations/sample), including 112 driver mutations. TP53, PTEN, PPP2R1A, ARID1A, FGFR2, and PIK3CA were the most frequently mutated. Based on the genomic status, nine oncogenic pathways were altered in more than 25% of primary EC. Clinically, 22 (57.9%) and 6 (15.8%) patients presented CBHT and LRHT, respectively. Neither oncogenic pathways alterations nor the variables tested were associated with CBHT and LRHT. Only patient’s age, mitotic index and the presence of at least one HR were associated with OS. Paired analysis of the primary/metastatic samples showed that among the 22 mutations acquired in the metastatic counterparts, the most frequently targeted genes were involved in pathways that might confer a selective advantage to cancer metastasis including hormone resistance. In conclusion, only patient’s age, mitotic index and the presence of at least one HR were associated with OS. The identification of gene mutations newly acquired in metastasis might help to better understand the formation of EC metastasis and select the best actionable candidates for HT-treated patients at the metastatic stage.

Mammographic Density Decline, Tamoxifen Response, and Prognosis by Molecular Characteristics of Estrogen Receptor-Positive Breast Cancer

BACKGROUND

Mammographic breast density (MBD) decline post-tamoxifen initiation is a favorable prognostic factor in estrogen receptor (ER)-positive breast cancer (BC) and has potential utility as a biomarker of tamoxifen response. However, the prognostic value of MBD decline may vary by molecular characteristics among ER-positive patients.

METHODS

We investigated associations between MBD decline (≥10% vs <10%) and breast cancer-specific mortality (BCSM) among ER-positive breast cancer patients aged 36-87 years at diagnosis treated with tamoxifen at Kaiser Permanente Northwest (1990-2008). Patients who died of BC (case patients; n = 62) were compared with those who did not (control patients; n = 215) overall and by tumor molecular characteristics (immunohistochemistry [IHC]-based subtype [luminal A-like: ER-positive/progesterone receptor [PR]-positive/HER2-negative/low Ki67; luminal B-like: ER-positive and 1 or more of PR-negative, HER2-positive, high Ki67] and modified IHC [mIHC]-based recurrence score of ER/PR/Ki67). Percent MBD was measured in the unaffected breast at baseline mammogram (mean = 6 months before tamoxifen initiation) and follow-up (mean = 12 months post-tamoxifen initiation). Adjusted odds ratios (ORs) and 95% confidence intervals (CIs) were computed from logistic regression models. All statistical tests were 2-sided.

RESULTS

MBD decline was statistically significantly associated with reduced risk of BCSM overall (OR = 0.38, 95% CI = 0.15 to 0.92). This association was, however, stronger among women with aggressive tumor characteristics including luminal B-like (OR = 0.17, 95% CI = 0.04 to 0.73) vs A-like (OR = 0.74, 95% CI = 0.19 to 2.92); large (OR = 0.26, 95% CI = 0.08 to 0.78) vs small (OR = 0.41, 95% CI = 0.04 to 3.79) tumors; PR-negative (OR = 0.02, 95% CI = 0.001 to 0.37) vs PR-positive (OR = 0.50, 95% CI = 0.18 to 1.40) disease; and high (OR = 0.25, 95% CI = 0.07 to 0.93) vs low (OR = 0.44, 95% CI = 0.10 to 2.09) mIHC3 score.

CONCLUSION

The findings support MBD decline as a prognostic marker of tamoxifen response among patients with aggressive ER-positive BC phenotypes, for whom understanding treatment effectiveness is critical.