The Immune Microenvironment of Breast Cancer Progression

Progesterone receptor impairs immune respond and down-regulates sensitivity to anti-LAG3 in breast cancer

BACKGROUND

Progesterone receptor (PR) serves as a crucial prognostic and predictive marker in breast cancer. Nonetheless, the interplay between PR and the tumor immune microenvironment remains inadequately understood. This investigation employs bioinformatics analyses, mouse models, and clinical specimens to elucidate the impact of PR on immune microenvironment and identify potential targets for immunotherapy, furnishing valuable guidance for clinical practice.

METHODS

Analysis of immune infiltration score by Xcell between PR-positive and PR-negative breast cancer tumors. Construction of overexpression mouse progesterone receptor (mPgr) EMT-6 cell was to explore the tumor immune microenvironment. Furthermore, anti- Lymphocyte-activation gene 3 (LAG3) therapy aimed to investigate whether PR could influence the effectiveness of immune treatments.

RESULTS

Overexpression mPgr inhibited tumor growth in vitro, but promoted tumor growth in Balb/c mouse. Flow cytometry showed that the proportion and cytotoxicity of CD8+T cells in tumor of overexpressing mPgr group were significantly reduced. The significant reduction in overexpressing mPgr group was found in the proportions of LAG3+CD8+ T cells and LAG3+ Treg T cells. Anti-LAG3 treatment resulted in reduced tumor growth in EV group mouse rather than in overexpressing mPgr group. Patents derived tumor fragment (PDTF) also showed higher anti-tumor ability of CD3+T cell in patents' tumor with PR <20% after anti-human LAG3 treatment in vitro.

CONCLUSIONS

The mPgr promotes tumor growth by downregulating the infiltration and function of cytotoxic cell. LAG3 may be a target of ER-positive breast cancer immunotherapy. The high expression of PR hinders the sensitivity to anti-LAG3 treatment.

A novel model based on lipid metabolism-related genes associated with immune microenvironment predicts metastasis of breast cancer

BACKGROUND

Breast cancer (BC) is the most prevalent malignant tumor among women worldwide and a significant cause of cancer-related deaths in females. Recent studies have shown that lipid metabolism-related genes (LMRGs) exhibit prognostic potential in various types of tumors, including BC. Our study aimed to establish a novel model to predict the metastasis of BC.

METHODS

Clinical information and corresponding RNA data of patients with BC were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus databases. Consensus clustering was performed to identify novel molecular subgroups. Estimation of Stromal and Immune Cells in Malignant Tumor Tissues using Expression, microenvironment cell populations counter, microenvironment cell populations counter, and single-sample gene set enrichment analyses were employed to determine the tumor immune microenvironment and immune status of the identified subgroups. Functional analyses, including Gene Ontology and gene set enrichment analyses, were conducted to elucidate the underlying mechanisms. A prognostic risk model was constructed using the Least Absolute Shrinkage and Selection Operator algorithm and multivariate Cox regression analysis.

RESULTS

This study identified differential gene expression between patients with BC exhibiting metastasis and those without metastasis using public databases. Using the obtained data, we established predictive models based on six LMRGs. Furthermore, consensus clustering and prognostic score grouping analysis revealed that differentially expressed LMRGs influence tumor prognosis by regulating tumor immunity. To facilitate clinical application, we developed a nomogram integrating the risk model and clinical characteristics to accurately predict the prognosis of patients with BC.

CONCLUSION

We developed and validated a novel signature associated with LMRGs for predicting disease-free survival in patients with BC. The expression of LMRGs correlates with the immune microenvironment of patients with BC, providing new insights and improved strategies for the diagnosis and treatment of BC.

Assessment and process optimization of high throughput biofabrication of immunocompetent breast cancer model for drug screening applications

