Identification of three subtypes of triple-negative breast cancer with potential therapeutic implications

Calpain 2 Isoform-Specific Cleavage of Filamin A Enhances HIF1α Nuclear Translocation, Promoting Metastasis in Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) remains a challenge due to its aggressive nature and limited therapeutic options. Calpain 2, a member of the calcium-dependent cysteine protease family, is particularly associated with poor prognosis in TNBC. This study explores the isoform-specific role of calpain 2 in TNBC, examining its correlation with prognosis and its mechanistic impact on metastasis. Bioinformatic analyses, including Kaplan-Meier survival plots, univariate Cox proportional analysis, and gene set enrichment analysis (GSEA), assessed CAPN2 expression and its association with mesenchymal genes in TNBC. Results of cell-based experiments with CAPN2 knockdown or overexpression indicate that elevated CAPN2 expression correlates with poor clinical outcomes and enhanced metastatic potential in TNBC. CAPN2 knockdown inhibited the epithelial-mesenchymal transition (EMT), reducing cancer cell proliferation, migration, and invasion. Calpain 2 downregulation reversed the EMT by reducing isoform-specific cleavage of filamin A, HIF1α nuclear localization and TWIST1 transcription. CNa 29, a calpain 2-specific inhibitor, reduced cancer cell proliferation, decreased filamin A cleavage, downregulated TWIST1 expression, and significantly retarded metastasis,. In conclusion, calpain 2 plays a critical role in TNBC progression by modulating HIF1α and TWIST1, to promote the EMT and metastasis. Isoform-selective inhibition of calpain 2 with CNa 29 presents a promising therapeutic strategy for managing TNBC.

Investigating the Prognostic Role of Telomerase-Related Cellular Senescence Gene Signatures in Breast Cancer Using Machine Learning

Background: Telomeres and cellular senescence are critical biological processes implicated in cancer development and progression, including breast cancer, through their influence on genomic stability and modulation of the tumor microenvironment. Methods: This study integrated bulk RNA sequencing and single-cell RNA sequencing (scRNA-seq) data to establish a gene signature associated with telomere maintenance and cellular senescence for prognostic prediction in breast cancer. Telomere-related genes (TEGs) and senescence-associated genes were curated from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. A comprehensive machine learning framework incorporating 101 algorithmic combinations across 10 survival modeling approaches, including random survival forests and ridge regression, was employed to develop a robust prognostic model. Results: A set of 19 key telomere- and senescence-related genes was identified as the optimal prognostic signature. The model demonstrated strong predictive accuracy and was successfully validated in multiple independent cohorts. Functional enrichment analyses indicated significant associations with immune responses and aging-related pathways. Single-cell transcriptomic analysis revealed marked cellular heterogeneity, identifying distinct subpopulations (fibroblasts and immune cells) with divergent risk scores and biological pathway activity. Additionally, pseudo-time trajectory analysis and intercellular communication mapping provided insights into the dynamic evolution of the tumor microenvironment. Immunohistochemical (IHC) validation using data from the Human Protein Atlas confirmed differential protein expression between normal and tumor tissues for several of the selected genes, reinforcing their biological relevance and clinical utility. Conclusions: This study presents a novel 19-gene telomere- and senescence-associated signature with strong prognostic value in breast cancer. These findings enhance our understanding of tumor heterogeneity and may inform precision oncology approaches and future therapeutic strategies.

A metabolic shift to the serine pathway induced by lipids fosters epigenetic reprogramming in nontransformed breast cells

Lipid metabolism and the serine, one-carbon, glycine (SOG) and methionine pathways are independently and significantly correlated with estrogen receptor-negative breast cancer (ERneg BC). Here, we propose a link between lipid metabolism and ERneg BC through phosphoglycerate dehydrogenase (PHGDH), the rate-limiting enzyme in the de novo serine pathway. We demonstrate that the metabolism of the paradigmatic medium-chain fatty acid octanoic acid leads to a metabolic shift toward the SOG and methionine pathways. PHGDH plays a role in both the forward direction, contributing to the production of S-adenosylmethionine, and the reverse direction, generating the oncometabolite 2-hydroxyglutarate, leading to epigenomic reprogramming and phenotypic plasticity. The methionine cycle is closely linked to the transsulfuration pathway. Consequently, we observe that the shift increases the antioxidant glutathione, which mitigates reactive oxygen species (ROS), enabling survival of a subset of cells that have undergone DNA damage. These metabolic changes contribute to several hallmarks of cancer.

Androgen receptor expression distribution characteristics in young female breast cancer patients in China: a study of clinicopathological features

Background

The expression of androgen receptor (AR) in breast cancer has potential implications for predicting clinical outcomes, especially amongst young female patients. Numerous studies have reported that the co-expression of AR with hormone receptors (HRs) is correlated with a favorable prognosis in breast cancer. However, research on the frequency and distribution of AR expression in Chinese breast cancer patients is limited. This study aims to investigate the relationship between AR expression and the expression of progesterone receptor (PR), estrogen receptor (ER), P53, human epidermal growth factor receptor 2 (HER2), and epidermal growth factor receptor (EGFR) in breast cancer patients, and the distribution of molecular subtypes of breast cancer. Further, we aim to explore the pattern of AR expression and its correlation with clinicopathological features and prognosis among young female patients in China.

Methods

Formalin-fixed paraffin-embedded tissue samples from 321 young female breast cancer patients were collected from the Third Hospital of Nanchang. Immunohistochemistry was used to assess the expression of AR, ER, PR, HER2, and Ki67. A statistical analysis was conducted to explore the correlation between the expression of AR and these molecular markers, as well as their distribution across different molecular subtypes of breast cancer, and their prognostic significance.

Results

A total of 321 breast cancer patients were included in this study. Significant correlations were found between the positive expression of AR and the high expression of PR and ER (P<0.001). The rate of P53 positivity was significantly higher in the AR-positive patients than the AR-negative patients (P=0.01). Additionally, HER2 expression was significantly higher in the AR-positive patients than the AR-negative patients (P<0.001). Notably, the rate of EGFR positivity was significantly lower in the AR-positive patients compared to AR-negative patients (P<0.001). In relation to the molecular subtypes, AR positivity was significantly associated with the luminal A subtype (P<0.001), while the triple-negative breast cancer (TNBC)/basal-like subtype was more common in the AR-negative patients.

Conclusions

This study revealed that in young female breast cancer patients in China, AR-positive breast cancer was significantly associated with the high expression of HRs, increased P53 expression and reduced EGFR expression. The expression status of AR can serve as a biomarker to predict therapeutic responses but could also influence the classification of molecular subtypes and the selection of treatment strategies.

Divide and Conquer-Targeted Therapy for Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) is the most aggressive and malignant type of breast cancer with limited treatment options and poor prognosis. One of the most significant impediments in TNBC treatment is the high heterogeneity of this disease, as highlighted by the detection of several molecular subtypes of TNBC. Each subtype is driven by distinct mutations and pathway aberrations, giving rise to specific molecular characteristics closely connected to clinical behavior, outcomes, and drug sensitivity. This review summarizes the knowledge regarding TNBC molecular subtypes and how it can be harnessed to devise tailored treatment strategies instead of blindly using targeted drugs. We provide an overview of novel targeted agents and key insights about new treatment modalities with an emphasis on the androgen receptor signaling pathway, cancer stem cell-associated pathways, phosphatidylinositol 3-kinase (PI3K)/AKT pathway, growth factor signaling, and immunotherapy.

Classifications of triple-negative breast cancer: insights and current therapeutic approaches

Triple-negative breast cancer (TNBC) is an aggressive and challenging type of cancer, characterized by the absence of specific receptors targeted by current therapies, which limits effective targeted treatment options. TNBC has a high risk of recurrence and distant metastasis, resulting in lower survival rates. Additionally, TNBC exhibits significant heterogeneity at histopathological, proteomic, transcriptomic, and genomic levels, further complicating the development of effective treatments. While some TNBC subtypes may initially respond to chemotherapy, resistance frequently develops, increasing the risk of aggressive recurrence. Therefore, precisely classifying and characterizing the distinct features of TNBC subtypes is crucial for identifying the most suitable molecular-based therapies for individual patients. In this review, we provide a comprehensive overview of these subtypes, highlighting their unique profiles as defined by various classification systems. We also address the limitations of conventional therapeutic approaches and explore innovative biological strategies, all aimed at advancing the development of targeted and effective therapeutic strategies for TNBC.

Glycosylation profiling of triple-negative breast cancer: clinical and immune correlations and identification of LMAN1L as a biomarker and therapeutic target

Introduction

Breast cancer (BC) is the most prevalent malignant tumor in women, with triple-negative breast cancer (TNBC) showing the poorest prognosis among all subtypes. Glycosylation is increasingly recognized as a critical biomarker in the tumor microenvironment, particularly in BC. However, the glycosylation-related genes associated with TNBC have not yet been defined. Additionally, their characteristics and relationship with prognosis have not been deeply investigated.

