Breast Cancer Immunotherapy: Facts and Hopes

Identifying tumour microenvironment-related signature that correlates with prognosis and immunotherapy response in breast cancer

Tumor microenvironment (TME) plays important roles in prognosis and immune evasion. However, the relationship between TME-related genes and clinical prognosis, immune cell infiltration, and immunotherapy response in breast cancer (BRCA) remains unclear. This study described the TME pattern to construct a TME-related prognosis signature, including risk factors PXDNL, LINC02038 and protective factors SLC27A2, KLRB1, IGHV1-12 and IGKV1OR2-108, as an independent prognostic factor for BRCA. We found that the prognosis signature was negatively correlated with the survival time of BRCA patients, infiltration of immune cells and the expression of immune checkpoints, while positively correlated with tumor mutation burden and adverse treatment effects of immunotherapy. Upregulation of PXDNL and LINC02038 and downregulation of SLC27A2, KLRB1, IGHV1-12 and IGKV1OR2-108 in high-risk score group synergistically contribute to immunosuppressive microenvironment which characterized by immunosuppressive neutrophils, impaired cytotoxic T lymphocytes migration and natural killer cell cytotoxicity. In summary, we identified a TME-related prognostic signature in BRCA, which was connected with immune cell infiltration, immune checkpoints, immunotherapy response and could be developed for immunotherapy targets.

Tumor Microenvironment Responsive Nanomicelle with Folic Acid Modification Co-Delivery of Doxorubicin/Shikonin for Triple Negative Breast Cancer Treatment

Triple negative breast cancer (TNBC), which has poor prognosis, easily develops drug resistance and metastasizes. In general, those TNBC characteristics are related to a high activation of the epithelial-mesenchymal transition (EMT) pathway, which is inhibited by shikonin (SKN). Therefore, the synergistic therapy of SKN and doxorubicin (DOX) will increase anti-tumor efficacy and reduce metastasis. In this study, we prepared the folic acid-linked PEG nanomicelle (NM) grafted with the DOX (denoted as FPD) to load the SKN. We prepared the SKN@FPD NM according to the effective ratio of dual drugs, where the drug loadings of DOX and SKN were 8.86 ± 0.21% and 9.43 ± 0.13%, with 121.8 ± 1.1 nm of its hydrodynamic dimension and 6.33 ± 0.16 mV of zeta potential, respectively. The nanomaterials significantly slowed down the release of DOX and SKN over 48 h, leading to the release of pH-responsive drugs. Meanwhile, the prepared NM inhibited the activity of MBA-MD-231 cells in vitro. Further in vitro study revealed that the SKN@FPD NM increased the DOX uptake and significantly reduced the metastasis of MBA-MD-231 cells. Overall, these active-targeting NMs improved the tumor-targeting of small molecular drugs and effectively treated TNBC.

Roles of circular RNAs in regulating the development of glioma

BACKGROUND

Glioma is the most common malignant tumor in the central nervous system. In patients with glioma, the prognosis is poor and median survival is only 12-15 months. With the recent development of sequencing technology, important roles of noncoding RNAs are being discovered in cells, especially those of circular RNAs (circRNAs). Because circRNAs are stable, abundant, and highly conserved, they are regarded as novel biomarkers in the early diagnosis and prognosis of diseases.

PURPOSE

In this review, roles and mechanisms of circRNAs in the development of glioma are summarized.

METHODS

This paper collects and reviews relevant PubMed literature.

CONCLUSION

Several classes of circRNAs are highly expressed in glioma and are associated with malignant biological behaviors of gliomas, including proliferation, migration, invasion, apoptosis, angiogenesis, and drug resistance. Further studies are needed to clarify the roles of circRNAs in glioma and to determine whether it is possible to increase therapeutic effects on tumors through circRNA intervention.

CRISPR/Cas genome editing in triple negative breast cancer: Current situation and future directions

Triple negative breast cancer (TNBC) has been well-known to be closely associated with the abnormal expression of both oncogenes and tumor suppressors. Although several pathogenic mutations in TNBC have been identified, the current therapeutic strategy is usually aimed at symptom relief rather than correcting mutations in the DNA sequence. Of note, clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein (Cas) has been gradually regarded as a breakthrough gene-editing tool with potential therapeutic applications in human cancers, including TNBC. Thus, in this review, we focus on summarizing the molecular subtypes of TNBC, as well as the CRISPR system and its potential applications in TNBC treatment. Moreover, we further discuss several emerging strategies for utilizing the CRISPR/Cas system to aid in the precise diagnosis of TNBC, as well as the limitations of the CRISPR/Cas system. Taken together, these findings would demonstrate that CRISPR/Cas system is not only an effective genome editing tool in TNBC, but a promising strategy for the future therapeutic purposes.

The prognostic value of tumor mutation burden (TMB) and its relationship with immune infiltration in breast cancer patients

OBJECTIVE

Although the tumor mutation burden (TMB) was reported as a biomarker for immunotherapy of various cancers, whether it can effectively predict the survival prognosis in breast cancer patients remains unclear. In this study, the prognostic value of TMB and its correlation with immune infiltration were explored by using multigroup studies.

METHODS

The somatic mutation data of 986 breast cancer patients were obtained from TCGA database. Breast cancer patients were divided into a low-TMB group and a high-TMB group according to the quartile of TMB scores. The differentially expressed genes (DEGs) were identified by the "limma" R program. The CIBERSORT algorithm was utilized to estimate the immune cell fraction of each sample. The TIMER database was utilized to evaluate the association between CNVs of immune genes and tumor immune cell infiltration and the prognostic value of the immune cells in breast cancer.

RESULTS

In breast cancer, TP53, PIK3CA, TTN, CDH1 and other genes were the most important mutated genes. Higher survival rate of patients was found in the low-TMB group. Among the top 10 DEGs, three of them belong to the KRT gene family. GSEA enrichment analysis showed that MAPK, Hedgehog, mTOR, TGF-bate and GnRH signaling pathways were enriched in the low-TMB group. The infiltration levels of the most of immune cells were higher in the low-TMB group (P < 0.01). Higher expression of CCL18 and TRGC1 was correlated with poor prognosis. Breast cancer patients with CCL18 copy number variations, especially arm-level gains, showed significantly decreased immune cell infiltration. In the low B cell infiltration group, the survival prognosis of breast cancer patients was poor.

CONCLUSIONS

TMB is a potential prognosis marker in breast cancer. Immune-related gene CCL18 and TRGC1 are biomarkers of poor prognosis while immune (B cell) infiltration is a biomarker of good prognosis.

New Biomarkers Based on Dendritic Cells for Breast Cancer Treatment and Prognosis Diagnosis

Dendritic cells(DCs) play a protective role in the antitumor immunity of most cancers, which can be divided into conventional dendritic cells (cDCs) and plasmacytoid dendritic cells (pDCs). Most current studies are only based on either cDCs or pDCs for the study of the relationship between DCs and breast cancer prognosis, without combining the two together. We aimed to select new biomarkers from pDCs and cDCs. In this paper, the xCell algorithm was first used to calculate the cellular abundance of 64 types of immune cells and stromal cells in tumor samples from the TCGA database, and the high-abundance pDC group and cDC group were divided according to the results of a survival analysis. Then, we looked for the co-expressed gene module of highly infiltrating pDC and cDC patients with a weighted correlation network analysis (WGCNA) and screened out the hub genes, including RBBP5, HNRNPU, PEX19, TPR, and BCL9. Finally, we analyzed the biological functions of the hub genes, and the results showed that RBBP5, TPR, and BCL9 were significantly related to the immune cells and prognosis of patients, and RBBP5 and BCL9 were involved in responding to TCF-related instructions of the Wnt pathway. In addition, we also evaluated the response of pDCs and cDCs with different abundances to chemotherapy, and the results showed that the higher the abundance of pDCs and cDCs, the higher their sensitivity to drugs. This paper revealed new biomarkers related to DCs-among them, BCL9, TPR, and RBBP5 were proven to be closely related to dendritic cells in cancer. For the first time, this paper puts forward that HNRNPU and PEX19 are related to the prognosis of dendritic cells in cancer, which also provides new possibilities for finding new targets for breast cancer immunotherapy.

Radiotherapy, PARP Inhibition, and Immune-Checkpoint Blockade: A Triad to Overcome the Double-Edged Effects of Each Single Player

Radiotherapy and, more recently, PARP inhibitors (PARPis) and immune-checkpoint inhibitors represent effective tools in cancer therapy. Radiotherapy exerts its effects not only by damaging DNA and inducing tumor cell death, but also stimulating anti-tumor immune responses. PARPis are known to exert their therapeutic effects by inhibiting DNA repair, and they may be used in combination with radiotherapy. Both radiotherapy and PARPis modulate inflammatory signals and stimulate type I IFN (IFN-I)-dependent immune activation. However, they can also support the development of an immunosuppressive tumor environment and upregulate PD-L1 expression on tumor cells. When provided as monotherapy, immune-checkpoint inhibitors (mainly antibodies to CTLA-4 and the PD-1/PD-L1 axis) result particularly effective only in immunogenic tumors. Combinations of immunotherapy with therapies that favor priming of the immune response to tumor-associated antigens are, therefore, suitable strategies. The widely explored association of radiotherapy and immunotherapy has confirmed this benefit for several cancers. Association with PARPis has also been investigated in clinical trials. Immunotherapy counteracts the immunosuppressive effects of radiotherapy and/or PARPis and synergies with their immunological effects, promoting and unleashing immune responses toward primary and metastatic lesions (abscopal effect). Here, we discuss the beneficial and counterproductive effects of each therapy and how they can synergize to overcome single-therapy limitations.