Recent advancements in 3D cancer modeling have significantly enhanced our ability to delve into the intricacies of carcinogenesis. Despite the pharmaceutical industry's substantial investment of both capital and time in the drug screening and development pipeline, a concerning trend persists: drug candidates screened on conventional cancer models exhibit a dismal success rate in clinical trials. One pivotal factor contributing to this discrepancy is the absence of drug testing on pathophysiologically biomimetic 3D cancer models during pre-clinical stages. Unfortunately, current manual methods of 3D cancer modeling, such as spheroids and organoids, suffer from limitations in reproducibility and scalability. In our study, we have meticulously developed 3D bioprinted breast cancer model utilizing decellularized adipose tissue-based hydrogel obtained via a detergent-free decellularization method. Our innovative printing techniques allows for rapid, high-throughput fabrication of 3D cancer models in a 96-well plate format, demonstrating unmatched scalability and reproducibility. Moreover, we have conducted extensive validation, showcasing the efficacy of our platform through drug screening assays involving two potent anti-cancer drugs, 5-Fluorouracil and PRIMA-1Met. Notably, our platform facilitates effortless imaging and gene expression analysis, streamlining the evaluation process. In a bid to enhance the relevance of our cancer model, we have introduced a heterogeneous cell population into the DAT-based bioink. Through meticulous optimization and characterization, we have successfully developed a biomimetic immunocompetent breast cancer model, complete with microenvironmental cues and diverse cell populations. This breakthrough paves the way for rapid multiplex drug screening and the development of personalized cancer models, marking a paradigm shift in cancer research and pharmaceutical development.

Estrogen receptor regulation of the immune microenvironment in breast cancer

Breast cancer (BCa) is the most common cancer in women and the estrogen receptor (ER)+ subtype is increasing in incidence. There are numerous therapy options available for patients that target the ER, however issues such as innate and acquired treatment resistance, and treatment related side effects justify research into alternative therapeutic options for these patients. Patients of many solid tumour types have benefitted from immunotherapy, however response rates have been generally low in ER+ BCa. We summarise the recent work assessing CDK4/6 inhibitors for ER+ BCa and how they have been shown to prime anti-tumour immune cells and achieve impressive results in preclinical models. A great example of how the immune system might be activated against ER+ BCa. We review the role of estrogen signalling in immune cells, and explore recent data highlighting the hormonal regulation of the immune microenvironment of normal breast, BCa and immune disorders. As recent data has indicated that macrophages are particularly susceptible to estrogen signalling, we highlight macrophage phagocytosis as a key potential target for priming the tumour immune microenvironment. We challenge the generally accepted paradigm that ER+ BCa are "immune-cold" - advocating instead for research into therapies that could be used in combination with targeted therapies and/or immune checkpoint blockade to achieve durable antitumour responses in ER+ BCa.

Progression from ductal carcinoma in situ to invasive breast cancer: molecular features and clinical significance

Ductal carcinoma in situ (DCIS) represents pre-invasive breast carcinoma. In untreated cases, 25-60% DCIS progress to invasive ductal carcinoma (IDC). The challenge lies in distinguishing between non-progressive and progressive DCIS, often resulting in over- or under-treatment in many cases. With increasing screen-detected DCIS in these years, the nature of DCIS has aroused worldwide attention. A deeper understanding of the biological nature of DCIS and the molecular journey of the DCIS-IDC transition is crucial for more effective clinical management. Here, we reviewed the key signaling pathways in breast cancer that may contribute to DCIS initiation and progression. We also explored the molecular features of DCIS and IDC, shedding light on the progression of DCIS through both inherent changes within tumor cells and alterations in the tumor microenvironment. In addition, valuable research tools utilized in studying DCIS including preclinical models and newer advanced technologies such as single-cell sequencing, spatial transcriptomics and artificial intelligence, have been systematically summarized. Further, we thoroughly discussed the clinical advancements in DCIS and IDC, including prognostic biomarkers and clinical managements, with the aim of facilitating more personalized treatment strategies in the future. Research on DCIS has already yielded significant insights into breast carcinogenesis and will continue to pave the way for practical clinical applications.

Tumor Cell-Associated IL-1α Affects Breast Cancer Progression and Metastasis in Mice through Manipulation of the Tumor Immune Microenvironment

IL-1α is a dual function cytokine that affects inflammatory and immune responses and plays a pivotal role in cancer. The effects of intracellular IL-1α on the development of triple negative breast cancer (TNBC) in mice were assessed using the CRISPR/Cas9 system to suppress IL-1α expression in 4T1 breast cancer cells. Knockout of IL-1α in 4T1 cells modified expression of multiple genes, including downregulation of cytokines and chemokines involved in the recruitment of tumor-associated pro-inflammatory cells. Orthotopical injection of IL-1α knockout (KO) 4T1 cells into BALB/c mice led to a significant decrease in local tumor growth and lung metastases, compared to injection of wild-type 4T1 (4T1/WT) cells. Neutrophils and myeloid-derived suppressor cells were abundant in tumors developing after injection of 4T1/WT cells, whereas more antigen-presenting cells were observed in the tumor microenvironment after injection of IL-1α KO 4T1 cells. This switch correlated with increased infiltration of CD3+CD8+ and NKp46+cells. Engraftment of IL-1α knockout 4T1 cells into immunodeficient NOD.SCID mice resulted in more rapid tumor growth, with increased lung metastasis in comparison to engraftment of 4T1/WT cells. Our results suggest that tumor-associated IL-1α is involved in TNBC progression in mice by modulating the interplay between immunosuppressive pro-inflammatory cells vs. antigen-presenting and cytotoxic cells.