Methods

Transcriptomic analyses were used to identify a glycosylation-related signature (GRS) associated with TNBC prognosis. A machine learning-based prediction model was constructed and validated across multiple independent datasets. The model's predictive capability was extended to evaluate the prognosis of TNBC individuals, tumor immune microenvironment and immunotherapy response. LMAN1L (Lectin, Mannose Binding 1 Like) was identified as a novel prognostic marker in TNBC, and its biological effects were validated through experimental assays.

Results

The GRS showed significant prognostic relevance for TNBC patients. The risk model effectively predicted molecular features, including immune cell infiltration and potential responses to immunotherapy. Experimental validation confirmed LMAN1L as a novel glycosylation-related prognostic gene, with low expression significantly inhibiting TNBC cell proliferation and migration.

Discussion

Our GRS risk model demonstrates robust predictive capability for TNBC prognosis and immunotherapy response. This model offers a promising strategy for personalized treatment and improved clinical outcomes in TNBC.

Targeting CD200 in Breast Cancer: Opportunities and Challenges in Immunotherapeutic Strategies

One of the key factors that contribute to tumor progression and resistance is the immunosuppressive microenvironment of the tumor. CD200 is a recently identified cell surface glycoprotein recognized as an important molecule in breast cancer for its versatile modulation of the immune response via its receptor, CD200R. The interaction between CD200 and CD200R suppresses the immune activities against tumor cells and allows them to be undetected and, in doing so, to escape from the destructive capability of the immune cells. Here, we review recent advances and future trends in CD200-targeted therapies for cancer treatments. We also discuss molecular pathways that include variable expressions across different cancer types and their importance in treatment options.

Integrative analysis of homologous recombination repair patterns unveils prognostic signatures and immunotherapeutic insights in breast cancer

Globally, breast cancer (BC) is the leading cause of female death and morbidity. Homologous recombination repair (HRR) is critical in BC. However, the prognostic role and immunotherapy response of HRR in BC remains to be clarified. Firstly, we identified HRR types in BC samples from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) dataset (GSE42568) based on 65 HRR genes (HRRGs). A differentially expressed gene (DEG) list for different HRR types was generated. Then, the influences of gene sets composed of these DEGs on biological pathways and BC prognosis were explored. Next, we identified gene clusters based on gene sets composed of DEGs. Genes associated with prognosis for DEGs were identified using univariate Cox regression. Finally, the HRR score was constructed based on genes associated with prognosis. We analyzed how HRR score correlates with tumor mutation burden (TMB), immune cell infiltration (ICI), and immunotherapy response. Three HRR clusters were discovered. HRR subtype A demonstrated decreased infiltration and a high number of immunosuppressive cells with a poor prognosis. DEGs among various HRR types were predominantly enriched in cell cycle and genomic stability-related pathways. The prognostic model based on sixteen DEGs accurately predicted BC prognosis. The HRRGs were differentially expressed in three DEG clusters. TMB, ICI, and immunotherapy responses differed significantly between the high and low HRR groups (HSG, LSG). The HSG was distinguished by a high degree of ICI and low TMB. LSG had a better response to anti-PD-1 or anti-PD-1 and anti-CTLA4 combination therapy. This work revealed that HRR patterns would contribute to predicting prognosis and immunotherapy response in BC, which may benefit patients.

Targeting tumor-associated macrophages with nanocarrier-based treatment for breast cancer: A step toward developing innovative anti-cancer therapeutics

Tumor-associated macrophages (TAMs) promote tumor advancement in many ways, such as inducing angiogenesis and the formation of new blood vessels that provide tumors with nourishment and oxygen. TAMs also facilitate tumor invasion and metastasis by secreting enzymes that degrade the extracellular matrix and generating pro-inflammatory cytokines that enhance the migration of tumor cells. TAMs also have a role in inhibiting the immune response against malignancies. To accomplish this, they release immunosuppressive cytokines such as IL-10, and TAMs can hinder the function of T cells and natural killer cells, which play crucial roles in the immune system's ability to combat cancer. The role of TAMs in breast cancer advancement is a complex and dynamic field of research. Therefore, TAMs are a highly favorable focus for innovative breast cancer treatments. This review presents an extensive overview of the correlation between TAMs and breast cancer development as well as its role in the tumor microenvironment (TME) shedding light on their impact on tumor advancement and immune evasion mechanisms. Notably, our study provides an innovative approach to employing nanomedicine approaches for targeted TAM therapy in breast cancer, providing an in-depth overview of recent advances in this emerging field.

Integrated machine learning algorithms identify KIF15 as a potential prognostic biomarker and correlated with stemness in triple-negative breast cancer

Cancer stem cells (CSCs) have the potential to self-renew and induce cancer, which may contribute to a poor prognosis by enabling metastasis, recurrence, and therapy resistance. Hence, this study was performed to identify the association between CSC-related genes and triple-negative breast cancer (TNBC) development. Stemness gene sets were downloaded from StemChecker. Based on the online databases, a consensus clustering algorithm was conducted for unsupervised classification of TNBC samples. The variations between subtypes were assessed with regard to prognosis, tumor immune microenvironment (TIME), and chemotherapeutic sensitivity. The stemness-related gene signature was established and random survival forest analysis was employed to identify the core gene for validation experiments and tumor sphere formation assays. 499 patients with TNBC were classified into three subgroups and the Cluster 1 had a better OS than others. After that, WGCNA study was performed to identify genes important for Cluster 1 subtype. Out of all 8 modules, the subtype of Cluster 1 and the yellow module with 103 genes demonstrated the largest positive association. After that, a four-gene stemness-related signature was established. Based on the yellow module, the 39 potential pivotal genes were subjected to the random forest survival analysis to find out the gene that was relatively important for OS. KIF15 was confirmed as the targeted gene by LASSO and random survival forest analyses. In vitro experiments, the downregulation of KIF15 promoted the stemness of TNBC cells. The expression levels of stem cell markers Nanog, SOX2, and OCT4 were found to be elevated in TNBC cell lines after KIF15 inhibition. A stemness-associated risk model was constructed to forecast the clinical outcomes of TNBC patients. The downregulation of KIF15 expression in a subpopulation of TNBC stem cells may promote stemness and possibly TNBC progression.

Mesenchymal-like immune-altered is the fourth robust triple-negative breast cancer molecular subtype

BACKGROUND

Robust molecular subtyping of triple-negative breast cancer (TNBC) is a prerequisite for the success of precision medicine. Today, there is a clear consensus on three TNBC molecular subtypes: luminal androgen receptor (LAR), basal-like immune-activated (BLIA), and basal-like immune-suppressed (BLIS). However, the debate about the robustness of other subtypes is still open.

METHODS

An unprecedented number (n = 1942) of TNBC patient data was collected. Microarray- and RNAseq-based cohorts were independently investigated. Unsupervised analyses were conducted using k-means consensus clustering. Clusters of patients were then functionally annotated using different approaches. Prediction of response to chemotherapy and targeted therapies, immune checkpoint blockade, and radiotherapy were also screened for each TNBC subtype.

RESULTS

Four TNBC subtypes were identified in the cohort: LAR (19.36%); mesenchymal stem-like (MSL/MES) (17.35%); BLIA (31.06%); and BLIS (32.23%). Regarding the MSL/MES subtype, we suggest renaming it to mesenchymal-like immune-altered (MLIA) to emphasize its specific histological background and nature of immune response. Treatment response prediction results show, among other things, that despite immune activation, immune checkpoint blockade is probably less or completely ineffective in MLIA, possibly caused by mesenchymal background and/or an enrichment in dysfunctional cytotoxic T lymphocytes. TNBC subtyping results were included in the bc-GenExMiner v5.0 webtool ( http://bcgenex.ico.unicancer.fr ).

CONCLUSION

The mesenchymal TNBC subtype is characterized by an exhausted and altered immune response, and resistance to immune checkpoint inhibitors. Consensus for molecular classification of TNBC subtyping and prediction of cancer treatment responses helps usher in the era of precision medicine for TNBC patients.

Advancements in triple-negative breast cancer sub-typing, diagnosis and treatment with assistance of artificial intelligence : a focused review

Triple negative breast cancer (TNBC) is most aggressive type of breast cancer with multiple invasive sub-types and leading cause of women's death worldwide. Lack of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER-2) causes it to spread rapidly making its treatment challenging due to unresponsiveness towards anti-HER and endocrine therapy. Hence, needing advanced therapeutic treatments and strategies in order to get better recovery from TNBC. Artificial intelligence (AI) has been emerged by giving its high inputs in the automated diagnosis as well as treatment of several diseases, particularly TNBC. AI based TNBC molecular sub-typing, diagnosis as well as therapeutic treatment has become successful now days. Therefore, present review has reviewed recent advancements in the role and assistance of AI particularly focusing on molecular sub-typing, diagnosis as well as treatment of TNBC. Meanwhile, advantages, certain limitations and future implications of AI assistance in the TNBC diagnosis and treatment are also discussed in order to fully understand readers regarding this issue.