Regulation of Inflammasome by microRNAs in Triple-Negative Breast Cancer: New Opportunities for Therapy

During the past decade, researchers have investigated the molecular mechanisms of breast cancer initiation and progression, especially triple-negative breast cancer (TNBC), in order to identify specific biomarkers that could serve as feasible targets for innovative therapeutic strategies development. TNBC is characterized by a dynamic and aggressive nature, due to the absence of estrogen, progesterone and human epidermal growth factor 2 receptors. TNBC progression is associated with the dysregulation of nucleotide-binding oligomerization domain-like receptor and pyrin domain-containing protein 3 (NLRP3) inflammasome, followed by the release of pro-inflammatory cytokines and caspase-1 dependent cell death, termed pyroptosis. The heterogeneity of the breast tumor microenvironment triggers the interest of non-coding RNAs' involvement in NLRP3 inflammasome assembly, TNBC progression and metastasis. Non-coding RNAs are paramount regulators of carcinogenesis and inflammasome pathways, which could help in the development of efficient treatments. This review aims to highlight the contribution of non-coding RNAs that support inflammasome activation and TNBC progression, pointing up their potential for clinical applications as biomarkers for diagnosis and therapy.

Glucose metabolism and lncRNAs in breast cancer: Sworn friend

BACKGROUND

Glucose metabolism disorder is a common feature in cancer. Cancer cells generate much energy through anaerobic glycolysis, which promote the development of tumors. However, long non-coding RNA may play an important role in this process. Our aim is to explore a prognostic risk model based on the glucose metabolism-related lncRNAs which provides clues that lncRNAs predict a clinical outcome through glucose metabolism in breast cancer.

METHODS

1222 RNA-seq were extracted from the TCGA database, and 74 glucose metabolism-related genes were loaded from the GSEA website. Then, 7 glucose metabolism-related lncRNAs risk score model was developed by univariate, Lasso, and multivariate regression analysis. The lncRNA risk model showed that high-risk patients predict a poor clinical outcome with high reliability (P=2.838×10-6). Univariate and multivariate independent prognostic analysis and ROC curve analysis proved that the risk score was an independent prognostic factor in breast cancer with an AUC value of 0.652. Finally, Gene set enrichment analysis showed that cell cycle-related pathways were significantly enriched in a high-risk group.

RESULTS

Our results showed that glucose metabolism-related lncRNAs can affect breast cancer progression. 7 glucose metabolism-related lncRNAs prognostic signature was established to evaluate the OS of patients with breast cancer. PICSAR, LINC00839, AP001505.1, LINC00393 were risk factors and expressed highly in the high-risk group. A Nomogram was made based on this signature to judge patients' living conditions and prognosis.

CONCLUSION

7 glucose metabolism-related lncRNAs risk score model had a high prognostic value in breast cancer. PICSAR, LINC00839, AP001505.1, LINC00393 were risk factors. AP001505.1 expression was increased in most triple-negative breast cancer cells treated with high glucose, which may also take part in breast cancer progression and potential therapeutic targets.

Manganese-enriched photonic/catalytic nanomedicine augments synergistic anti-TNBC photothermal/nanocatalytic/immuno-therapy via activating cGAS-STING pathway

As the clinical efficacy of immunotherapy for triple-negative breast cancer (TNBC) remains limited, exploring new immunotherapy approaches is still indispensable. Mn²⁺ has been proven as a cGAS-STING agonist to remarkably enhance antitumor immunity. Here, we report a combined tumor-therapeutic strategy based on Prussian blue (PB)-mediated photothermal therapy with Mn²⁺-augmented immunotherapy by synergistically activating the cGAS-STING pathway. Mn-enriched photonic nanomedicine (MnPB-MnO_x) were constructed by integrating MnO_x onto the surface of Mn-doped PB nanoparticles. All components of MnPB-MnO_x are biocompatible and biodegradable, wherein sufficient Mn are endowed through rational nanostructure design, conferring easier cGAS-STING activation. Additionally, tumor hyperthermia strengthened by MnPB under near-infrared light radiation, synergistic with the generation of reactive oxygen species catalyzed by MnO_x, double hits cancer cells to release abundant tumor-associated antigens for further promoting immune response stimulation. The local anti-TNBC efficacy of photothermal/immuno-therapy has been proven effective in subcutaneous 4T1-bearing mice. Especially, it has been systematically demonstrated in bilateral orthotopic 4T1-bearing mice that the as-proposed treatment could successfully activate innate and adaptive immunity, and local therapy could engender systemic responses to suppress the distant tumors. Collectively, this work represents a proof-of-concept for a non-invasive Mn-based tumor-immunotherapeutic modality, providing a paradigm for the immunotherapy of metastatic-prone tumors.

Efficacy and Safety of Immune Checkpoint Inhibitors in Triple-negative Breast Cancer: A Study Based on 41 Cohorts Incorporating 6558 Participants

The project was designed to investigate the efficacy and safety of immune checkpoint inhibitors (ICIs) in triple-negative breast cancer (TNBC). Electronic databases were screened to identify relevant trials. The primary endpoints were prognostic parameters and adverse events (AEs) through pooled rate, odds ratio, and hazard ratio (HR) with 95% CI. Totally, 6558 TNBC patients from 41 cohorts were included. The pooled pathologic complete response rate (odds ratio=2.03, 95% CI: 1.35-3.06, P =0.0007) and event-free survival (HR=0.84, 95% CI: 0.73-0.96, P =0.0100) of ICIs plus chemotherapy was higher than that of chemotherapy-alone in early-stage TNBC. For metastatic TNBC, compared with chemotherapy-alone, the addition of ICIs prolonged the progression-free survival (PFS) (HR=0.92, 95% CI: 0.88-0.96, P <0.0001); the improvement also existed in the following 3 subgroups: programmed cell death-ligand 1 positive, race of White and Asian, and patients without previous neoadjuvant or adjuvant chemotherapy; however, the benefit of the combined regimen was not observed in overall survival (OS) (HR=0.95; 95% CI: 0.89-1.03, P =0.2127). In addition, the pooled rates of OS, PFS, and objective response rate of ICIs plus chemotherapy were better than those of ICIs plus targeted therapy or ICIs-alone. In the safety analysis, compared with chemotherapy-alone, ICIs plus chemotherapy increased immune-related AEs and several serious AE. The regimen of ICIs plus chemotherapy is promising in both early-stage and metastatic TNBC, while the increased serious AE should not be neglected. Furthermore, the pooled rates of OS, PFS, and objective response rate of ICIs plus chemotherapy were better than those of ICIs plus targeted therapy or ICIs-alone.

CXCL11 negatively regulated by MED19 favours antitumour immune infiltration in breast cancer

BACKGROUND

Through microarray results, we found that the C-X-C motif chemokine ligand 11 (CXCL11) was negatively regulated by mediator complex subunit 19 (MED19), a protumour factor. However, the biological role and potential mechanism of CXCL11 need to be explored in breast cancer (BRCA).

METHODS

The BRCA dataset was obtained from the Cancer Genome Atlas (TCGA) dataset. Our microarray data and the BRCA dataset of TCGA were analysed and visualized using the R software package. The mRNA and protein levels were measured by qRT-PCR and western blotting.

RESULTS

Inhibition of MED19 in MDA-MB-231 cells caused CXCL11 upregulation. The relative positive regulation of cytokine pathways was enriched after MED19 knockdown. High CXCL11 was determined to be positively correlated with immune response activation, increased antitumour immune cell infiltration, immune checkpoint molecule expression, and enhanced sensitivity to immunotherapy and chemotherapy. Collectively, CXCL11 promoted antitumour immunity and was regulated by MED19 in BRCA. Clarifying the prognostic value and underlying mechanism of CXCL11 in BRCA could provide a theoretical basis to find new diagnostic and therapeutic targets.

Expression of hormone receptors is associated with specific immunological profiles of the breast cancer microenvironment

BACKGROUND

Elucidating the unique immunoregulatory mechanisms in breast cancer microenvironment may help develop new therapeutic strategies. Some studies have suggested that hormone receptors also have immune regulatory functions, but their mechanisms are not fully understood. In this study, we have comprehensively analyzed the relationship between the expressions of estrogen (ER), progesterone (PgR), and androgen receptors (AR), and the immunological profile in breast cancer.

METHODS

Using publicly available gene expression profile datasets, METABRIC and SCAN-B, the associations between the expressions of hormone receptors and the immune cell compositions in breast cancer tissue, estimated by CIBERSORTx algorithm, were analyzed. We histologically evaluated tumor-infiltrating lymphocytes (hTIL), PD-L1 (hPD-L1) expression, and the infiltration of 11 types of immune cells by flow cytometry (FCM) for 45 breast cancer tissue samples. The relationships between them and the expressions of ER, PgR, and AR of tumor tissues, evaluated immunohistochemically, were analyzed.