Analysis of the Correlation and Prognostic Significance of Tertiary Lymphoid Structures in Breast Cancer: A Radiomics-Clinical Integration Approach

BACKGROUND

Tertiary lymphoid structures (TLSs) are potential prognostic indicators. Radiomics may help reduce unnecessary invasive operations.

PURPOSE

To analyze the association between TLSs and prognosis, and to establish a nomogram model to evaluate the expression of TLSs in breast cancer (BC) patients.

STUDY TYPE

Retrospective.

POPULATION

Two hundred forty-two patients with localized primary BC (confirmed by surgery) were divided into BC + TLS group (N = 122) and BC - TLS group (N = 120).

FIELD STRENGTH/SEQUENCE

3.0T; Caipirinha-Dixon-TWIST-volume interpolated breath-hold sequence for dynamic contrast-enhanced (DCE) MRI and inversion-recovery turbo spin echo sequence for T2-weighted imaging (T2WI).

ASSESSMENT

Three models for differentiating BC + TLS and BC - TLS were developed: 1) a clinical model, 2) a radiomics signature model, and 3) a combined clinical and radiomics (nomogram) model. The overall survival (OS), distant metastasis-free survival (DMFS), and disease-free survival (DFS) were compared to evaluate the prognostic value of TLSs.

STATISTICAL TESTS

LASSO algorithm and ANOVA were used to select highly correlated features. Clinical relevant variables were identified by multivariable logistic regression. Model performance was evaluated by the area under the receiver operating characteristic (ROC) curve (AUC), and through decision curve analysis (DCA). The Kaplan-Meier method was used to calculate the survival rate.

RESULTS

The radiomics signature model (training: AUC 0.766; test: AUC 0.749) and the nomogram model (training: AUC 0.820; test: AUC 0.749) showed better validation performance than the clinical model. DCA showed that the nomogram model had a higher net benefit than the other models. The median follow-up time was 52 months. While there was no significant difference in 3-year OS (P = 0.22) between BC + TLS and BC - TLS patients, there were significant differences in 3-year DFS and 3-year DMFS between the two groups.

DATA CONCLUSION

The nomogram model performs well in distinguishing the presence or absence of TLS. BC + TLS patients had higher long-term disease control rates and better prognoses than those without TLS.

EVIDENCE LEVEL

2 TECHNICAL EFFICACY: Stage 2.

Exploring neutrophil functionality in breast cancer progression: A review

Breast cancer remains a pressing global health concern, with a myriad of intricate factors contributing to its development, progression, and heterogeneity. Among these multifaceted elements, the role of immune cells within the tumor microenvironment is gaining increasing attention. In this context, neutrophils, traditionally regarded as the first responders to infections, are emerging as noteworthy participants in the complex landscape of breast cancer. This paper seeks to unravel the intricate and multifaceted role of neutrophils in breast cancer. Neutrophils, classically known for their phagocytic and pro-inflammatory functions, are now recognized for their involvement in promoting or restraining tumor growth. While their presence within the tumor microenvironment may exert antitumor effects through immune surveillance and cytotoxic activities, these innate immune cells can also facilitate tumor progression by fostering an immunosuppressive milieu, promoting angiogenesis, and aiding metastatic dissemination. The intricacies of neutrophil-tumor cell interactions, signaling pathways, and mechanisms governing their recruitment to the tumor site are explored in detail. Challenges and gaps in current knowledge are acknowledged, and future directions for research are outlined. This review underscores the dynamic and context-dependent role of neutrophils in breast cancer and emphasizes the significance of unraveling their multifaceted contributions. As we delve into the complexities of the immune landscape in breast cancer, a deeper understanding of the warriors within, the neutrophils, presents exciting prospects for the development of novel therapeutic strategies and a more comprehensive approach to breast cancer management.