Peroxiporins in Triple-Negative Breast Cancer: Biomarker Potential and Therapeutic Perspectives

Triple-negative breast cancer (TNBC) remains one of the most challenging subtypes since it is initially characterized by the absence of specific biomarkers and corresponding targeted therapies. Advances in methodology, translational informatics, genomics, and proteomics have significantly contributed to the identification of therapeutic targets. The development of innovative treatments, such as antibody-drug conjugates and immune checkpoint inhibitors, alongside chemotherapy, has now become the standard of care. However, the quest for biomarkers defining therapy outcomes is still ongoing. Peroxiporins, which comprise a subgroup of aquaporins, which are membrane pores facilitating the transport of water, glycerol, and hydrogen peroxide, have emerged as potential biomarkers for therapy response. Research on peroxiporins reveals their involvement beyond traditional channeling activities, which is also reflected in their cellular localization and roles in cellular signaling pathways. This research on peroxiporins provides fresh insights into the mechanisms of therapy resistance in tumors, offering potential avenues for predicting treatment outcomes and tailoring successful TNBC therapies.

Necroptosis-related KLRB1 was a potent tumor suppressor and immunotherapy determinant in breast cancer

Breast cancer is a multifaceted and diverse illness that impacts millions of people globally. Identifying the underlying causes of BRCA and creating efficient treatment plans are urgent. Necroptosis is widely involved in cancer development. However, the specific roles of necroptosis in cancer immunotherapy of breast cancer have not been explored. In this study, we aim to establish the connection between necroptosis and immunotherapy in BRCA. TCGA, METABRIC, GSE103091, GSE159956, and GSE96058 were included for bioinformatics analysis. NMF and CoxBoost algorithms were used to develop the necroptosis-related patterns and model, respectively. A necroptosis-related model was developed and determined KLRB1 as a critical tumor suppressor by in vitro validation. The mutation characteristics, immune characteristics, and molecular functions of KLRB1 were explored. We further examined how necroptosis-related KLRB1 functions in BRCA as a powerful tumor suppressor and regulates the activity of macrophages by in vitro validation, including CCK8, EdU, and Transwell assays. KLRB1 was also revealed to be an immunotherapy determinant.

Effects of Eribulin on the RNA Content of Extracellular Vesicles Released by Metastatic Breast Cancer Cells

Extracellular vesicles (EVs) are small lipid particles secreted by almost all human cells into the extracellular space. They perform the essential function of cell-to-cell communication, and their role in promoting breast cancer progression has been well demonstrated. It is known that EVs released by triple-negative and highly aggressive MDA-MB-231 breast cancer cells treated with paclitaxel, a microtubule-targeting agent (MTA), promoted chemoresistance in EV-recipient cells. Here, we studied the RNA content of EVs produced by the same MDA-MB-231 breast cancer cells treated with another MTA, eribulin mesylate. In particular, we analyzed the expression of different RNA species, including mRNAs, lncRNAs, miRNAs, snoRNAs, piRNAs and tRNA fragments by RNA-seq. Then, we performed differential expression analysis, weighted gene co-expression network analysis (WGCNA), functional enrichment analysis, and miRNA-target identification. Our findings demonstrate the possible involvement of EVs from eribulin-treated cells in the spread of chemoresistance, prompting the design of strategies that selectively target tumor EVs.

Tertiary lymphoid structures predict survival and response to neoadjuvant therapy in locally advanced rectal cancer

Tertiary lymphoid structure (TLS) contributes to the anti-tumor immune response, and predicts the prognosis of colorectal cancer patients. However, the potential impact of TLS in shaping the immune status of rectal adenocarcinoma, and the intrinsic relationship between TLS and neoadjuvant therapies (neoTx) remain unclear. We performed hematoxylin-eosin staining, immunohistochemical and biomolecular analyses to investigate TLS and tumor-infiltrating lymphocytes (TILs) in 221 neoTx-treated and 242 treatment-naïve locally advanced rectal cancer (LARC) patients. High TLS density was significantly associated with the absence of vascular invasion, a lower neutrophil-to-lymphocyte ratio, increased TLS maturity, a longer recurrence-free survival (RFS) (hazard ratio [HR] 0.2985 95% confidence interval [CI] 0.1894-0.4706, p < 0.0001) and enhanced infiltration of adaptive immune cells. Biomolecular analysis showed that high TLS-score was strongly associated with more infiltration of immune cells and increased activation of immune-related pathways. TLS+ tumors in pre-treatment specimens were associated with a higher proportion of good respond (62.5% vs. 29.8%, p < 0.0002) and pathological complete remission (pCR) (40.0% vs. 11.1%, p < 0.0001), and significantly increased RFS (HR 0.3574 95%CI 0.1489-0.8578 p = 0.0213) compared with TLS- tumors in the neoTx cohort, which was confirmed in GSE119409 and GSE150082. Further studies showed that neoTx significantly reduced TLS density and maturity, and abolished the prognostic value of TLS. Our study illustrates that TLS may have a key role in mediating the T-cell-inflamed tumor microenvironment, which also provides a new direction for neoTx, especially neoadjuvant immunotherapy, in LRAC patients.

Natural History of Germline BRCA1 Mutated and BRCA Wild-type Triple-negative Breast Cancer

We report a deep next-generation sequencing analysis of 13 sequentially obtained tumor samples, eight sequentially obtained circulating tumor DNA (ctDNA) samples and three germline DNA samples over the life history of 3 patients with triple-negative breast cancer (TNBC), 2 of whom had germline pathogenic BRCA1 mutation, to unravel tumor evolution. Tumor tissue from all timepoints and germline DNA was subjected to whole-exome sequencing (WES), custom amplicon deep sequencing (30,000X) of a WES-derived somatic mutation panel, and SNP arrays for copy-number variation (CNV), while whole transcriptome sequencing (RNA-seq) was performed only on somatic tumor.There was enrichment of homologous recombination deficiency signature in all tumors and widespread CNV, which remained largely stable over time. Somatic tumor mutation numbers varied between patients and within each patient (range: 70-216, one outlier). There was minimal mutational overlap between patients with TP53 being the sole commonly mutated gene, but there was substantial overlap in sequential samples in each patient. Each patient's tumor contained a founding ("stem") clone at diagnosis, which persisted over time, from which all other clones ("subclone") were derived ("branching evolution"), which contained mutations in well-characterized cancer-related genes like PDGFRB, ARID2, TP53 (Patient_02), TP53, BRAF, BRIP1, CSF3R (Patient_04), and TP53, APC, EZH2 (Patient_07). Including stem and subclones, tumors from all patients were polyclonal at diagnosis and during disease progression. ctDNA recapitulated most tissue-derived stem clonal and subclonal mutations while detecting some additional subclonal mutations. RNA-seq revealed a stable basal-like pattern, with most highly expressed variants belonging to stem clone.

SIGNIFICANCE

In germline BRCA1 mutated and BRCA wild-type patients, TNBC shows a branching evolutionary pattern of mutations with a single founding clone, are polyclonal throughout their disease course, and have widespread copy-number aberrations. This evolutionary pattern may be associated with treatment resistance or sensitivity and could be therapeutically exploited.

Spatial multimodal analysis revealed tertiary lymphoid structures as a risk stratification indicator in combined hepatocellular-cholangiocarcinoma

The microenvironment created by tertiary lymphoid structures (TLSs) can support and regulate immune responses, affecting the prognosis and immune treatment of patients. Nevertheless, the actual importance of TLSs for predicting the prognosis of combined hepatocellular-cholangiocarcinoma (cHCC-CCA) patients remains unclear. Herein, using spatial transcriptomic analysis, we revealed that a gene signature of TLSs specific to cHCC-CCA was associated with high-intensity immune infiltration. Then, a novel scoring system was developed to evaluate the distribution and frequency of TLSs in intra-tumoral and extra-tumoral regions (iTLS and eTLS scores) in 146 cHCC-CCA patients. iTLS score was positively associated with promising prognosis, likely due to the decreased frequency of suppressive immune cell like Tregs, and the ratio of CD163+ macrophages to macrophages in intra-tumoral TLSs via imaging mass cytometry, while improved prognosis is not necessarily indicated by a higher eTLS score. Overall, this study highlights the potential of TLSs as a prognostic factor and an indicator of immune therapy in cHCC-CCA.

Single-cell histone chaperones patterns guide intercellular communication of tumor microenvironment that contribute to breast cancer metastases

BACKGROUND

Histone chaperones (HCs) are crucial for governing genome stability and gene expression in multiple cancers. However, the functioning of HCs in the tumor microenvironment (TME) is still not clearly understood.