RESULTS

Expressions of ESR1, PGR, and AR were negatively correlated with overall immune composition. Expressions of ER and AR, but not that of PgR, were inversely associated with hTIL and hPD-L1 expression. FCM analysis showed that the expressions of ER and AR, but not that of PgR, were associated with decreased total leukocyte infiltration. Both CIBERSORTx and FCM analysis showed that ER expression was associated with reduced infiltration of macrophages and CD4+ T cells and that of AR with reduced macrophage infiltration.

CONCLUSION

Hormone receptor expression correlates with specific immunological profiles in the breast cancer microenvironment both at the gene and protein expression levels.

A powerful antitumor "trident": the combination of radio-, immuno- and anti-angiogenesis therapy based on mesoporous silica single coated gold nanoparticles

Although immunotherapy in combination with anti-angiogenesis therapy has made a breakthrough in the first-line treatment of cancer, considering the low responder rate and the adverse events, it is vital to propose a new combination modality. In this study, we report single encapsulated mesoporous silica coated gold nanoparticles that synergize sensitizing radiotherapy with the current combination therapy. Distinguished from simply combining two treatments, the nanoparticle-mediated "trident" therapy resolved the problem of matching the dose between radiation and drug, which determines the outcome since drug demand rises with immunosuppression from increased sensitivity to radiotherapy. The nanomedicine produced energy depositions when radiation was introduced, and released the loaded toripalimab and bevacizumab, exhibiting significant anti-tumor properties. In vitro tumor cell viability results indicated the highest inhibition by the "trident" therapy and in vivo animal models also revealed the earliest decrease in tumor tissue volume. As a result, the "trident" therapy is expected to further improve the anti-tumor benefits of the combination of immunotherapy and anti-angiogenesis therapy and provides a versatile perspective on cancer treatment.

Self-Assembling Peptide-Based Functional Biomaterials

Peptides can self-assemble into various hierarchical nanostructures through noncovalent interactions and form functional materials exhibiting excellent chemical and physical properties, which have broad applications in bio-/nanotechnology. The self-assembly mechanism, self-assembly morphology of peptide supramolecular architecture and their various applications, have been widely explored which have the merit of biocompatibility, easy preparation, and controllable functionality. Herein, we introduce the latest research progress of self-assembling peptide-based nanomaterials and review their applications in biomedicine and optoelectronics, including tissue engineering, anticancer therapy, biomimetic catalysis, energy harvesting. We believe that this review will inspire the rational design and development of novel peptide-based functional bio-inspired materials in the future.

Immunotherapy: Review of the Existing Evidence and Challenges in Breast Cancer

Breast cancer (BC) is a representative malignant tumor that affects women across the world, and it is the main cause of cancer-related deaths in women. Although a large number of treatment methods have been developed for BC in recent years, the results are sometimes unsatisfying. In recent years, treatments of BC have been expanded with immunotherapy. In our article, we list some tumor markers related to immunotherapy for BC. Moreover, we introduce the existing relatively mature immunotherapy and the markers' pathogenesis are involved. The combination of immunotherapy and other therapies for BC are introduced in detail, including the combination of immunotherapy and chemotherapy, the combined use of immunosuppressants and chemotherapy drugs, immunotherapy and molecular targeted therapy. We summarize the clinical effects of these methods. In addition, this paper also makes a preliminary exploration of the combination of immunotherapy, radiotherapy, and nanotechnology for BC.

Combination Analysis of Ferroptosis and Immune Status Predicts Patients Survival in Breast Invasive Ductal Carcinoma

Ferroptosis is a new form of iron-dependent cell death and plays an important role during the occurrence and development of various tumors. Increasingly, evidence shows a convincing interaction between ferroptosis and tumor immunity, which affects cancer patients' prognoses. These two processes cooperatively regulate different developmental stages of tumors and could be considered important tumor therapeutic targets. However, reliable prognostic markers screened based on the combination of ferroptosis and tumor immune status have not been well characterized. Here, we chose the ssGSEA and ESTIMATE algorithms to evaluate the ferroptosis and immune status of a TCGA breast invasive ductal carcinoma (IDC) cohort, which revealed their correlation characteristics as well as patients' prognoses. The WGCNA algorithm was used to identify genes related to both ferroptosis and immunity. Univariate COX, LASSO regression, and multivariate Cox regression models were used to screen prognostic-related genes and construct prognostic risk models. Based on the ferroptosis and immune scores, the cohort was divided into three groups: a high-ferroptosis/low-immune group, a low-ferroptosis/high-immune group, and a mixed group. These three groups exhibited distinctive survival characteristics, as well as unique clinical phenotypes, immune characteristics, and activated signaling pathways. Among them, low-ferroptosis and high-immune statuses were favorable factors for the survival rates of patients. A total of 34 differentially expressed genes related to ferroptosis-immunity were identified among the three groups. After univariate, Lasso regression, and multivariate stepwise screening, two key prognostic genes (GNAI2, PSME1) were identified. Meanwhile, a risk prognosis model was constructed, which can predict the overall survival rate in the validation set. Lastly, we verified the importance of model genes in three independent GEO cohorts. In short, we constructed a prognostic model that assists in patient risk stratification based on ferroptosis-immune-related genes in IDC. This model helps assess patients' prognoses and guide individualized treatment, which also further eelucidatesthe molecular mechanisms of IDC.

Carrier-Free Nanoplatform via Evoking Pyroptosis and Immune Response against Breast Cancer

Pyroptosis, as a novel mode of cell death, has been proven to have impressive antitumor effects. Dying cells undergoing pyroptosis can elicit antitumor immunity by the release of tumor-associated antigens (TAAs) and damage-associated molecular patterns (DAMPs). Accordingly, developing an effective, stable, and controllable nanoplatform that can promote these two side effects is a promising option for cancer therapy. In this study, we designed a carrier-free chemo-photodynamic nanoplatform (A-C/NPs) using a co-assembly strategy with cytarabine (Ara-C) and chlorin e6 (Ce6) to induce pyroptosis and a subsequent immune response against breast cancer. Mechanistically, A-C/NPs can trigger GSDME-mediated pyroptosis in a controllable manner through reactive oxygen species (ROS) accumulation, causing immunogenic cell death (ICD), in which dying cells release high-mobility group box 1 (HMGB1), adenosine triphosphate (ATP), and calcitonin (CRT). Additionally, Ara-C can stimulate the maturation of cytotoxic T lymphocytes to act synergistically with Ce6-mediated immunogenic cell death (ICD), collectively augmenting the anticancer effect of A-C/NPs. The A-C/NPs showed excellent suppressive effects on the growth of orthotopic, abscopal, and recurrent tumors in a breast cancer mouse model. The chemo-photodynamic therapy (PDT) using the proposed nanomedicine strategy could be a novel strategy for triggering pyroptosis and improving the global anticancer immune response.

Facts and Perspectives: Implications of tumor glycolysis on immunotherapy response in triple negative breast cancer

Triple negative breast cancer (TNBC) is an aggressive disease that is difficult to treat and portends a poor prognosis in many patients. Recent efforts to implement immune checkpoint inhibitors into the treatment landscape of TNBC have led to improved outcomes in a subset of patients both in the early stage and metastatic settings. However, a large portion of patients with TNBC remain resistant to immune checkpoint inhibitors and have limited treatment options beyond cytotoxic chemotherapy. The interplay between the anti-tumor immune response and tumor metabolism contributes to immunotherapy response in the preclinical setting, and likely in the clinical setting as well. Specifically, tumor glycolysis and lactate production influence the tumor immune microenvironment through creation of metabolic competition with infiltrating immune cells, which impacts response to immune checkpoint blockade. In this review, we will focus on how glucose metabolism within TNBC tumors influences the response to immune checkpoint blockade and potential ways of harnessing this information to improve clinical outcomes.

Neoadjuvant checkpoint blockade in combination with Chemotherapy in patients with tripe-negative breast cancer: exploratory analysis of real-world, multicenter data

PURPOSE

Despite the poor prognosis of triple-negative breast cancer (TNBC), it has been demonstrated that neoadjuvant immunotherapy in combination with chemotherapy can improve the pathologic complete response (pCR) rate and/or long-term outcome of TNBC. However, there have been no real-world studies reporting on the effectiveness of neoadjuvant checkpoint inhibitors in early TNBC.

METHODS

Between November 2019 and December 2021, 63 early TNBC patients treated with anti-PD-1 antibodies (pembrolizumab or camrelizumab) or anti-PD-L1 antibody (atezolizumab) in combination with chemotherapy at seven institutions were included. PCR1 defined as ypT0/Tis and ypN0 was the primary endpoint. Secondary endpoints included pCR2 defined as ypT0/Tis, overall response rate (ORR), disease-free survival (DFS), drug-related adverse events (AEs) and biomarkers.

RESULTS

Among the patients in the current study, 34.9% of patients were able to achieve pCR1, and 47.6% of patients had achieved pCR2. The ORR was 82.5%. 33 patients with non-pCR2 tumors were found to have a median DFS of 20.7 months (95% CI 16.3 months-not reached). The DFS of patients with pCR2 and non-pCR2 after neoadjuvant therapy was significantly different (HR = 0.28, 95% CI 0.10-0.79; P = 0.038). The most common AEs were nausea (63.4%), fatigue (42.7%), leucopenia (30.0%) and elevated transaminase (11.7%).