Automated quantification of stromal tumour infiltrating lymphocytes is associated with prognosis in breast cancer

Stromal tumour infiltrating lymphocytes (sTIL) in haematoxylin and eosin (H&E) stained sections has been linked to better outcomes and better responses to neoadjuvant therapy in triple-negative and HER2-positive breast cancer (TNBC and HER2 +). However, the infiltrate includes different cell populations that have specific roles in the tumour immune microenvironment. Various studies have found high concordance between sTIL visual quantification and computational assessment, but specific data on the individual prognostic impact of plasma cells or lymphocytes within sTIL on patient prognosis is still unknown. In this study, we validated a deep-learning breast cancer sTIL scoring model (smsTIL) based on the segmentation of tumour cells, benign ductal cells, lymphocytes, plasma cells, necrosis, and 'other' cells in whole slide images (WSI). Focusing on HER2 + and TNBC patient samples, we assessed the concordance between sTIL visual scoring and the smsTIL in 130 WSI. Furthermore, we analysed 175 WSI to correlate smsTIL with clinical data and patient outcomes. We found a high correlation between sTIL values scored visually and semi-automatically (R = 0.76; P = 2.2e-16). Patients with higher smsTIL had better overall survival (OS) in TNBC (P = 0.0021). In the TNBC cohort, smsTIL was as an independent prognostic factor for OS. As part of this work, we introduce a new segmentation dataset of H&E-stained WSI.

The renin-angiotensin-aldosterone system (RAAS) signaling pathways and cancer: foes versus allies

The renin-angiotensin-aldosterone system (RAAS), is an old system with new fundamental roles in cancer biology which influences cell growth, migration, death, and metastasis. RAAS signaling enhances cell proliferation in malignancy directly and indirectly by affecting tumor cells and modulating angiogenesis. Cancer development may be influenced by the balance between the ACE/Ang II/AT1R and the ACE2/Ang 1-7/Mas receptor pathways. The interactions between Ang II/AT1R and Ang I/AT2R as well as Ang1-7/Mas and alamandine/MrgD receptors in the RAAS pathway can significantly impact the development of cancer. Ang I/AT2R, Ang1-7/Mas, and alamandine/MrgD interactions can have anticancer effects while Ang II/AT1R interactions can be involved in the development of cancer. Evidence suggests that inhibitors of the RAAS, which are conventionally used to treat cardiovascular diseases, may be beneficial in cancer therapies.Herein, we aim to provide a thorough description of the elements of RAAS and their molecular play in cancer. Alongside this, the role of RAAS components in sex-dependent cancers as well as GI cancers will be discussed with the hope of enlightening new venues for adjuvant cancer treatment.

Unveiling the Immune Microenvironment's Role in Breast Cancer: A Glimpse into Promising Frontiers

Breast cancer (BC), one of the most widespread and devastating diseases affecting women worldwide, presents a significant public health challenge. This review explores the emerging frontiers of research focused on deciphering the intricate interplay between BC cells and the immune microenvironment. Understanding the role of the immune system in BC is critical as it holds promise for novel therapeutic approaches and precision medicine strategies. This review delves into the current literature regarding the immune microenvironment's contribution to BC initiation, progression, and metastasis. It examines the complex mechanisms by which BC cells interact with various immune cell populations, including tumor-infiltrating lymphocytes (TILs) and tumor-associated macrophages (TAMs). Furthermore, this review highlights the impact of immune-related factors, such as cytokines and immune checkpoint molecules. Additionally, this comprehensive analysis sheds light on the potential biomarkers associated with the immune response in BC, enabling early diagnosis and prognostic assessment. The therapeutic implications of targeting the immune microenvironment are also explored, encompassing immunotherapeutic strategies and combination therapies to enhance treatment efficacy. The significance of this review lies in its potential to pave the way for novel therapeutic interventions, providing clinicians and researchers with essential knowledge to design targeted and personalized treatment regimens for BC patients.

A novel T-cell exhaustion-related feature can accurately predict the prognosis of OC patients