METHODS

Self-tested single-cell RNA-seq data derived from 6 breast cancer (BC) patients with brain and liver metastases were reanalyzed by nonnegative matrix factorization (NMF) algorithm for 36 HCs. TME subclusters were observed with BC and immunotherapy public cohorts to assess their prognosis and immune response. The biological effect of HSPA8, one of the HCs, was verified by transwell assay and wound-healing assays.

RESULTS

Cells including fibroblasts, macrophages, B cells, and T cells, were classified into various subclusters based on marker genes. Additionally, it showed that HCs might be strongly associated with biological and clinical features of BC metastases, along with the pseudotime trajectory of each TME cell type. Besides, the results of bulk-seq analysis revealed that TME cell subclusters mediated by HCs distinguished significant prognostic value for BC patients and were relevant to patients' immunotherapy responses, especially for B cells and macrophages. In particular, CellChat analysis exhibited that HCs-related TME cell subclusters revealed extensive and diverse interactions with malignant cells. Finally, transwell and wound-healing assays exhibited that HSPA8 deficiency inhibited BC cell migration and invasion.

CONCLUSIONS

Collectively, our study first dissected HCs-guided intercellular communication of TME that contribute to BC metastases.

Is the Androgen Receptor a Viable Target in Triple Negative Breast Cancer in 5 Years?

Triple negative breast cancer (TNBC) is characterized by high rates of disease recurrence after definitive therapy, and median survival of less than 18 months in the metastatic setting. Systemic therapy options for TNBC consist primarily of cytotoxic chemotherapy-containing regimens, and while recently FDA-approved chemo-immunotherapy combinations and antibody-drug conjugates such as Sacituzumab govitecan have improved clinical outcomes, there remains an unmet need for more effective and less toxic therapies. A subset of TNBC expresses the androgen receptor (AR), a nuclear hormone steroid receptor that activates an androgen-responsive transcriptional program, and gene expression profiling has revealed a TNBC molecular subtype with AR expression and luminal and androgen responsive features. Both preclinical and clinical data suggest biologic similarities between luminal AR (LAR) TNBC and ER+ luminal breast cancer, including lower proliferative activity, relative chemoresistance, and high rates of oncogenic activating mutations in the phosphatidylinositol-3-kinase (PI3K) pathway. Preclinical LAR-TNBC models are sensitive to androgen signaling inhibitors (ASIs), and particularly given the availability of FDA-approved ASIs with robust efficacy in prostate cancer, there has been great interest in targeting this pathway in AR+ TNBC. Here, we review the underlying biology and completed and ongoing androgen-targeted therapy studies in early stage and metastatic AR+ TNBC.

PD-1/PD-L1 Inhibitors Response in Triple-Negative Breast Cancer: Can Long Noncoding RNAs Be Associated?

As immune checkpoint inhibitors (ICI) emerge as a paradigm-shifting treatment option for patients with advanced or metastatic cancer, there is a growing demand for biomarkers that can distinguish which patients are likely to benefit. In the case of triple-negative breast cancer (TNBC), characterized by a lack of therapeutic targets, pembrolizumab approval for high-risk early-stage disease occurred regardless of PD-L1 status, which keeps the condition in a biomarker limbus. In this review, we highlight the participation of long non-coding RNAs (lncRNAs) in the regulation of the PD-1/PD-L1 pathway, as well as in the definition of prognostic immune-related signatures in many types of tumors, aiming to shed light on molecules that deserve further investigation for a potential role as biomarkers. We also conducted a bioinformatic analysis to investigate lncRNAs already investigated in PD-1/PDL-1 pathways in other cancer types, considering the TNBC molecular context. In this sense, from the generated data, we evidence here two lncRNAs, UCA1 and HCP5, which have not yet been identified in the context of the tumoral immune response in breast cancer. These candidates can be further explored to verify their use as biomarkers for ICI response. In this article, we present an updated review regarding the use of lncRNA as biomarkers of response to ICI, highlighting the versatility of using these molecules.

Delineating intra-tumoral heterogeneity and tumor evolution in breast cancer using precision-based approaches

The burden of breast cancer continues to increase worldwide as it remains the most diagnosed tumor in females and the second leading cause of cancer-related deaths. Breast cancer is a heterogeneous disease characterized by different subtypes which are driven by aberrations in key genes such as BRCA1 and BRCA2, and hormone receptors. However, even within each subtype, heterogeneity that is driven by underlying evolutionary mechanisms is suggested to underlie poor response to therapy, variance in disease progression, recurrence, and relapse. Intratumoral heterogeneity highlights that the evolvability of tumor cells depends on interactions with cells of the tumor microenvironment. The complexity of the tumor microenvironment is being unraveled by recent advances in screening technologies such as high throughput sequencing; however, there remain challenges that impede the practical use of these approaches, considering the underlying biology of the tumor microenvironment and the impact of selective pressures on the evolvability of tumor cells. In this review, we will highlight the advances made thus far in defining the molecular heterogeneity in breast cancer and the implications thereof in diagnosis, the design and application of targeted therapies for improved clinical outcomes. We describe the different precision-based approaches to diagnosis and treatment and their prospects. We further propose that effective cancer diagnosis and treatment are dependent on unpacking the tumor microenvironment and its role in driving intratumoral heterogeneity. Underwriting such heterogeneity are Darwinian concepts of natural selection that we suggest need to be taken into account to ensure evolutionarily informed therapeutic decisions.

Artificial intelligence: opportunities and challenges in the clinical applications of triple-negative breast cancer

Triple-negative breast cancer (TNBC) accounts for 15-20% of all invasive breast cancer subtypes. Owing to its clinical characteristics, such as the lack of effective therapeutic targets, high invasiveness, and high recurrence rate, TNBC is difficult to treat and has a poor prognosis. Currently, with the accumulation of large amounts of medical data and the development of computing technology, artificial intelligence (AI), particularly machine learning, has been applied to various aspects of TNBC research, including early screening, diagnosis, identification of molecular subtypes, personalised treatment, and prediction of prognosis and treatment response. In this review, we discussed the general principles of artificial intelligence, summarised its main applications in the diagnosis and treatment of TNBC, and provided new ideas and theoretical basis for the clinical diagnosis and treatment of TNBC.

Integration of multiomics data shows down regulation of mismatch repair and tubulin pathways in triple-negative chemotherapy-resistant breast tumors

BACKGROUND

Triple-negative breast cancer (TNBC) is the most aggressive breast cancer subtype. Patients with TNBC are primarily treated with neoadjuvant chemotherapy (NAC). The response to NAC is prognostic, with reductions in overall survival and disease-free survival rates in those patients who do not achieve a pathological complete response (pCR). Based on this premise, we hypothesized that paired analysis of primary and residual TNBC tumors following NAC could identify unique biomarkers associated with post-NAC recurrence.

METHODS AND RESULTS

We investigated 24 samples from 12 non-LAR TNBC patients with paired pre- and post-NAC data, including four patients with recurrence shortly after surgery (< 24 months) and eight who remained recurrence-free (> 48 months). These tumors were collected from a prospective NAC breast cancer study (BEAUTY) conducted at the Mayo Clinic. Differential expression analysis of pre-NAC biopsies showed minimal gene expression differences between early recurrent and nonrecurrent TNBC tumors; however, post-NAC samples demonstrated significant alterations in expression patterns in response to intervention. Topological-level differences associated with early recurrence were implicated in 251 gene sets, and an independent assessment of microarray gene expression data from the 9 paired non-LAR samples available in the NAC I-SPY1 trial confirmed 56 gene sets. Within these 56 gene sets, 113 genes were observed to be differentially expressed in the I-SPY1 and BEAUTY post-NAC studies. An independent (n = 392) breast cancer dataset with relapse-free survival (RFS) data was used to refine our gene list to a 17-gene signature. A threefold cross-validation analysis of the gene signature with the combined BEAUTY and I-SPY1 data yielded an average AUC of 0.88 for six machine-learning models. Due to the limited number of studies with pre- and post-NAC TNBC tumor data, further validation of the signature is needed.

CONCLUSION

Analysis of multiomics data from post-NAC TNBC chemoresistant tumors showed down regulation of mismatch repair and tubulin pathways. Additionally, we identified a 17-gene signature in TNBC associated with post-NAC recurrence enriched with down-regulated immune genes.

Tertiary Lymphoid Structures (TLSs) and Stromal Blood Vessels Have Significant and Heterogeneous Impact on Recurrence, Lymphovascular and Perineural Invasion amongst Breast Cancer Molecular Subtypes

BACKGROUND

Tertiary lymphoid structures (TLSs) mediate local antitumor immunity, and interest in them significantly increased since cancer immunotherapy was implemented. We examined TLS- tumor stromal blood vessel interplay for each breast cancer (BC) molecular subtype related to recurrence, lymphovascular invasion (LVI), and perineural invasion (PnI).