CONCLUSION

It is possible to achieve a meaningful pCR rate and DFS by combining neoadjuvant checkpoint blockade with chemotherapy in patients with high-risk TNBC. Compared to clinical trials, however, there was a slightly lower pCR rate in this multicentered real-world study.

A circadian rhythm-related gene signature for prognosis, invasion and immune microenvironment of breast cancer

Background: Circadian dysregulation is linked to the onset and progression of cancer, but current knowledge of the role of circadian rhythm-related genes (CRRGs) in breast cancer (BC) is limited and incomplete. The purpose of this study was to investigate the potential role and immune-related prognostic significance of CRRGs in BC. Methods: The Cancer Genome Atlas breast cancer (TCGA-BRCA) genetic data were combined with 1369 CRRGs to create a model of BC prognosis-related CRRGs. To validate the model's predictive power in TCGA and other external datasets, the Kaplan-Meier survival curve and receptor operation characteristic curve were plotted. The relationship between CRRGs model and gene enrichment pathways, immune cell infiltration, and differences in patient response to immune checkpoint inhibitors (ICIs) therapy was then discussed. Results: A CRRG-based eighteen-gene model was developed that accurately predicted the survival time of BC patients. Based on this model, BC patients can be classified as high or low risk. The high-risk group has negative immune cell infiltration (such as macrophages M0 and M2) and a poor therapeutic response to ICIs due to lower immune checkpoint gene expression. Furthermore, TCF7 and IFNG were found to be strongly associated with immune checkpoints in CRRGs model. Conclusion: The 18 CRRGs may be useful in assessing the prognosis of BC patients, studying immune infiltration, and developing more effective immunotherapy strategies.

Identification and Validation of a Novel Glycolysis-Related Gene Signature for Predicting the Prognosis and Therapeutic Response in Triple-Negative Breast Cancer

INTRODUCTION

A high malignancy rate and poor prognosis are common problems with triple-negative breast cancer (TNBC). There is increasing evidence that glycolysis plays vital roles in tumorigenesis, tumor invasion, immune evasion, chemoresistance, and metastasis. However, a comprehensive analysis of the diagnostic and prognostic significance of glycolysis in TNBC is lacking.

METHODS

Transcriptomic and clinical data of TNBC patients were obtained from The Cancer Genome Atlas (TCGA) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) databases, respectively. Glycolysis-related genes (GRGs) were collected from the Molecular Signatures Database (MSigDB). Differential comparative analysis was performed to obtain the differentially expressed (DE)-GRGs associated with TNBC. Based on the DE-GRGs, a glycolysis-related risk signature was established using Least Absolute Shrinkage and Selector Operation (LASSO) and multivariable Cox regression analyses. The prognostic value, tumor microenvironment, mutation status, and chemotherapy response of different risk groups were analyzed. An independent cohort from the METABRIC database was used for external validation. Furthermore, the expression patterns of five genes derived from the prognostic model were validated by quantitative real-time polymerase chain reaction (RT-qPCR).

RESULTS

The glycolysis-related prognostic signature included five genes (IFNG, ACSS2, IRS2, GFUS, and GAL3ST1) and predicted the prognosis of TNBC patients independent of clinical factors (p < 0.05). Patients were divided into high- and low-risk groups based on the median risk score. Compared to low-risk TNBC patients, high-risk patients had significantly decreased overall survival (HR = 2.718, p < 0.001). Receiver operating characteristic and calibration curves demonstrated that the model had high performance in terms of predicting survival and risk stratification. The results remained consistent after external verification. Additionally, the tumor immune microenvironment significantly differed between the risk groups. Low-risk TNBC patients had a better immunotherapy response than high-risk patients. High-risk TNBC patients with a poor prognosis may benefit from targeted therapy.

CONCLUSIONS

This study developed a novel glycolysis and prognosis-related (GRP) signature based on GRGs to predict the prognosis of TNBC patients, and may aid clinical decision-making for these patients.

Identification of a centrosome-related prognostic signature for breast cancer

Background

As the major microtubule organizing center in animal cells, the centrosome is implicated with human breast tumor in multiple ways, such as promotion of tumor cell immune evasion. Here, we aimed to detect the expression of centrosome-related genes (CRGs) in normal and malignant breast tissues, and construct a novel centrosome-related prognostic model to discover new biomarkers and screen drugs for breast cancer.

Methods

We collected CRGs from the public databases and literature. The differentially expressed CRGs between normal and malignant breast tissues were identified by the DESeq2. Univariate Cox and LASSO regression analyses were conducted to screen candidate prognostic CRGs and develop a centrosome-related signature (CRS) to score breast cancer patients. We further manipulated and visualized data from TCGA, GEO, IMvigor210, TCIA and TIMER to explore the correlation between CRS and patient outcomes, clinical manifestations, mutational landscapes, tumor immune microenvironments, and responses to diverse therapies. Single cell analyses were performed to investigate the difference of immune cell landscape between high- and low-risk group patients. In addition, we constructed a nomogram to guide clinicians in precise treatment.

Results

A total of 726 CRGs were collected from the public databases and literature. PSME2, MAPK10, EIF4EBP1 were screened as the prognostic genes in breast cancer. Next, we constructed a centrosome-related prognostic signature and validated its efficacy based on the genes for predicting the survival of breast cancer patients. The high-risk group patients had poor prognoses, the area under the ROC curve for 1-, 3-, and 5-year overall survival (OS) was 0.77, 0.67, and 0.65, respectively. The predictive capacity of CRS was validated by other datasets from GEO dataset. In addition, high-risk group patients exhibited elevated level of mutational landscapes and decreased level of immune infiltration, especially T and B lymphocytes. In terms of treatment responses, patients in the high-risk group were found to be resistant to immunotherapy but sensitive to chemotherapy. Moreover, we screened a series of candidate anticancer drugs with high sensitivity in the high-risk group.

Conclusion

Our work exploited a centrosome-related prognostic signature and developed a predictive nomogram capable of accurately predicting breast cancer OS. The above discoveries provide deeper insights into the vital roles of the centrosome and contribute to the development of personalized treatment for breast cancer.

Comprehensive analysis of nicotinamide metabolism-related signature for predicting prognosis and immunotherapy response in breast cancer

Background

Breast cancer (BC) is the most common malignancy among women. Nicotinamide (NAM) metabolism regulates the development of multiple tumors. Herein, we sought to develop a NAM metabolism-related signature (NMRS) to make predictions of survival, tumor microenvironment (TME) and treatment efficacy in BC patients.

Methods

Transcriptional profiles and clinical data from The Cancer Genome Atlas (TCGA) were analyzed. NAM metabolism-related genes (NMRGs) were retrieved from the Molecular Signatures Database. Consensus clustering was performed on the NMRGs and the differentially expressed genes between different clusters were identified. Univariate Cox, Lasso, and multivariate Cox regression analyses were sequentially conducted to develop the NAM metabolism-related signature (NMRS), which was then validated in the International Cancer Genome Consortium (ICGC) database and Gene Expression Omnibus (GEO) single-cell RNA-seq data. Further studies, such as gene set enrichment analysis (GSEA), ESTIMATE, CIBERSORT, SubMap, and Immunophenoscore (IPS) algorithm, cancer-immunity cycle (CIC), tumor mutation burden (TMB), and drug sensitivity were performed to assess the TME and treatment response.

Results

We identified a 6-gene NMRS that was significantly associated with BC prognosis as an independent indicator. We performed risk stratification according to the NMRS and the low-risk group showed preferable clinical outcomes (P < 0.001). A comprehensive nomogram was developed and showed excellent predictive value for prognosis. GSEA demonstrated that the low-risk group was predominantly enriched in immune-associated pathways, whereas the high-risk group was enriched in cancer-related pathways. The ESTIMATE and CIBERSORT algorithms revealed that the low-risk group had a higher abundance of anti-tumor immunocyte infiltration (P < 0.05). Results of Submap, IPS, CIC, TMB, and external immunotherapy cohort (iMvigor210) analyses showed that the low-risk group were indicative of better immunotherapy response (P < 0.05).

Conclusions

The novel signature offers a promising way to evaluate the prognosis and treatment efficacy in BC patients, which may facilitate clinical practice and management.