The phenomenon of T Cell exhaustion (TEX) entails a progressive deterioration in the functionality of T cells within the immune system during prolonged conflicts with chronic infections or tumors. In the context of ovarian cancer immunotherapy, the development, and outcome of treatment are closely linked to T-cell exhaustion. Hence, gaining an in-depth understanding of the features of TEX within the immune microenvironment of ovarian cancer is of paramount importance for the management of OC patients. To this end, we leveraged single-cell RNA data from OC to perform clustering and identify T-cell marker genes utilizing the Unified Modal Approximation and Projection (UMAP) approach. Through GSVA and WGCNA in bulk RNA-seq data, we identified 185 TEX-related genes (TEXRGs). Subsequently, we transformed ten machine learning algorithms into 80 combinations and selected the most optimal one to construct TEX-related prognostic features (TEXRPS) based on the mean C-index of the three OC cohorts. In addition, we explored the disparities in clinicopathological features, mutational status, immune cell infiltration, and immunotherapy efficacy between the high-risk (HR) and low-risk (LR) groups. Upon the integration of clinicopathological features, TEXRPS displayed robust predictive power. Notably, patients in the LR group exhibited a superior prognosis, higher tumor mutational load (TMB), greater immune cell infiltration abundance, and enhanced sensitivity to immunotherapy. Lastly, we verified the differential expression of the model gene CD44 using qRT-PCR. In conclusion, our study offers a valuable tool to guide clinical management and targeted therapy of OC.

Combating breast cancer progression through combination therapy with hypomethylating agent and glucocorticoid

Breast cancer is the leading cause of cancer-related death in women. Among breast cancer types, triple-negative breast cancer (TNBC) accounts for 15% of all breast cancers with aggressive tumor behavior. By using bioinformatic approaches, we observed that the microRNA-708 promoter is highly methylated in breast carcinomas, and this methylation is linked to a poor prognosis. Moreover, microRNA-708 expression correlates with better clinical outcomes in TNBC patients. Combination treatment with the hypomethylating agent decitabine and synthetic glucocorticoid significantly increased the expression of microRNA-708, reactivated DNMT-suppressed pathways, and decreased the expression of multiple metastasis-promoting genes such as matrix metalloproteinases (MMPs) and IL-1β, leading to the suppression of breast cancer cell proliferation, migration, and invasion, as well as reduced tumor growth and distant metastasis in the TNBC xenograft mouse model. Overall, our study reveals a therapeutic opportunity in which a combined regimen of decitabine with glucocorticoid may have therapeutic potential in treating TNBC patients.

Comprehensive research into prognostic and immune signatures of transcription factor family in breast cancer

BACKGROUND

Breast cancer (BRCA) is the most common malignancy with high morbidity and mortality in women, and transcription factor (TF) is closely related to the occurrence and development of BRCA. This study was designed to identify a prognostic gene signature based on TF family to reveal immune characteristics and prognostic survival of BRCA.

METHODS

In this study, RNA-sequence with corresponding clinical data were obtained from The Cancer Genome Atlas (TCGA) and GSE42568. Prognostic differentially expressed transcription factor family genes (TFDEGs) were screened to construct a risk score model, after which BRCA patients were stratified into low-risk and high-risk groups based on their corresponding risk scores. Kaplan-Meier (KM) analysis was applied to evaluate the prognostic implication of risk score model, and a nomogram model was developed and validated with the TCGA and GSE20685. Furthermore, the GSEA revealed pathological processes and signaling pathways enriched in the low-risk and high-risk groups. Finally, analyses regarding levels of immune infiltration, immune checkpoints and chemotactic factors were all completed to investigate the correlation between the risk score and tumor immune microenvironment (TIME).

RESULTS

A prognostic 9-gene signature based on TFDEGs was selected to establish a risk score model. According to KM analyses, high-risk group witnessed a significantly worse overall survival (OS) than low-risk group in both TCGA-BRCA and GSE20685. Furthermore, the nomogram model proved great possibility in predicting the OS of BRCA patients. As indicted in GSEA analysis, tumor-associated pathological processes and pathways were relatively enriched in high-risk group, and the risk score was negatively correlated with ESTIMATE score, infiltration levels of CD4+ and CD8+T cells, as well as expression levels of immune checkpoints and chemotactic factors.

CONCLUSIONS

The prognostic model based on TFDEGs could distinguish as a novel biomarker for predicting prognosis of BRCA patients; in addition, it may also be utilized to identify potential benefit population from immunotherapy in different TIME and predict potential drug targets.