METHODS

TLSs were quantified on hematoxylin and eosin stain specimens followed by CD34/smooth muscle actin (SMA) double immunostaining for stromal blood vessel maturation assessment. Statistical analysis linked microscopy to recurrence, LVI, and PnI.

RESULTS

TLS negative (TLS-) subgroups in each BC molecular subtype (except to Luminal A) have higher LVI, PnI, and recurrence. A significant rise in LVI and PnI were observed for the HER2+/TLS- subgroup (p < 0.001). The triple negative breast cancer (TNBC)/TLS- subgroup had the highest recurrence and invasion risk which was also significantly related to tumor grade. PnI but not LVI significantly influenced recurrence in the TNBC/TLS+ subgroup (p < 0.001). TLS-stromal blood vessel interrelation was different amongst BC molecular subtypes.

CONCLUSION

BC invasion and recurrence are strongly influenced by TLS presence and stromal blood vessels, especially for HER2 and TNBC BC molecular subtypes.

Understanding and modeling nerve-cancer interactions

The peripheral nervous system plays an important role in cancer progression. Studies in multiple cancer types have shown that higher intratumoral nerve density is associated with poor outcomes. Peripheral nerves have been shown to directly regulate tumor cell properties, such as growth and metastasis, as well as affect the local environment by modulating angiogenesis and the immune system. In this Review, we discuss the identity of nerves in organs in the periphery where solid tumors grow, the known mechanisms by which nerve density increases in tumors, and the effects these nerves have on cancer progression. We also discuss the strengths and weaknesses of current in vitro and in vivo models used to study nerve-cancer interactions. Increased understanding of the mechanisms by which nerves impact tumor progression and the development of new approaches to study nerve-cancer interactions will facilitate the discovery of novel treatment strategies to treat cancer by targeting nerves.

Identification of a minimum number of genes to predict triple-negative breast cancer subgroups from gene expression profiles

BACKGROUND

Triple-negative breast cancer (TNBC) is a very heterogeneous disease. Several gene expression and mutation profiling approaches were used to classify it, and all converged to the identification of distinct molecular subtypes, with some overlapping across different approaches. However, a standardised tool to routinely classify TNBC in the clinics and guide personalised treatment is lacking. We aimed at defining a specific gene signature for each of the six TNBC subtypes proposed by Lehman et al. in 2011 (basal-like 1 (BL1); basal-like 2 (BL2); mesenchymal (M); immunomodulatory (IM); mesenchymal stem-like (MSL); and luminal androgen receptor (LAR)), to be able to accurately predict them.

METHODS

Lehman's TNBCtype subtyping tool was applied to RNA-sequencing data from 482 TNBC (GSE164458), and a minimal subtype-specific gene signature was defined by combining two class comparison techniques with seven attribute selection methods. Several machine learning algorithms for subtype prediction were used, and the best classifier was applied on microarray data from 72 Italian TNBC and on the TNBC subset of the BRCA-TCGA data set.

RESULTS

We identified two signatures with the 120 and 81 top up- and downregulated genes that define the six TNBC subtypes, with prediction accuracy ranging from 88.6 to 89.4%, and even improving after removal of the least important genes. Network analysis was used to identify highly interconnected genes within each subgroup. Two druggable matrix metalloproteinases were found in the BL1 and BL2 subsets, and several druggable targets were complementary to androgen receptor or aromatase in the LAR subset. Several secondary drug-target interactions were found among the upregulated genes in the M, IM and MSL subsets.

CONCLUSIONS

Our study took full advantage of available TNBC data sets to stratify samples and genes into distinct subtypes, according to gene expression profiles. The development of a data mining approach to acquire a large amount of information from several data sets has allowed us to identify a well-determined minimal number of genes that may help in the recognition of TNBC subtypes. These genes, most of which have been previously found to be associated with breast cancer, have the potential to become novel diagnostic markers and/or therapeutic targets for specific TNBC subsets.

The Revelation of Continuously Organized, Co-Overexpressed Protein-Coding Genes with Roles in Cellular Communications in Breast Cancer

Many human cancers, including breast cancer, are polygenic and involve the co-dysregulation of multiple regulatory molecules and pathways. Though the overexpression of genes and amplified chromosomal regions have been closely linked in breast cancer, the notion of the co-upregulation of genes at a single locus remains poorly described. Here, we describe the co-overexpression of 34 continuously organized protein-coding genes with diverse functions at 8q.24.3(143437655-144326919) in breast and other cancer types, the CanCord34 genes. In total, 10 out of 34 genes have not been reported to be overexpressed in breast cancer. Interestingly, the overexpression of CanCord34 genes is not necessarily associated with genomic amplification and is independent of hormonal or HER2 status in breast cancer. CanCord34 genes exhibit diverse known and predicted functions, including enzymatic activities, cell viability, multipotency, cancer stem cells, and secretory activities, including extracellular vesicles. The co-overexpression of 33 of the CanCord34 genes in a multivariant analysis was correlated with poor survival among patients with breast cancer. The analysis of the genome-wide RNAi functional screening, cell dependency fitness, and breast cancer stem cell databases indicated that three diverse overexpressed CanCord34 genes, including a component of spliceosome PUF60, a component of exosome complex EXOSC4, and a ribosomal biogenesis factor BOP1, shared roles in cell viability, cell fitness, and stem cell phenotypes. In addition, 17 of the CanCord34 genes were found in the microvesicles (MVs) secreted from the mesenchymal stem cells that were primed with MDA-MB-231 breast cancer cells. Since these MVs were important in the chemoresistance and dedifferentiation of breast cancer cells into cancer stem cells, these findings highlight the significance of the CanCord34 genes in cellular communications. In brief, the persistent co-overexpression of CanCord34 genes with diverse functions can lead to the dysregulation of complementary functions in breast cancer. In brief, the present study provides new insights into the polygenic nature of breast cancer and opens new research avenues for basic, preclinical, and therapeutic studies in human cancer.

The Monocyte, a Maestro in the Tumor Microenvironment (TME) of Breast Cancer

Breast cancer (BC) is well-known for being a leading cause of death worldwide. It is classified molecularly into luminal A, luminal B HER2-, luminal B HER2+, HER2+, and triple-negative breast cancer (TNBC). These subtypes differ in their prognosis; thus, understanding the tumor microenvironment (TME) makes new treatment strategies possible. The TME contains populations that exhibit anti-tumorigenic actions such as tumor-associated eosinophils. Moreover, it contains pro-tumorigenic populations such as tumor-associated neutrophils (TANs), or monocyte-derived populations. The monocyte-derived populations are tumor-associated macrophages (TAMs) and MDSCs. Thus, a monocyte can be considered a maestro within the TME. Moreover, the expansion of monocytes in the TME depends on many factors such as the BC stage, the presence of macrophage colony-stimulating factor (M-CSF), and the presence of some chemoattractants. After expansion, monocytes can differentiate into pro-inflammatory populations such as M1 macrophages or anti-inflammatory populations such as M2 macrophages according to the nature of cytokines present in the TME. Differentiation to TAMs depends on various factors such as the BC subtype, the presence of anti-inflammatory cytokines, and epigenetic factors. Furthermore, TAMs and MDSCs not only have a role in tumor progression but also are key players in metastasis. Thus, understanding the monocytes further can introduce new target therapies.

Sensory nerves enhance triple-negative breast cancer invasion and metastasis via the axon guidance molecule PlexinB3

In breast cancer, nerve presence has been correlated with more invasive disease and worse prognosis, yet the mechanisms by which different types of peripheral nerves drive tumor progression remain poorly understood. In this study, we identified sensory nerves as more abundant in human triple-negative breast cancer (TNBC) tumors. Co-injection of sensory neurons isolated from the dorsal root ganglia (DRG) of adult female mice with human TNBC cells in immunocompromised mice increased the number of lung metastases. Direct in vitro co-culture of human TNBC cells with the dorsal root ganglia (DRG) of adult female mice revealed that TNBC cells adhere to sensory neuron fibers leading to an increase in migration speed. Species-specific RNA sequencing revealed that co-culture of TNBC cells with sensory nerves upregulates the expression of genes associated with cell migration and adhesion in cancer cells. We demonstrated that lack of the semaphorin receptor PlexinB3 in cancer cells attenuate their adhesion to and migration on sensory nerves. Together, our results identify a mechanism by which nerves contribute to breast cancer migration and metastasis by inducing a shift in TNBC cell gene expression and support the rationale for disrupting neuron-cancer cell interactions to target metastasis.

Nanobiotherapeutic strategies to target immune microenvironment of triple-negative breast cancer

Triple-negative breast cancer (TNBC) is the subtype with the least favourable outcomes in breast cancer. Besides chemotherapy, there is a chronic lack of other effective treatments. Advances in omic technologies have liberated us from the ambiguity of TNBC heterogeneity in terms of cancer cell and immune microenvironment in recent years. This new understanding of TNBC pathology has already led to the exploitation of novel nanoparticulate systems, including tumor vaccines, oncolytic viruses, and antibody derivatives. The revolutionary ideas in the therapeutic landscape provide new opportunities for TNBC patients. Translating these experimental medicines into clinical benefit is both appreciated and challenging. In this review, we describe the prospective nanobiotherapy of TNBC that has been developed to overcome clinical obstacles, and provide our vision for this booming field at the overlap of cancer biotherapy and nanomaterial design.