KLF2 is a clinical diagnostic and treatment biomarker of breast cancer

Background: As a highly prevalent malignancy among women worldwide, breast cancer, remains a critical public health issue necessitating the development of novel therapeutics and biomarkers. Kruppel Like Factor 2 (KLF2), a member of the Kruppel family of transcription factors, has been implicated in various types of cancer due to its diminished expression; however, the potential implications of KLF2 expression in relation to breast cancer progression, prognosis, and therapy remain unclear. Methods: The present study employed the Tumor Immune Estimation Resource (TIMER) and The Human Protein Atlas databases to investigate the expression pattern of KLF2 in pan-cancer. The relationship between KLF2 expression and clinical features or immune infiltration of The Cancer Genome Atlas (TCGA) breast cancer samples was evaluated using Breast Cancer Integrative Platform (BCIP) and TIMER. The expression levels of KLF2 in breast cancer were validated via immunohistochemical staining analysis. Gene Set Enrichment Analysis (GSEA) to study the KLF2-related gene ontology. STRING database was employed to construct a protein-protein interaction (PPI) network of KLF2 in relation to vascular endothelial growth factor A (VEGFA) and hypoxia-inducible factor 1α (HIF1α). The expression of KLF2 following diverse breast cancer therapies was analyzed in the Gene Expression Omnibus (GEO) databases. The expression of KLF2 following treatment with simvastatin was validated via immunofluorescence and western blotting. Results: Our study reveals that KLF2 displays significantly reduced expression in cancerous tissues compared to non-cancerous controls. Patients with low KLF2 expression levels exhibited poor prognosis across multiple cancer types. KLF2 expression levels were found to be reduced in advanced cancer stages and grades, while positively correlated with the expression of estrogen receptor (ER), progesterone receptor (PR), and tumor size in breast cancer. KLF2 expression is associated with diverse immune infiltration cells, and may impact the breast tumor immune microenvironment by regulating dendritic cell activation. Additionally, we observed a negative correlation between KLF2 expression levels and angiogenesis, as well as the expression of VEGFA and HIF1α. Notably, the anticancer drug simvastatin could induce KLF2 expression in both breast cancer. Conclusion: Based on our observations, KLF2 has potential as a diagnostic, prognostic, and therapeutic biomarker for breast cancer.

High VISTA expression is linked to a potent epithelial-mesenchymal transition and is positively correlated with PD1 in breast cancer

Breast cancer is the most common type of tumor in women worldwide. Immune checkpoint inhibitors, particularly anti-PDL1, have shown promise as a therapeutic approach for managing this disease. However, this type of immunotherapy still fails to work for some patients, leading researchers to explore alternative immune checkpoint targets. The Ig suppressor of T cell activation domain V (VISTA) has emerged as a novel immune checkpoint that delivers inhibitory signals to T cells and has demonstrated encouraging results in various cancers. Our study investigated the association of VISTA expression with clinicopathological parameters in breast cancer patients, its involvement in the Epithelial-Mesenchymal-Transition (EMT) process, and its correlation with PD1 expression. Transcriptomic analysis revealed that VISTA was associated with lobular and metaplastic histological type, tumor size, lymph node status, ER and PR negative status, and the TNBC molecular subtype. Furthermore, VISTA expression was strongly associated with an immunosuppressive tumor microenvironment. Immunohistochemistry analysis corroborated the transcriptomic results, indicating that VISTA was expressed in most immune cells (94%) and was significantly expressed in breast cancer tumor cells compared to matched adjacent tissues. Our study also showed for the first time that VISTA overexpression in breast cancer cells could be associated with the EMT process. Additionally, we identified a positive correlation between VISTA and PD-1 expression. Together, these results highlight the immunosuppressive effect of VISTA in breast cancer patients and suggest that bi-specific targeting of VISTA and PD-1 in combination therapy could be beneficial for these patients.

Identification of prognostic cancer-associated fibroblast markers in luminal breast cancer using weighted gene co-expression network analysis

Background

Cancer-associated fibroblasts (CAFs) play a pivotal role in cancer progression and are known to mediate endocrine and chemotherapy resistance through paracrine signaling. Additionally, they directly influence the expression and growth dependence of ER in Luminal breast cancer (LBC). This study aims to investigate stromal CAF-related factors and develop a CAF-related classifier to predict the prognosis and therapeutic outcomes in LBC.

Methods

The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were utilized to obtain mRNA expression and clinical information from 694 and 101 LBC samples, respectively. CAF infiltrations were determined by estimating the proportion of immune and cancer cells (EPIC) method, while stromal scores were calculated using the Estimation of STromal and Immune cells in MAlignant Tumors using Expression data (ESTIMATE) algorithm. Weighted gene co-expression network analysis (WGCNA) was used to identify stromal CAF-related genes. A CAF risk signature was developed through univariate and least absolute shrinkage and selection operator method (LASSO) Cox regression model. The Spearman test was used to evaluate the correlation between CAF risk score, CAF markers, and CAF infiltrations estimated through EPIC, xCell, microenvironment cell populations-counter (MCP-counter), and Tumor Immune Dysfunction and Exclusion (TIDE) algorithms. The TIDE algorithm was further utilized to assess the response to immunotherapy. Additionally, Gene set enrichment analysis (GSEA) was applied to elucidate the molecular mechanisms underlying the findings.

Results

We constructed a 5-gene prognostic model consisting of RIN2, THBS1, IL1R1, RAB31, and COL11A1 for CAF. Using the median CAF risk score as the cutoff, we classified LBC patients into high- and low-CAF-risk groups and found that those in the high-risk group had a significantly worse prognosis. Spearman correlation analyses demonstrated a strong positive correlation between the CAF risk score and stromal and CAF infiltrations, with the five model genes showing positive correlations with CAF markers. In addition, the TIDE analysis revealed that high-CAF-risk patients were less likely to respond to immunotherapy. Gene set enrichment analysis (GSEA) identified significant enrichment of ECM receptor interaction, regulation of actin cytoskeleton, epithelial-mesenchymal transition (EMT), and TGF-β signaling pathway gene sets in the high-CAF-risk group patients.

Conclusion

The five-gene prognostic CAF signature presented in this study was not only reliable for predicting prognosis in LBC patients, but it was also effective in estimating clinical immunotherapy response. These findings have significant clinical implications, as the signature may guide tailored anti-CAF therapy in combination with immunotherapy for LBC patients.

A comparison of cancer vaccine adjuvants in clinical trials

Cancer treatment has come a long way in increasing overall survival; however, evasion of the immune system continues to be a challenge in treating individuals with established disease burdens. Due to the difficulty in stimulating an immune response against cancer, approaches utilizing combination adjuvants with different mechanisms may be beneficial. A combination of these adjuvants with other adjuvants or other treatments has demonstrated synergistic effects in the form of a robust and sustained immune response, demonstrating the importance of further development. This review discusses the intricacies of immune evasion, applications of adjuvants with different mechanisms of action, and adjuvants used for cancer immunotherapy in clinical trials.

Triple-Negative Breast Cancer: Multimodality Appearance

Purpose of Review

Triple-negative breast cancer (TNBC) represents about 15–20% of all breast cancers and often presents as an aggressive cancer with poor prognosis compared to other forms of breast cancer. This article will review the clinical manifestations, imaging features, pathology correlation, treatment and management, and prognosis of TNBC.

Recent Findings

While mammography and ultrasound can be used to diagnose TNBC, MRI is the most accurate and sensitive modality to detect TNBC at nearly 100% sensitivity. Contrast-enhanced breast MRI is the optimal imaging study for assessing response to neoadjuvant chemotherapy and can be used to tailor systemic therapy.

Summary

Understanding the imaging appearance of TNBC is imperative to diagnose TNBC accurately and to help guide management.

Pharmaceutical targeting Th2-mediated immunity enhances immunotherapy response in breast cancer

BACKGROUND

Breast cancer is a complex disease with a highly immunosuppressive tumor microenvironment, and has limited clinical response to immune checkpoint blockade (ICB) therapy. T-helper 2 (Th2) cells, an important component of the tumor microenvironment (TME), play an essential role in regulation of tumor immunity. However, the deep relationship between Th2-mediated immunity and immune evasion in breast cancer remains enigmatic.

METHODS

Here, we first used bioinformatics analysis to explore the correlation between Th2 infiltration and immune landscape in breast cancer. Suplatast tosilate (IPD-1151 T, IPD), an inhibitor of Th2 function, was then employed to investigate the biological effects of Th2 blockade on tumor growth and immune microenvironment in immunocompetent murine breast cancer models. The tumor microenvironment was analyzed by flow cytometry, mass cytometry, and immunofluorescence staining. Furthermore, we examined the efficacy of IPD combination with ICB treatment by evaluating TME, tumor growth and mice survival.

RESULTS

Our bioinformatics analysis suggested that higher infiltration of Th2 cells indicates a tumor immunosuppressive microenvironment in breast cancer. In three murine breast cancer models (EO771, 4T1 and EMT6), IPD significantly inhibited the IL-4 secretion by Th2 cells, promoted Th2 to Th1 switching, remodeled the immune landscape and inhibited tumor growth. Remarkably, CD8⁺ T cell infiltration and the cytotoxic activity of cytotoxic T lymphocyte (CTL) in tumor tissues were evidently enhanced after IPD treatment. Furthermore, increased effector CD4⁺ T cells and decreased myeloid-derived suppressor cells and M2-like macrophages were also demonstrated in IPD-treated tumors. Importantly, we found IPD reinforced the therapeutic response of ICB without increasing potential adverse effects.

CONCLUSIONS

Our findings demonstrate that pharmaceutical inhibition of Th2 cell function improves ICB response via remodeling immune landscape of TME, which illustrates a promising combinatorial immunotherapy.

An autophagy-related long non-coding RNA prognostic model and related immune research for female breast cancer

Introduction

Breast cancer (BRCA) is the most common malignancy among women worldwide. It was widely accepted that autophagy and the tumor immune microenvironment play an important role in the biological process of BRCA. Long non-coding RNAs (lncRNAs), as vital regulatory molecules, are involved in the occurrence and development of BRCA. The aim of this study was to assess the prognosis of BRCA by constructing an autophagy-related lncRNA (ARlncRNA) prognostic model and to provide individualized guidance for the treatment of BRCA.