Isogenic Mammary Models of Intraductal Carcinoma Reveal Progression to Invasiveness in the Absence of a Non-Obligatory In Situ Stage

In breast cancer, progression to invasive ductal carcinoma (IDC) involves interactions between immune, myoepithelial, and tumor cells. Development of IDC can proceed through ductal carcinoma in situ (DCIS), a non-obligate, non-invasive stage, or IDC can develop without evidence of DCIS and these cases associate with poorer prognosis. Tractable, immune-competent mouse models are needed to help delineate distinct mechanisms of local tumor cell invasion and prognostic implications. To address these gaps, we delivered murine mammary carcinoma cell lines directly into the main mammary lactiferous duct of immune-competent mice. Using two strains of immune-competent mice (BALB/c, C57BL/6), one immune-compromised (severe combined immunodeficiency; SCID) C57BL/6 strain, and six different murine mammary cancer cell lines (D2.OR, D2A1, 4T1, EMT6, EO771, Py230), we found early loss of ductal myoepithelial cell differentiation markers p63, α-smooth muscle actin, and calponin, and rapid formation of IDC in the absence of DCIS. Rapid IDC formation also occurred in the absence of adaptive immunity. Combined, these studies demonstrate that loss of myoepithelial barrier function does not require an intact immune system, and suggest that these isogenic murine models may prove a useful tool to study IDC in the absence of a non-obligatory DCIS stage-an under-investigated subset of poor prognostic human breast cancer.

Tumour Infiltrating Lymphocytes (TILs) and immune composition in breast cancer patients from Kenya: Spatial distributions and associations with risk factors and tumour characteristics

BACKGROUND

The immune landscape of breast cancer (BC) in patients from Sub Saharan Africa is understudied. Our aims were to describe the distribution of Tumour Infiltrating Lymphocytes (TILs) within the intratumoural stroma (sTILs) and the leading/invasive edge stroma (LE-TILs), and to evaluate TILs across BC subtypes with established risk factors and clinical characteristics in Kenyan women.

METHODS

Visual quantification of sTILs and LE-TILs were performed on Haematoxylin and eosin -stained pathologically confirmed BC cases based on the International TIL working group guidelines. Tissue Microarrays were constructed and stained with immunohistochemistry (IHC) for CD3, CD4, CD8, CD68, CD20, and FOXP3. Linear and logistic regression models were used to assess associations between risk factors and tumour features with IHC markers and total TILs, after adjusting for other covariates.

RESULTS

A total of 226 invasive BC cases were included. Overall, LE-TIL (mean = 27.9, SD = 24.5) proportions were significantly higher than sTIL (mean = 13.5, SD = 15.8). Both sTILs and LE- TILs were predominantly composed of CD3, CD8, and CD68. We found higher TILs to be associated with high KI67/high grade and aggressive tumour subtypes, although these associations varied by TIL locations. Older age at menarche (≥ 15 vs. < 15 years) was associated with higher CD3 (OR: 2.06, 95%CI:1.26-3.37), but only for the intra-tumour stroma.

CONCLUSION

The TIL enrichment in more aggressive BCs is similar to previously published data in other populations. The distinct associations of sTIL/LE-TIL measures with most examined factors highlight the importance of spatial TIL evaluations in future studies.

T-cell exhaustion signatures characterize the immune landscape and predict HCC prognosis via integrating single-cell RNA-seq and bulk RNA-sequencing

Background

Hepatocellular carcinoma (HCC), the third most prevalent cause of cancer-related death, is a frequent primary liver cancer with a high rate of morbidity and mortality. T-cell depletion (TEX) is a progressive decline in T-cell function due to continuous stimulation of the TCR in the presence of sustained antigen exposure. Numerous studies have shown that TEX plays an essential role in the antitumor immune process and is significantly associated with patient prognosis. Hence, it is important to gain insight into the potential role of T cell depletion in the tumor microenvironment. The purpose of this study was to develop a trustworthy TEX-based signature using single-cell RNA-seq (scRNA-seq) and high-throughput RNA sequencing, opening up new avenues for evaluating the prognosis and immunotherapeutic response of HCC patients.

Methods

The International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA) databases were used to download RNA-seq information for HCC patients. The 10x scRNA-seq. data of HCC were downloaded from GSE166635, and UMAP was used for clustering descending, and subgroup identification. TEX-related genes were identified by gene set variance analysis (GSVA) and weighted gene correlation network analysis (WGCNA). Afterward, we established a prognostic TEX signature using LASSO-Cox analysis. External validation was performed in the ICGC cohort. Immunotherapy response was assessed by the IMvigor210, GSE78220, GSE79671, and GSE91061cohorts. In addition, differences in mutational landscape and chemotherapy sensitivity between different risk groups were investigated. Finally, the differential expression of TEX genes was verified by qRT-PCR.

Result

11 TEX genes were thought to be highly predictive of the prognosis of HCC and substantially related to HCC prognosis. Patients in the low-risk group had a greater overall survival rate than those in the high-risk group, according to multivariate analysis, which also revealed that the model was an independent predictor of HCC. The predictive efficacy of columnar maps created from clinical features and risk scores was strong.