The Role of Neural Signaling in the Pancreatic Cancer Microenvironment

Simple Summary

Pancreatic cancer is a highly lethal malignant disease with a dense stroma, called the tumor microenvironment. Accumulating evidence indicates the important role of sympathetic, parasympathetic, and sensory nerves in the tumor microenvironment of various cancers, including pancreatic cancer. Cancer cells and neural cells interact with each other to form a complex network and cooperatively promote cancer growth and invasion. In this review article, we describe the current understanding of the role of nerves in the tumor microenvironment.

Abstract

Pancreatic cancer is one of the most lethal malignant diseases. Various cells in the tumor microenvironment interact with tumor cells and orchestrate to support tumor progression. Several kinds of nerves are found in the tumor microenvironment, and each plays an essential role in tumor biology. Recent studies have shown that sympathetic, parasympathetic, and sensory neurons are found in the pancreatic cancer microenvironment. Neural signaling not only targets neural cells, but tumor cells and immune cells via neural receptors expressed on these cells, through which tumor growth, inflammation, and anti-tumor immunity are affected. Thus, these broad-range effects of neural signaling in the pancreatic cancer microenvironment may represent novel therapeutic targets. The modulation of neural signaling may be a therapeutic strategy targeting the whole tumor microenvironment. In this review, we describe the current understanding of the role of nerves in the tumor microenvironment of various cancers, with an emphasis on pancreatic cancer. We also discuss the underlying mechanisms and the possibility of therapeutic applications.

Oncogenic signaling pathway-related long non-coding RNAs for predicting prognosis and immunotherapy response in breast cancer

Background

The clinical outcomes of breast cancer (BC) are unpredictable due to the high level of heterogeneity and complex immune status of the tumor microenvironment (TME). When set up, multiple long non-coding RNA (lncRNA) signatures tended to be employed to appraise the prognosis of BC. Nevertheless, predicting immunotherapy responses in BC is still essential. LncRNAs play pivotal roles in cancer development through diverse oncogenic signal pathways. Hence, we attempted to construct an oncogenic signal pathway–based lncRNA signature for forecasting prognosis and immunotherapy response by providing reliable signatures.

Methods

We preliminarily retrieved RNA sequencing (RNA-seq) data from The Cancer Genome Atlas (TCGA) database and extracted lncRNA profiles by matching them with GENCODE. Following this, Gene Set Variation Analysis (GSVA) was used to identify the lncRNAs closely associated with 10 oncogenic signaling pathways from the TCGA-BRCA (breast-invasive carcinoma) cohort and was further screened by the least absolute shrinkage and selection operator Cox regression model. Next, an lncRNA signature (OncoSig) was established through the expression level of the final 29 selected lncRNAs. To examine survival differences in the stratification described by the OncoSig, the Kaplan–Meier (KM) survival curve with the log-rank test was operated on four independent cohorts (n = 936). Subsequently, multiple Cox regression was used to investigate the independence of the OncoSig as a prognostic factor. With the concordance index (C-index), the time-dependent receiver operating characteristic was employed to assess the performance of the OncoSig compared to other publicly available lncRNA signatures for BC. In addition, biological differences between the high- and low-risk groups, as portrayed by the OncoSig, were analyzed on the basis of statistical tests. Immune cell infiltration was investigated using gene set enrichment analysis (GSEA) and deconvolution tools (including CIBERSORT and ESTIMATE). The combined effect of the Oncosig and immune checkpoint genes on prognosis and immunotherapy was elucidated through the KM survival curve. Ultimately, a pan-cancer analysis was conducted to attest to the prevalence of the OncoSig.

Results

The OncoSig score stratified BC patients into high- and low-risk groups, where the latter manifested a significantly higher survival rate and immune cell infiltration when compared to the former. A multivariate analysis suggested that OncoSig is an independent prognosis predictor for BC patients. In addition, compared to the other four publicly available lncRNA signatures, OncoSig exhibited superior predictive performance (AUC = 0.787, mean C-index = 0.714). The analyses of the OncoSig and immune checkpoint genes clarified that a lower OncoSig score meant significantly longer survival and improved response to immunotherapy. In addition to BC, a high OncoSig score in several other cancers was negatively correlated with survival and immune cell infiltration.

Conclusions

Our study established a trustworthy and discriminable prognostic signature for BC patients with similar clinical profiles, thus providing a new perspective in the evaluation of immunotherapy responses. More importantly, this finding can be generalized to be applicable to the vast majority of human cancers.

Brain Neural Progenitors are New Predictive Biomarkers for Breast Cancer Hormonotherapy

Heterogeneity of the tumor microenvironment (TME) is one of the major causes of treatment resistance in breast cancer. Among TME components, nervous system role in clinical outcome has been underestimated. Identifying neuronal signatures associated with treatment response will help to characterize neuronal influence on tumor progression and identify new treatment targets. The search for hormonotherapy-predictive biomarkers was implemented by supervised machine learning (ML) analysis on merged transcriptomics datasets from public databases. ML-derived genes were investigated by pathway enrichment analysis, and potential gene signatures were curated by removing the variables that were not strictly nervous system specific. The predictive and prognostic abilities of the generated signatures were examined by Cox models, in the initial cohort and seven external cohorts. Generated signature performances were compared with 14 other published signatures, in both the initial and external cohorts. Underlying biological mechanisms were explored using deconvolution tools (CIBERSORTx and xCell). Our pipeline generated two nervous system-related signatures of 24 genes and 97 genes (NervSign24 and NervSign97). These signatures were prognostic and hormonotherapy-predictive, but not chemotherapy-predictive. When comparing their predictive performance with 14 published risk signatures in six hormonotherapy-treated cohorts, NervSign97 and NervSign24 were the two best performers. Pathway enrichment score and deconvolution analysis identified brain neural progenitor presence and perineural invasion as nervous system-related mechanisms positively associated with NervSign97 and poor clinical prognosis in hormonotherapy-treated patients. Transcriptomic profiling has identified two nervous system-related signatures that were validated in clinical samples as hormonotherapy-predictive signatures, meriting further exploration of neuronal component involvement in tumor progression.

Significance

The development of personalized and precision medicine is the future of cancer therapy. With only two gene expression signatures approved by FDA for breast cancer, we are in need of new ones that can reliably stratify patients for optimal treatment. This study provides two hormonotherapy-predictive and prognostic signatures that are related to nervous system in TME. It highlights tumor neuronal components as potential new targets for breast cancer therapy.

High PANX1 Expression Leads to Neutrophil Recruitment and the Formation of a High Adenosine Immunosuppressive Tumor Microenvironment in Basal-like Breast Cancer

Background: A high adenosine level is an important characteristic of the tumor microenvironment (TME) in breast cancer. Pannexin 1 (PANX1) can release intracellular ATP to the extracellular space and elevate extracellular ATP (exATP) levels under physiological conditions. Methods: We performed public database bioinformatics analysis, surgical specimen histological validation, RNA sequencing, and exATP/extracellular adenosine (exADO) assays to reveal the role of PANX1 in regulating the immune microenvironment of basal-like breast cancer. Results: Our results revealed that PANX1 acted as a poor prognostic factor for breast cancer and had high expression in basal-like breast cancer. PANX1 expression was positively correlated with exATP and exADO levels in basal-like breast cancer TME. PANX1 expression was also positively correlated with tumor-associated neutrophil (TAN) infiltration in breast cancer TME and TANs highly expressed ENTPD1 (CD39)/NT5E (CD73). Conclusions: This study suggests that high PANX1 expression is associated with high TAN infiltration and adenosine production to induce local immunosuppression in basal-like breast cancer TME.

Signaling Pathways and Natural Compounds in Triple-Negative Breast Cancer Cell Line

Triple-negative breast cancer (TNBC) is the most aggressive subtype of breast cancer, having a poor prognosis and rapid metastases. TNBC is characterized by the absence of estrogen, progesterone, and human epidermal growth receptor-2 (HER2) expressions and has a five-year survival rate. Compared to other breast cancer subtypes, TNBC patients only respond to conventional chemotherapies, and even then, with limited success. Shortages of chemotherapeutic medication can lead to resistance, pressured index therapy, non-selectivity, and severe adverse effects. Finding targeted treatments for TNBC is difficult owing to the various features of cancer. Hence, identifying the most effective molecular targets in TNBC pathogenesis is essential for predicting response to targeted therapies and preventing TNBC cell metastases. Nowadays, natural compounds have gained attention as TNBC treatments, and have offered new strategies for solving drug resistance. Here, we report a systematic review using the database from Pubmed, Science Direct, MDPI, BioScince, Springer, and Nature for articles screening from 2003 to 2022. This review analyzes relevant signaling pathways and the prospect of utilizing natural compounds as a therapeutic agent to improve TNBC treatments in the future.