Methods

The clinical data and transcriptome data of patients with BRCA were acquired from the Cancer Genome Atlas database (TCGA), and autophagy-related genes were obtained from the human autophagy database (HADb). ARlncRNAs were identified by conducting co‑expression analysis. Univariate and multivariate Cox regression analysis were performed to construct an ARlncRNA prognostic model. The prognostic model was evaluated by Kaplan-Meier survival analysis, plotting risk curve, Independent prognostic analysis, clinical correlation analysis and plotting ROC curves. Finally, the tumor immune microenvironment of the prognostic model was studied.

Results

10 ARlncRNAs(AC090912.1, LINC01871, AL358472.3, AL122010.1, SEMA3B-AS1, BAIAP2-DT, MAPT-AS1, DNAH10OS, AC015819.1, AC090198.1) were included in the model. Kaplan-Meier survival analysis of the prognostic model showed that the overall survival(OS) of the low-risk group was significantly better than that of the high-risk group (p< 0.001). Multivariate Cox regression analyses suggested that the prognostic model was an independent prognostic factor for BRCA (HR = 1.788, CI = 1.534-2.084, p < 0.001). ROCs of 1-, 3- and 5-year survival revealed that the AUC values of the prognostic model were all > 0.7, with values of 0.779, 0.746, and 0.731, respectively. In addition, Gene Set Enrichment Analysis (GSEA) suggested that several tumor-related pathways were enriched in the high-risk group, while several immune‑related pathways were enriched in the low-risk group. Patients in the low-risk group had higher immune scores and their immune cells and immune pathways were more active. Patients in the low-risk group had higher PD-1 and CTLA-4 levels and received more benefits from immune checkpoint inhibitors (ICIs) therapy.

Discussion

The ARlncRNA prognostic model showed good performance in predicting the prognosis of patients with BRCA and is of great significance to guide the individualized treatment of these patients.

Comprehensive analysis of the expression, prognostic significance, and regulation pathway of G2E3 in breast cancer

BACKGROUND

Loss of G2-specific E3-like (G2E3) protein sensitizes tumor cells to chemotherapy. However, the role of G2E3 in breast cancer development and patient's prognosis is unclear. Here, we explored the expression, prognostic significance, and regulatory pathway of G2E3 in breast cancer.

METHODS

TCGA and UALCAN database were utilized to explore G2E3 expression in breast cancer and normal tissues and its expression in breast cancer based on clinicopathological characteristics, respectively. The Kaplan-Meier plotter database was utilized to determine the effect of G2E3 on the prognosis of breast cancer patients. RT-PCR was utilized to validate the G2E3 expression in cancerous and normal breast tissues. Immunohistochemistry analysis was utilized to validate the prognostic effect of G2E3 expression in breast cancer patients and the relationship between G2E3 expression and lymphocyte infiltration levels. Receiver operating characteristic (ROC) curves were also generated to validate the diagnostic value of G2E3 expression in recurrence/distant organ metastasis and death. The STRING database, DAVID database, and Sanger-box tools were utilized to perform GO functional, KEGG pathway enrichment, and GSEA analysis. The TISIDB database was utilized to determine the relationship between G2E3 expression and tumor immunity. Finally, CTD database was utilized to screen for potential therapeutic compounds that could reduce the G2E3 mRNA expression.

RESULTS

TCGA data presented that G2E3 expression was higher in breast cancer tissues than in normal breast tissues. This result was further validated by RT-PCR (P = 0.003). The Kaplan-Meier plotter database suggested that patients with high G2E3 mRNA expression had significantly shorter RFS and OS than patients with low G2E3 mRNA expression. Immunohistochemistry analysis of 156 breast cancer clinical specimens also validated patients with G2E3-positive expression had a significantly shorter DFS and OS than patients with G2E3-negative expression. Thus, G2E3 expression was an independent prognostic predictor of DFS and OS. The G2E3-positive expression also has a high diagnostic value for recurrence/distant organ metastasis and death. GSEA analysis revealed that G2E3 might be enriched in the E2F, PI3K/AKT/mTOR signaling, DNA repair pathways, and other cancer-related signaling pathways. The TISIDB database showed that G2E3 expression was significantly negatively associated with lymphocyte infiltration. This result was further validated in clinical breast cancer samples (P = 0.048; R = -0.158). Using the CTD database, we found that (+)-JQ1 compound, 1,2-dimethylhydrazine, and other compounds may decrease the G2E3 mRNA expression. These compounds could serve as potential therapeutic compounds for the clinical treatment of breast cancer.

CONCLUSIONS

G2E3 expression was higher in breast cancer tissues than in normal tissues. G2E3-positive expression was related to a worse survival outcome in patients with breast cancer. Genes co-expressed with G2E3 may be enriched in the breast cancer-related signaling pathways. The G2E3 expression was significantly negatively associated with lymphocyte infiltration. G2E3 may serve as a novel prognostic biomarker and therapeutic target for breast cancer.

Prognostic value of CD8+ tumor-infiltrating T cells in patients with breast cancer: A systematic review and meta-analysis

CD8⁺ tumor-infiltrating lymphocytes have been regarded as potential biomarkers for cancer prognosis, while the prognostic effect of CD8⁺ tumor-infiltrating T cells remains controversial in breast cancer. In the present study, a meta-analysis was performed to evaluate the prognostic value of CD8⁺ T cells in breast cancer and the associations between CD8⁺ T cells and the pathological characteristics. The PubMed, Embase and the Cochrane Library were systematically searched entries added from the establishment of the database to November 2021 and prospective or retrospective studies of patients with breast cancer were included. The Newcastle-Ottawa Scale was used to assess the quality of evidence for each study. STATA 15.1 was used for the data analysis. A total of 14 studies comprising 22,222 patients were included in the final analysis and the pooled results suggested that a high CD8⁺ T-cell infiltration level was significantly related to better overall survival [hazard ratio (HR)=0.70, 95% confidence interval (CI): 0.60-0.82, P<0.001] and disease-free survival (HR=0.63, 95% CI: 0.49-0.81, P<0.001) for patients with breast cancer. In addition, a high CD8⁺ T-cell infiltration level was significantly associated with decreased expression of estrogen receptor [odds ratio (OR)=1.92, 95% CI: 1.30-2.85, P=0.001] and progesterone receptor (OR=1.66, 95% CI: 1.14-2.42, P=0.008), and increased human epidermal growth factor receptor 2 expression (OR=0.79, 95% CI: 0.66-0.94, P=0.010) in patients with breast cancer, while there was no significant association between CD8+ T-cell infiltration and age, tumor size or lymph node status of patients with breast cancer (P>0.05). In conclusion, CD8⁺ T-cell infiltration is of prognostic value in patients with breast cancer. High levels of CD8⁺ T-cell infiltration were related to improved prognosis, including OS and DFS, in patients with breast cancer.

CMTM7 recognizes an immune-hot tumor microenvironment and predicts therapeutic response of immunotherapy in breast cancer well

Breast cancer (BRCA) is a complex disease that leads to major mortalities and unsatisfactory clinical outcomes among women worldwide. CKLF-like MARVEL transmembrane domain-containing 7 (CMTM7) is a potential tumor suppressor and regulator of PD-L1, which has been found as a functional signature in considerable oncogenesis, progression, and therapeutic resistance via deletion and downregulation. In this research, triple-negative breast cancer (BRCA), a molecular subtype having a lower response to endocrinotherapy but a higher response to chemotherapy and immunotherapy, showed higher transcriptional levels of CMTM7. Moreover, CMTM7 positively correlated with immunomodulators, tumor-infiltrating immune cells (TIICs), and immune checkpoints in many independent datasets. Furthermore, in an immunotherapy cohort of BRCA, patients with high CMTM7 expression were more sensitive to immunotherapy, and the therapeutic predictive value of CMTM7 is higher than that of PD-1 and PD-L1. To sum up, CMTM7 correlated with an inflamed tumor microenvironment and identified immune-hot tumors, which can be a novel biomarker for the recognition of immunological characteristics and an immunotherapeutic response in BRCA.

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.

Pan-cancer analysis of DEPDC1 as a candidate prognostic biomarker and associated with immune infiltration

Background

DEP domain containing 1 (DEPDC1) gene is upregulated in several malignancies and contributes to tumorigenesis. Although the role of DEPDC1 in tumor is becoming increasingly popular, the function of DEPDC1 in pan-cancer still needs to be systematically elucidated.

Methods

Data were downloaded from Genotype-Tissue Expression Data (GTEx), The Cancer Genome Atlas (TCGA) TIMER2.0, TISIDB, STRING, and CancerSEA databases and analyzed to determine the functionality of the DEPDC1. The results were visualized using tools provided by the databases and the R language.

Results

The results showed that DEPDC1 was significantly upregulated in 29 of the 33 human cancers analyzed. In addition, there were significant differences in DEPDC1 expression among cancer immune and molecular subtypes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that DEPDC1 was mainly involved in the cell cycle, and CancerSEA analysis showed that DEPDC1 promoted cell cycle, DNA repair, DNA damage, and proliferation in pan-cancer. Receiver operating characteristic (ROC) curve analysis showed high predictive accuracy for pan-cancer. DEPDC1 expression was positively correlated with activated CD4⁺ T helper 2 cells and common lymphoid progenitor cells, and negatively correlated with natural killer (NK) T cells, CD4⁺ central memory T cells, and CD4⁺ effector memory T cells. Furthermore, DEPDC1 was significantly positively correlated with T cell exhaustion marker genes, such as CD274, transforming growth factor beta receptor 1 (TGFBR1), kinase insert domain receptor (KDR), programmed cell death 1 ligand 2 (PDCD1LG2), granzyme B (GZMB), and granulysin (LAG2). Additionally, DEPDC1 was associated with overall survival (OS), disease-specific survival (DSS), and progress-free interval (PFI) prognosis in multiple tumor types. The ROC analysis showed high predictive accuracy for pan-cancer.