Conclusion

TEX signature and column line plots showed good predictive performance, providing a new perspective for assessing pre-immune efficacy, which will be useful for future precision immuno-oncology studies.

Defining the Emergence of New Immunotherapy Approaches in Breast Cancer: Role of Myeloid-Derived Suppressor Cells

Breast cancer (BC) continues to be the most diagnosed tumor in women and a very heterogeneous disease both inter- and intratumoral, mainly given by the variety of molecular profiles with different biological and clinical characteristics. Despite the advancements in early detection and therapeutic strategies, the survival rate is low in patients who develop metastatic disease. Therefore, it is mandatory to explore new approaches to achieve better responses. In this regard, immunotherapy arose as a promising alternative to conventional treatments due to its ability to modulate the immune system, which may play a dual role in this disease since the relationship between the immune system and BC cells depends on several factors: the tumor histology and size, as well as the involvement of lymph nodes, immune cells, and molecules that are part of the tumor microenvironment. Particularly, myeloid-derived suppressor cell (MDSC) expansion is one of the major immunosuppressive mechanisms used by breast tumors since it has been associated with worse clinical stage, metastatic burden, and poor efficacy of immunotherapies. This review focuses on the new immunotherapies in BC in the last five years. Additionally, the role of MDSC as a therapeutic target in breast cancer will be described.

Aggrephagy-related LncRNAs index: A predictor for HCC prognosis, immunotherapy efficacy, and chemosensitivity

BACKGROUND

Due to the complexity and heterogeneity of hepatocellular carcinoma, the existing clinical staging criterias are insufficient to accurately reflect the tumor microenvironment and predict the prognosis of HCC patients. Aggrephagy, as a type of selective autophagy, is associated with various phenotypes of malignant tumors.

OBJECTIVE

This study aimed to identify and validate a prognostic model based on aggrephagy-related LncRNAs to assess the prognosis and immunotherapeutic response of HCC patients.

METHODS

Based on the TCGA-LIHC cohort, aggrephagy-related LncRNAs were identified. Univariate Cox regression analysis and lasso and multivariate Cox regression were used to construct a risk-scoring system based on eight ARLs. CIBERSORT, ssGSEA, and other algorithms were used to evaluate and present the immune landscape of tumor microenvironment.

RESULTS

The high-risk group had a worse overall survival (OS) than the low-risk group. Patients in the high-risk group are more likely to benefit from immunotherapy because of their high infiltration level and high immune checkpoint expression.

CONCLUSION

The ARLs signature is a powerful predictor of prognosis for HCC patients, and the nomogram based on this model can help clinicians accurately determine the prognosis of HCC patients and screen for specific subgroups of patients who are more sensitive to immunotherapy and chemotherapy.

Increased expression of the immunoproteasome subunits PSMB8 and PSMB9 by cancer cells correlate with better outcomes for triple-negative breast cancers

Proteasome dependency is a feature of many cancers that can be targeted by proteasome inhibitors. For some cancer types, notably breast cancer and triple-negative breast cancer (TNBC), high mRNA expression of a modified form of the proteasome, called the immunoproteasome (ImP), correlates with better outcomes and higher expression of one ImP subunit was associated with slower tumor growth in a small patient cohort. While these findings are in line with an anti-tumoral role of the ImP in breast cancer, studies investigating ImP expression at the protein level in large patient cohorts are lacking. Furthermore, while ImPs can be found in both immune and non-immune cells, the cellular source is often ignored in correlative studies. In order to determine the impact of ImP expression on breast cancer outcomes, we assessed the protein expression and cellular source of the ImP subunits PSMB8 and PSMB9 in a cohort of 2070 patients. Our data show a clear correlation between high ImP expression and better outcomes, most notably for TNBC patients and when tumor cells rather than stromal or immune cells express PSMB8 or PSMB9. Our results therefore suggest that ImP expression by tumor cells could be used as prognostic markers of TNBC outcomes.

Shaping Up the Tumor Microenvironment: Extracellular Vesicles as Important Intermediaries in Building a Tumor-Supportive Cellular Network

A tumor is not just comprised of cancer cells but also a heterogeneous group of infiltrating and resident host cells, as well as their secreted factors that form the extracellular matrix [...].