Luminal androgen receptor breast cancer subtype and investigation of the microenvironment and neoadjuvant chemotherapy response

Triple-negative breast cancer (TNBC) is the most aggressive breast cancer subtype with low overall survival rates and high molecular heterogeneity; therefore, few targeted therapies are available. The luminal androgen receptor (LAR) is the most consistently identified TNBC subtype, but the clinical utility has yet to be established. Here, we constructed a novel genomic classifier, LAR-Sig, that distinguishes the LAR subtype from other TNBC subtypes and provide evidence that it is a clinically distinct disease. A meta-analysis of seven TNBC datasets (n = 1086 samples) from neoadjuvant clinical trials demonstrated that LAR patients have significantly reduced response (pCR) rates than non-LAR TNBC patients (odds ratio = 2.11, 95% CI: 1.33, 2.89). Moreover, deconvolution of the tumor microenvironment confirmed an enrichment of luminal epithelium corresponding with a decrease in basal and myoepithelium in LAR TNBC tumors. Increased immunosuppression in LAR patients may lead to a decreased presence of cycling T-cells and plasma cells. While, an increased presence of myofibroblast-like cancer-associated cells may impede drug delivery and treatment. In summary, the lower levels of tumor infiltrating lymphocytes (TILs), reduced immune activity in the micro-environment, and lower pCR rates after NAC, suggest that new therapeutic strategies for the LAR TNBC subtype need to be developed.

Reassessment of Reliability and Reproducibility for Triple-Negative Breast Cancer Subtyping

Simple Summary

Triple-negative breast cancer (TNBC) is a heterogeneous disease. A proper classification system is needed to develop targetable biomarkers and guide personalized treatment in clinical practice. However, there has been no consensus on the molecular subtypes of TNBC, probably due to discrepancies in technical and computational methods chosen by different research groups. In this paper, we reassessed each major step for TNBC subtyping and provided suggestions, which promote rational workflow design and ensure reliable and reproducible results for future studies. We presented a recommended pipeline to the existing data, validated established TNBC subtypes with a larger sample size, and revealed two intermediate subtypes with prognostic significance. This work provides perspectives on issues and limitations regarding TNBC subtyping, indicating promising directions for developing targeted therapy based on the molecular characteristics of each TNBC subtype.

Abstract

Triple-negative breast cancer (TNBC) is a heterogeneous disease with diverse, often poor prognoses and treatment responses. In order to identify targetable biomarkers and guide personalized care, scientists have developed multiple molecular classification systems for TNBC based on transcriptomic profiling. However, there is no consensus on the molecular subtypes of TNBC, likely due to discrepancies in technical and computational methods used by different research groups. Here, we reassessed the major steps for TNBC subtyping, validated the reproducibility of established TNBC subtypes, and identified two more subtypes with a larger sample size. By comparing results from different workflows, we demonstrated the limitations of formalin-fixed, paraffin-embedded samples, as well as batch effect removal across microarray platforms. We also refined the usage of computational tools for TNBC subtyping. Furthermore, we integrated high-quality multi-institutional TNBC datasets (discovery set: n = 457; validation set: n = 165). Performing unsupervised clustering on the discovery and validation sets independently, we validated four previously discovered subtypes: luminal androgen receptor, mesenchymal, immunomodulatory, and basal-like immunosuppressed. Additionally, we identified two potential intermediate states of TNBC tumors based on their resemblance with more than one well-characterized subtype. In summary, we addressed the issues and limitations of previous TNBC subtyping through comprehensive analyses. Our results promote the rational design of future subtyping studies and provide new insights into TNBC patient stratification.

Impact of HER2 Status on Pathological Response after Neoadjuvant Chemotherapy in Early Triple-Negative Breast Cancer

PURPOSE

Investigates the link between HER2 status and histological response after neoadjuvant chemotherapy in patients with early TNBC.

METHODS

We retrieved clinical and anatomopathological data retrospectively from 449 patients treated for the first time with standard neoadjuvant chemotherapy for early unilateral BC between 2005 and 2020. The primary endpoint was pathological complete response (pCR, i.e., ypT0 ypN0), according to HER2 status. Secondary endpoints included invasive disease-free survival (I-DFS) and overall survival (OS).

RESULTS

437 patients were included, and 121 (27.7%) patients had HER2-low tumours. The pCR rate was not significantly different between the HER2-low group vs. the HER2-0 group (35.7% versus 41.8%, p = 0.284) in either univariate analysis or multivariate analysis adjusted for TNM classification and grade (odds ratio [OR] = 0.70, confidence interval [CI] 95% 0.45-1.08). With a median follow-up of 72.9 months, no significant survival differences were observed between patients with HER2-low tumours vs. patients with HER2-0 tumours in terms of I-DFS (p = 0.487) and OS (p = 0.329).

CONCLUSIONS

In our cohort, HER2 status was not significantly associated with pCR in a manner consistent with data published recently on TNBC. However, the prognostic impact of HER2-low expression among TNBC patients warrants further evaluation.

Inhibition of triple negative breast cancer-associated inflammation, tumor growth and brain colonization by targeting monoacylglycerol lipase

While the prevalence of breast cancer metastasis in the brain is significantly higher in triple negative breast cancers (TNBCs), there is a lack of novel and/or improved therapies for these patients. Monoacylglycerol lipase (MAGL) is a hydrolase involved in lipid metabolism that catalyzes the degradation of 2-arachidonoylglycerol (2-AG) linked to generation of pro- and anti-inflammatory molecules. Here, we targeted MAGL in TNBCs, using a potent carbamate-based inhibitor AM9928 (hMAGL IC₅₀ = 9 nM) with prolonged pharmacodynamic effects (46 h of target residence time). AM9928 blocked TNBC cell adhesion and transmigration across human brain microvascular endothelial cells (HBMECs) in 3D co-cultures. In addition, AM9928 inhibited the secretion of IL-6, IL-8, and VEGF-A from TNBC cells. TNBC-derived exosomes activated HBMECs resulting in secretion of elevated levels of IL-8 and VEGF, which were inhibited by AM9928. Using in vivo studies of syngeneic GFP-4T1-BrM5 mammary tumor cells, AM9928 inhibited tumor growth in the mammary fat pads and attenuated blood brain barrier (BBB) permeability changes, resulting in reduced TNBC colonization in brain. Together, these results support the potential clinical application of MAGL inhibitors as novel treatments for TNBC.

PTPN2 elicits cell autonomous and non-cell autonomous effects on antitumor immunity in triple-negative breast cancer

The tumor-suppressor PTPN2 is diminished in a subset of triple-negative breast cancers (TNBCs). Paradoxically, PTPN2-deficiency in tumors or T cells in mice can facilitate T cell recruitment and/or activation to promote antitumor immunity. Here, we explored the therapeutic potential of targeting PTPN2 in tumor cells and T cells. PTPN2-deficiency in TNBC associated with T cell infiltrates and PD-L1 expression, whereas low PTPN2 associated with improved survival. PTPN2 deletion in murine mammary epithelial cells TNBC models, did not promote tumorigenicity but increased STAT-1-dependent T cell recruitment and PD-L1 expression to repress tumor growth and enhance the efficacy of anti-PD-1. Furthermore, the combined deletion of PTPN2 in tumors and T cells facilitated T cell recruitment and activation and further repressed tumor growth or ablated tumors already predominated by exhausted T cells. Thus, PTPN2-targeting in tumors and/or T cells facilitates T cell recruitment and/or alleviates inhibitory constraints on T cells to combat TNBC.

Prognostic Value of Metabolic, Volumetric and Textural Parameters of Baseline [18F]FDG PET/CT in Early Triple-Negative Breast Cancer

Simple Summary

The aim of this study was to evaluate PET/CT parameters to determine different prognostic groups in TNBC, in order to select patients with a high risk of relapse, for whom therapeutic escalation can be considered. We have demonstrated that the MTV, TLG and entropy of the primary breast lesion could be of interest to predict the prognostic outcome of TNBC patients.