Conclusions

Collectively, DEPDC1 is aberrantly expressed and plays an immune-oncogenic role in pan-cancer, and DEPDC1 may serve as a biomarker for cancer diagnosis and therapy.

Effect of N6-methyladenosine (m6A) regulator-related immunogenes on the prognosis and immune microenvironment of breast cancer

Background

Breast cancer is one of the most common malignant tumor and the prognosis remains unsatisfying. Various studies demonstrate that m6A modulators are new predictors of prognosis in immune microenvironment. We aimed to identify several m6A regulator-related immunogenes and explore the relationship between m6A regulator-related immunogenes and breast cancer prognosis as well as the tumor immune microenvironment (TIME).

Methods

RNA sequencing data and clinical information on 21 m6A regulators in 1,047 breast cancer samples were downloaded from The Cancer Genome Atlas (TCGA), and immune gene data were downloaded from InnateDB. Kaplan-Meier survival analysis was conducted with log-rank test using the survival package. An m6A-related immunogene-prognostic signature was then constructed, followed by immune infiltration and checkpoint analyses.

Results

A risk prognostic signature of m6A regulator-related immunogenes, including TOX, PSME2, MCTS1, NFKBIE, SH3BP4, RSPH1, JAK1, MLLT4, and PTGES3, was constructed. Furthermore, univariate and multivariate Cox regression analyses suggested that the tumor stage and risk score could be independent prognostic factors for patients with breast cancer. Immune infiltration analysis showed that the infiltration levels of T cells, memory B cells, activated NK cells, and macrophages between the high- and low-risk groups were significantly different. In addition, checkpoint analyses demonstrated that the levels of immune checkpoint genes, such as those of LAG3, PDCD1, CTLA4, and HAVCR2, were downregulated in the high-risk group compared to those in the low-risk group.

Conclusions

Our findings suggest that the m6A regulator-related risk prognostic signature can predict the prognosis of breast cancer and that it is related to the immune microenvironment.

A novel ferroptosis‑related gene signature for overall survival prediction and immune infiltration in patients with breast cancer

Breast cancer is the most prevalent type of cancer among women worldwide. The heterogeneous nature of breast cancer poses a serious challenge for prognostic prediction and individualized therapies. Recently, ferroptosis, an iron‑dependent form of programmed cell death, has been reported to serve a significant role in the regulation of the biological behavior of tumors. Several studies have revealed the prognostic significance of the ferroptosis‑related gene (FRG) model; however, additional efforts are required to elucidate the details. Moreover, genes that modulate ferroptosis may be promising candidate bioindicators in cancer therapy. The present study systematically assessed the expression profiles of FRGs to reveal the relationship between FRGs and the prognostic features of patients with breast cancer based on data obtained from the Gene Expression Omnibus and Molecular Taxonomy of Breast Cancer International Consortium. Using a non‑negative matrix factorization clustering method, patients with breast cancer were classified into two sub‑groups (cluster 1 and cluster 2) based on the expression of FRGs. Furthermore, Cox regression, and least absolute shrinkage and selection operator methods were used to construct a risk score formula comprised of nine genes, which stratified patients with breast cancer into two risk groups. Patients belonging to the high‑risk group exhibited significantly shorter overall survival (OS) time compared with patients in the low‑risk group. The prognostic value of this signature was further verified in the training and validation cohorts. The results for univariate and multivariate Cox regression analyses indicated that risk score acted as an independent predictor for OS. Subsequently, a nomogram was constructed. Receiver operating characteristic analysis further confirmed that the resulting nomogram exhibited powerful discriminatory ability. Functional analysis revealed that the immune environment differed notably between the two groups and indicated an association between ferroptosis and breast cancer proliferation, migration and drug resistance. Taken together, the present study demonstrated that FRGs were significantly associated with breast cancer progression, and thus could be used as novel biomarkers for prognostic prediction and individualized treatment of patients with breast cancer.

PDLIM2 is highly expressed in Breast Cancer tumour-associated macrophages and is required for M2 macrophage polarization

The PDZ-LIM domain-containing protein 2 (PDLIM2) regulates cell polarity and the protein stability of key transcription factors in epithelial and hemopoietic cells. We previously reported that PDLIM2 is more highly expressed in Triple Negative Breast Cancer (TNBC) than in other breast cancer types or normal breast tissue. In the course of the TNBC study, it was noted that PDLIM2 was highly expressed in the stroma of PDLIM2-expressing tumours. Here, we investigated the phenotype of these stromal cells and whether any infiltrating immune population was linked to PDLIM2 expression. We found that high PDLIM2 expression in breast tumours was associated with higher levels of infiltrating M2 macrophages, but was not associated with infiltrating T cell sub-populations. We then tested whether PDLIM2 contributes to macrophage differentiation or function by using cultures of bone marrow-derived macrophages from wildtype and Pdlim2 knockout mice. This demonstrated that PDLIM2 is required for naïve macrophage migration and for the full adoption of IL-4-induced M2 polarization, including expression of M2 phenotypic markers, cell adhesion and cell migration. TLR4-, TLR3- or IFNγ-induced M1 macrophage activity was less dependent on PDLIM2. Finally, analysis of publicly available breast cancer datasets showed that high PDLIM2 expression is associated with increased M2 macrophage infiltration. We conclude that PDLIM2 expression influences the tumour associated stroma and, in particular, M2 macrophage infiltration that may contribute to the progression of TNBC or other subsets of breast cancer.

Prognosis stratification in breast cancer and characterization of immunosuppressive microenvironment through a pyrimidine metabolism-related signature

Pyrimidine metabolism is a hallmark of cancer and will soon become an essential part of cancer therapy. In the tumor microenvironment, cells reprogram pyrimidine metabolism intrinsically and extracellularly, thereby promoting tumorigenesis. Metabolites in pyrimidine metabolism have a significant impact on promoting cancer advancement and modulating immune system responses. In preclinical studies and practical clinical applications, critical targets in pyrimidine metabolism are acted upon by drugs to exert promising therapeutic effects on tumors. However, the pyrimidine metabolism in breast cancer (BC) is still largely underexplored. In this study, 163 credible pyrimidine metabolism-related genes (PMGs) were retrieved, and their somatic mutations and expression levels were determined. In addition, by using The Cancer Genome Atlas (TCGA) and the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) databases, 12 PMGs related to the overall survival (OS) were determined using the univariate Cox regression analysis. Subsequently, by performing the LASSO Cox hazards regression analysis in the 12 PMGs in TCGA-BRCA dataset, we developed a prognosis nomogram using eight OS-related PMGs and then verified the same in the METABRIC, GSE96058, GSE20685, GSE42568 and GSE86166 data. Moreover, we validated relationships between the pyrimidine metabolism index (PMI) and the survival probability of patients, essential clinical parameters, including the TNM stage and the PAM50 subtypes. Next, we verified the predictive capability of the optimum model, including the signature, the PAM50 subtype, and age, using ROC analysis and calibration curve, and compared it with other single clinical factors for the predictive power of benefit using decision curve analysis. Finally, we investigated the potential effects of pyrimidine metabolism on immune checkpoints, tumor-infiltrating immune cells, and cytokine levels and determined the potential implications of pyrimidine metabolism in BC immunotherapy. In conclusion, our findings suggest that pyrimidine metabolism has underlying prognostic significance in BC and can facilitate a new management approach for patients with different prognoses and more precise immunotherapy.

Vemurafenib inhibits immune escape biomarker BCL2A1 by targeting PI3K/AKT signaling pathway to suppress breast cancer

Objectives

To investigate the role of immune escape encoding genes on the prognosis of BC, and to predict the novel targeting agents.

Methods

Human immune genes and immune escape encoding genes were obtained from the IMMPORT database and the previous study. Sample information and clinical data on BC were obtained from the TCGA and GTEX databases. Obtaining differentially expressed protein data from cBioportal database. To construct a risk score model by lasso analysis, and nomogram was used to predict score core. GSCA, TIMER and CELLMINER databases were used for immune and drug susceptibility correlation analyses. Cell experiments were verified by MTT, Western blotting, and RT-qPCR.

Results

We found prognostic models consisting of eleven immune escape related protein-coding genes with ROC curves that performed well in the ontology data (AUC for TCGA is 0.672) and the external data (AUC for GSE20685 is 0.663 and for GES42568 is 0.706). Five core prognostic models are related to survival (EIF4EBP1, BCL2A1, NDRG1, ERRFI1 and BRD4) were summarized, and a nomogram was constructed to validate a C-index of 0.695, which was superior to other prognostic models. Relevant drugs targeting core genes were identified based on drug sensitivity analysis, and found that Vemurafenib downregulates the PI3K-AKT pathway and BCL2A1 protein in BC, as confirmed by external data and cellular assays.