Abstract

(1) Background: triple-negative breast cancer (TNBC) remains a clinical and therapeutic challenge primarily affecting young women with poor prognosis. TNBC is currently treated as a single entity but presents a very diverse profile in terms of prognosis and response to treatment. Positron emission tomography/computed tomography (PET/CT) with ¹⁸F-fluorodeoxyglucose ([¹⁸F]FDG) is gaining importance for the staging of breast cancers. TNBCs often show high [¹⁸F]FDG uptake and some studies have suggested a prognostic value for metabolic and volumetric parameters, but no study to our knowledge has examined textural features in TNBC. The objective of this study was to evaluate the association between metabolic, volumetric and textural parameters measured at the initial [¹⁸F]FDG PET/CT and disease-free survival (DFS) and overall survival (OS) in patients with nonmetastatic TBNC. (2) Methods: all consecutive nonmetastatic TNBC patients who underwent a [¹⁸F]FDG PET/CT examination upon diagnosis between 2012 and 2018 were retrospectively included. The metabolic and volumetric parameters (SUV_max, SUV_mean, SUV_peak, MTV, and TLG) and the textural features (entropy, homogeneity, SRE, LRE, LGZE, and HGZE) of the primary tumor were collected. (3) Results: 111 patients were enrolled (median follow-up: 53.6 months). In the univariate analysis, high TLG, MTV and entropy values of the primary tumor were associated with lower DFS (p = 0.008, p = 0.006 and p = 0.025, respectively) and lower OS (p = 0.002, p = 0.001 and p = 0.046, respectively). The discriminating thresholds for two-year DFS were calculated as 7.5 for MTV, 55.8 for TLG and 2.6 for entropy. The discriminating thresholds for two-year OS were calculated as 9.3 for MTV, 57.4 for TLG and 2.67 for entropy. In the multivariate analysis, lymph node involvement in PET/CT was associated with lower DFS (p = 0.036), and the high MTV of the primary tumor was correlated with lower OS (p = 0.014). (4) Conclusions: textural features associated with metabolic and volumetric parameters of baseline [¹⁸F]FDG PET/CT have a prognostic value for identifying high-relapse-risk groups in early TNBC patients.

Tertiary lymphoid structures in cancer

Ectopic lymphoid aggregates, termed tertiary lymphoid structures (TLSs), are formed in numerous cancer types, and, with few exceptions, their presence is associated with superior prognosis and response to immunotherapy. In spite of their presumed importance, the triggers that lead to TLS formation in cancer tissue and the contribution of these structures to intratumoral immune responses remain incompletely understood. Here, we discuss the present knowledge on TLSs in cancer, focusing on (i) the drivers of TLS formation, (ii) the function and contribution of TLSs to the antitumor immune response, and (iii) the potential of TLSs as therapeutic targets in human cancers.

Curcuma zedoaria petroleum ether extract reverses the resistance of triple-negative breast cancer to docetaxel via pregnane X receptor

Background

Triple-negative breast cancer (TNBC) is characterized by its aggressiveness and poor prognosis. Docetaxel is the common chemotherapeutic drug used in the treatment of TNBC. However, resistance to docetaxel has limited the effectiveness of TNBC treatment. Petroleum ether extracts of Curcuma zedoaria (PECZ) can inhibit the proliferation of MDA-MB-231 cells. However, the effect of PECZ on docetaxel resistance is not clear.

Methods

A docetaxel-resistant MDA-MB-231 (MDA-MB-231/docetaxel) cell line was established, and Cell Counting Kit-8 (CCK-8), quantitative real-time PCR (qRT-PCR), and western blotting assays were used to evaluate the effect of docetaxel resistance in MDA-MB-231 cells. Next, CCK-8 was also performed to detect the effect of docetaxel or the combination treatment of docetaxel and PECZ on the proliferation of MDA-MB-231/docetaxel cells. Thereafter, MDA-MB-231/docetaxel cells were subcutaneously injected into nude mice to induce a TNBC xenograft model, and the mice were divided into a model group, docetaxel group, PECZ group, and combination of docetaxel and PECZ group. Subsequently, hematoxylin and eosin (HE) staining, immunohistochemical, qRT-PCR, and western blotting were used to estimate the effect of pre-treatment with PECZ on docetaxel tolerance reversal.

Results

PECZ significantly inhibited the expression of pregnane X receptor (PXR), multidrug resistance 1 (MDR1), breast cancer resistance protein (BCRP), and cytochrome P-450 (CYP3A4) in MDA-MB-231/docetaxel cells. Only higher concentrations of docetaxel could inhibit the viability of MDA-MB-231/docetaxel cells. When pre-treated with PECZ, lower concentrations of docetaxel could significantly inhibit cell viability. Meanwhile, combination treatment also reduced the tumor volume, ameliorated the pathological change of tumor tissues, and down-regulated the expressions of PXR, MDR1, BCRP, and CYP3A4 (according to HE staining, immunohistochemical, qRT-PCR and western blotting results in vivo).

Conclusions

Our research showed that PECZ reversed docetaxel resistance in TNBC by PXR both in vitro and in vivo, which provides the basis for further investigations into the potential therapeutic impact of docetaxel resistance in TNBC.

Tertiary lymphoid structure and B-cell-related pathways: A potential target in tumor immunotherapy

The tertiary lymphoid structure (TLS), also referred to as the ectopic lymphoid structure, has recently become a focus of attention. The TLS consists of T-cell and B-cell-rich regions, as well as plasma cells, follicular helper T cells, follicular dendritic cells (FDCs), germinal centers (GCs) and high endothelial venules. TLSs can be divided into different subtypes and mature stages according to the density of FDCs and GCs. The TLS serves as an effective site in which an antitumor inflammatory response is generated through infiltrating immune cells. B-cell-related pathways, known as the CXC chemokine ligand 13/CXC chemokine receptor type 5 axis and the CC chemokine ligand (CCL)19/CCL21/CC-chemokine receptor 7 axis, play a key role in the generation and formation of TLSs. The aim of the present review was to systematically summarize updated research progress on the formation, subtypes, evaluation and B-cell-related pathways of TLSs. Furthermore, researchers have previously reported that TLSs are present in several types of solid cancers and that they are associated with survival outcomes. Therefore, studies on TLS in breast, lung, colorectal and ovarian cancers and melanoma were summarized and compared. The TLS and B-cell-related pathways require further investigation as important immune signals and promising new immunotherapy targets in the era of T-cell therapy revolution.

Impact of Epithelial-Mesenchymal Transition on the Immune Landscape in Breast Cancer

The impact of epithelial-mesenchymal transition (EMT) signature on the immune infiltrate present in the breast cancer tumor microenvironment (TME) is still poorly understood. Since there is mounting interest in the use of immunotherapy for the treatment of subsets of breast cancer patients, it is of major importance to understand the fundamental tumor characteristics which dictate the inter-tumor heterogeneity in immune landscapes. We aimed to assess the impact of EMT-related markers on the nature and magnitude of the inflammatory infiltrate present in breast cancer TME and their association with the clinicopathological parameters. Tissue microarrays were constructed from 144 formalin-fixed paraffin-embedded invasive breast cancer tumor samples. The protein expression patterns of Snail, Twist, ZEB1, N-cadherin, Vimentin, GRHL2, E-cadherin, and EpCAM were examined by immunohistochemistry (IHC). The inflammatory infiltrate in the TME was assessed semi-quantitatively on hematoxylin and eosin (H&E)-stained whole sections and was characterized using IHC. The inflammatory infiltrate was more intense in poorly differentiated carcinomas and triple-negative carcinomas in which the expression of E-cadherin and GRHL2 was reduced, while EpCAM was overexpressed. Most EMT-related markers correlated with plasma cell infiltration of the TME. Taken together, our findings reveal that the EMT signature might impact the immune response in the TME.

Molecular Targets and Promising Therapeutics of Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) is one of the most heterogeneous diseases in solid tumors and has limited therapeutic options. Due to the lack of appropriate targetable markers, the mainstay therapeutic strategy for patients with TNBC has been chemotherapy for the last several decades. Indeed, TNBC tumors have no expression of estrogen receptor, progesterone receptor, or human epidermal growth factor receptor 2 (HER2); therefore, they do not respond to hormone therapy and HER2-targeted therapy. In this review paper, the molecular heterogeneities, possible therapeutic targets, and recently approved and upcoming drugs for TNBC will be summarized.

[Interest of the bc-GenExMiner web tool in oncology]

We are taking advantage of the launch of the latest version (v4.6) of our web-based data mining tool "breast cancer gene-expression miner" (bc-GenExMiner) to take stock of its position within the oncology research landscape and to present an activity report ten years after its establishment (http://bcgenex.ico.unicancer.fr). bc-GenExMiner is an open-access, user-friendly tool for statistical mining on breast tumor transcriptomes, annotated with more than 20 clinicopathologic and molecular characteristics. The database comprises more than 16,000 patients from 64 cohorts - including TCGA, METABRIC and SCAN-B - for whom several thousands of genes have been quantified by microarrays or RNA-seq. Correlation, expression and prognostic analyses are available for targeted, exhaustive or customized explorations of queried genes. bc-GenExMiner facilitates the validation, investigation, and prioritization of discoveries and hypotheses on genes of interest. It allows users to analyse large databases, create data visualizations, and obtain robust statistical analysis, thereby accelerating biomarker discovery. Ten years after its launch, judging by the number of visits, analyses, and scientific citations of bc-GenExMiner, we conclude that this web resource serves its purpose in the international scientific community working in breast cancer research, with a never-ending rise in its use.