Conclusions

Briefly, our work establishes and validates an 11-immune escape risk model, and five core prognostic factors that are mined deeply from this model, and elucidates in detail that Vemurafenib suppresses breast cancer by targeting the PI3K/AKT signaling pathway to inhibit the immune escape biomarker BCL2A1, confirms the validity of the prognostic model, and provides corresponding targeted agents to guide individualized treatment of BC patients.

Comprehensive evaluation of breast cancer immunotherapy and tumor microenvironment characterization based on interleukin genes-related risk model

Breast cancer (BRCA) is the most prevalent malignancy and the leading cause of death in women. Interleukin (IL) genes are critical in tumor initiation and control. Nevertheless, the prognosis value of the IL in BRCA remains unclear. We collected data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), and 94 IL genes were identified from GeneCard. Based on the random forest (RF), least absolute shrinkage and selection operator (LASSO) analysis, and multivariate Cox regression analysis, we constructed an IL signature. GSE22219, GSE25065, and GSE21653 were derived as validation sets. The expression differences in the tumor microenvironment (TME), immunotherapy, and chemosensitivity of BRCA between the high- and low-risk groups were evaluated. Overall, 21 IL genes were selected to construct an IL risk model, of which IL18BP, IL17D, and IL23A were the first time identified as prognostic genes in BRCA. IL score could distinguish BRCA patients with inferior outcomes, and AUC of it was 0.70, 0.76, and 0.72 for 1-,3- and 5- years, respectively, which was also verified in GSE22219, GSE25065, and GSE21653 cohorts. Meanwhile, compared to luminal A and luminal B, HER2-positive and TNBC had significantly higher IL score. Besides, the high-risk group had a significantly higher prevalence of TP53 and TTN but a lower prevalence of PIK3CA, as well as higher tumor mutation burden (TMB) and neoantigen level. High- and low-risk groups exhibited notable differences in immunomodulators and tumor infiltrates immune cells (TIICs), and the high-risk group had significantly lower Tumor Immune Dysfunction and Exclusion (TIDE) score. Additionally, the high-risk group has more responders to immune or anti-HER2 combination therapy, whereas the low-risk group has higher sensitivity to docetaxel and paclitaxel. Consequently, we constructed a reliable risk model based on the IL genes, which can provide more information on both the risk stratification and personalizing management strategies for BRCA.

EIF4G1 Is a Potential Prognostic Biomarker of Breast Cancer

BACKGROUND

Breast cancer (BRCA) is one of the most common cancers in women worldwide and a leading cause of death from malignancy. This study was designed to identify a novel biomarker for prognosticating the survival of BRCA patients.

METHODS

The prognostic potential of eukaryotic translation initiation factor 4 gamma 1 (EIF4G1) was assessed using RNA sequencing (RNA-seq) data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) as training cohort and validation set, respectively. The functional enrichment analysis of differentially expressed genes (DEGs) was performed. The relationship between EIF4G1 and tumor microenvironment (TME) was analyzed. Immunotherapy responses were explored by the immunophenoscores (IPS) and tumor immune dysfunction and exclusion (TIDE) score. The Connectivity Map (CMap) was used to discover potentially effective therapeutic molecules against BRCA. Immunohistochemistry (IHC) was applied to compare the protein levels of EIF4G1 in normal and cancer tissues and to verify the prognostic value of EIF4G1.

RESULTS

BRCA patients with increased expression of EIF4G1 had a shorter overall survival (OS) in all cohorts and results from IHC. EIF4G1-related genes were mainly involved in DNA replication, BRCA metastasis, and the MAPK signaling pathway. Infiltration levels of CD4⁺-activated memory T cells, macrophages M0, macrophages M1, and neutrophils were higher in the EIF4G1 high-expression group than those in the EIF4G1 low-expression group. EIF4G1 was positively correlated with T cell exhaustion. Lower IPS was revealed in high EIF4G1 expression patients. Five potential groups of drugs against BRCA were identified.

CONCLUSION

EIF4G1 might regulate the TME and affect BRCA metastasis, and it is a potential prognostic biomarker and therapeutic target for BRCA.

Melanin-like nanoparticles: advances in surface modification and tumour photothermal therapy

Currently, tumor treatments are characterized by intelligence, diversity and personalization, but the therapeutic reagents used are often limited in clinical efficacy due to problems with water solubility, targeting, stability and multidrug resistance. To remedy these shortcomings, the application of multifunctional nanotechnology in the biomedical field has been widely studied. Synthetic melanin nanoparticles (MNPs) surfaces which contain highly reactive chemical groups such as carboxyl, hydroxyl and amine groups, can be used as a reaction platform on which to graft different functional components. In addition, MNPs easily adhere to substrate surface, and serve as a secondary reaction platform to modify it. The multifunctionality and intrinsic biocompatibility make melanin-like nanoparticles promising as a multifunctional and powerful nanoplatform for oncological applications. This paper first reviews the preparation methods, polymerization mechanisms and physicochemical properties of melanin including natural melanin and chemically synthesized melanin to guide scholars in MNP-based design. Then, recent advances in MNPs especially synthetic polydopamine (PDA) melanin for various medical oncological applications are systematically and thoroughly described, mainly focusing on bioimaging, photothermal therapy (PTT), and drug delivery for tumor therapy. Finally, based on the investigated literature, the current challenges and future directions for clinical translation are reasonably discussed, focusing on the innovative design of MNPs and further elucidation of pharmacokinetics. This paper is a timely and comprehensive and detailed study of the progress of MNPs in tumor therapy, especially PTT, and provides ideas for the design of personalized and customizable oncology nanomedicines to address the heterogeneity of the tumor microenvironment.

Tumor-Derived Exosomes and Their Role in Breast Cancer Metastasis

Breast cancer has been the most common cancer in women worldwide, and metastasis is the leading cause of death from breast cancer. Even though the study of breast cancer metastasis has been extensively carried out, the molecular mechanism is still not fully understood, and diagnosis and prognosis need to be improved. Breast cancer metastasis is a complicated process involving multiple physiological changes, and lung, brain, bone and liver are the main metastatic targets. Exosomes are membrane-bound extracellular vesicles that contain secreted cellular constitutes. The biogenesis and functions of exosomes in cancer have been intensively studied, and mounting studies have indicated that exosomes play a crucial role in cancer metastasis. In this review, we summarize recent findings on the role of breast cancer-derived exosomes in metastasis organotropism and discuss the potential promising clinical applications of targeting exosomes as novel strategies for breast cancer diagnosis and therapy.

Microfluidic live tracking and transcriptomics of cancer-immune cell doublets link intercellular proximity and gene regulation

Cell–cell communication and physical interactions play a vital role in cancer initiation, homeostasis, progression, and immune response. Here, we report a system that combines live capture of different cell types, co-incubation, time-lapse imaging, and gene expression profiling of doublets using a microfluidic integrated fluidic circuit that enables measurement of physical distances between cells and the associated transcriptional profiles due to cell–cell interactions. We track the temporal variations in natural killer—triple-negative breast cancer cell distances and compare them with terminal cellular transcriptome profiles. The results show the time-bound activities of regulatory modules and allude to the existence of transcriptional memory. Our experimental and bioinformatic approaches serve as a proof of concept for interrogating live-cell interactions at doublet resolution. Together, our findings highlight the use of our approach across different cancers and cell types.

Advancements in Polymeric Nanocarriers to Mediate Targeted Therapy against Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) is a destructive disease with a poor prognosis, low survival rate and high rate of metastasis. It comprises 15% of total breast cancers and is marked by deficiency of three important receptor expressions, i.e., progesterone, estrogen, and human epidermal growth factor receptors. This absence of receptors is the foremost cause of current TNBC therapy failure, resulting in poor therapeutic response in patients. Polymeric nanoparticles are gaining much popularity for transporting chemotherapeutics, genes, and small-interfering RNAs. Due to their exclusive properties such as great stability, easy surface modification, stimuli-responsive and controlled drug release, ability to condense more than one therapeutic moiety inside, tumor-specific delivery of payload, enhanced permeation and retention effect, present them as ideal nanocarriers for increasing efficacy, bioavailability and reducing the toxicity of therapeutic agents. They can even be used as theragnostic agents for the diagnosis of TNBC along with its treatment. In this review, we discuss the limitations of already existing TNBC therapies and highlight the novel approach to designing and the functionalization of polymeric nanocarriers for the effective treatment of TNBC.

Immunotherapy in triple negative breast cancer: beyond checkpoint inhibitors

The development of immunotherapy agents has revolutionized the field of oncology. The only FDA-approved immunotherapeutic approach in breast cancer consists of immune checkpoint inhibitors, yet several novel immune-modulatory strategies are being actively studied and appear promising. Innovative immunotherapeutic strategies are urgently needed in triple negative breast cancer (TNBC), a subtype of breast cancer known for its poor prognosis and its resistance to conventional treatments. TNBC is more primed to respond to immunotherapy given the presence of more tumor infiltrating lymphocytes, higher PD-L1 expression, and higher tumor mutation burden relative to the other breast cancer subtypes, and therefore, immuno-oncology represents a key area of promise for TNBC research. The aim of this review is to highlight current data and ongoing efforts to establish the safety and efficacy of immunotherapeutic approaches beyond checkpoint inhibitors in TNBC.