Machine learning to construct sphingolipid metabolism genes signature to characterize the immune landscape and prognosis of patients with uveal melanoma

Background

Uveal melanoma (UVM) is the most common primary intraocular malignancy in adults and is highly metastatic, resulting in a poor patient prognosis. Sphingolipid metabolism plays an important role in tumor development, diagnosis, and prognosis. This study aimed to establish a reliable signature based on sphingolipid metabolism genes (SMGs), thus providing a new perspective for assessing immunotherapy response and prognosis in patients with UVM.

Methods

In this study, SMGs were used to classify UVM from the TCGA-UVM and GEO cohorts. Genes significantly associated with prognosis in UVM patients were screened using univariate cox regression analysis. The most significantly characterized genes were obtained by machine learning, and 4-SMGs prognosis signature was constructed by stepwise multifactorial cox. External validation was performed in the GSE84976 cohort. The level of immune infiltration of 4-SMGs in high- and low-risk patients was analyzed by platforms such as CIBERSORT. The prediction of 4-SMGs on immunotherapy and immune checkpoint blockade (ICB) response in UVM patients was assessed by ImmuCellAI and TIP portals.

Results

4-SMGs were considered to be strongly associated with the prognosis of UVM and were good predictors of UVM prognosis. Multivariate analysis found that the model was an independent predictor of UVM, with patients in the low-risk group having higher overall survival than those in the high-risk group. The nomogram constructed from clinical characteristics and risk scores had good prognostic power. The high-risk group showed better results when receiving immunotherapy.

Conclusions

4-SMGs signature and nomogram showed excellent predictive performance and provided a new perspective for assessing pre-immune efficacy, which will facilitate future precision immuno-oncology studies.

p53 Mutation as Plausible Predictor for Endocrine Resistance Therapy in Luminal Breast Cancer

Endocrine therapy resistance in Luminal Breast Cancer is a significant issue to be tackled, but currently, no specific biomarker could be used to anticipate this event. p53 mutation is widely known as one of Breast Cancer's most prominent genetic alterations. Its mutation could generate various effects in Estrogen Receptor and Progesterone Receptor molecular works, tangled in events leading to the aggravation of endocrine therapy resistance. Hence the possibility of p53 mutation utilization as an endocrine therapy resistance predictive biomarker is plausible. The purpose of this review is to explore the latest knowledge of p53 role in Estrogen Receptor and Progesterone Receptor molecular actions, thus aggravating the Endocrine Therapy resistance in Luminal Breast Cancer, from which we could define possibilities and limitations to utilize p53 as the predictive biomarker of endocrine therapy resistance in Luminal Breast Cancer.

Estrogen-induced immune changes within the normal mammary gland

Breast cancer (BCa) incidence increases following aberrant hormone exposure, which has been linked to direct effects on estrogen receptor (ER)⁺ mammary epithelium. While estrogen exposure during mammary involution has been shown to drive tumour growth via neutrophils, the potential for the ER + immune microenvironment to mediate part (in addition to mammary epithelial cells) of hormonally controlled BCa risk during normal development has not been assessed. We collected mammary tissue, lymph nodes and blood from tumour naïve mice treated with, oophorectomy, estrogen (17β estradiol) or Fulvestrant. Flow cytometry was used to examine the impact on the frequency of innate and adaptive immune cells. Oophorectomy and fulvestrant decreased the proportion of macrophages, particularly pro-tumour polarized M2 macrophages and neutrophils. Conversely, dendritic cells were increased by these therapies, as were eosinophils. Estrogen increased the proportion of M2 macrophages and to a lesser extent CD4-CD8- double negative and FoxP3⁺ regulatory T cells but decreased CD8 + T cells and B cells. Excluding eosinophils, these changes were restricted to the mammary tissue. This suggests that inhibiting estrogen action lowers the immune suppressive myeloid cells, increases in antigen presentation and eosinophil-mediated direct or indirect cytotoxic effects. In contrast, estrogen exposure, which drives BCa risk, increases the suppressive myeloid cells and reduces anti-tumour cytotoxic T cells. The impact of hormonal exposure on BCa risk, may in part be linked to its immune modulatory activity.

The cuproptosis-related signature predicts prognosis and indicates immune microenvironment in breast cancer

Breast cancer (BC) is the most diagnosed cancer in women. Cuproptosis is new regulated cell death, distinct from known death mechanisms and dependent on copper and mitochondrial respiration. However, the comprehensive relationship between cuproptosis and BC is still blank until now. In the present study, we acquired 13 cuproptosis-related regulators (CRRs) from the previous research and downloaded the RNA sequencing data of TCGA-BRCA from the UCSC XENA database. The 13 CRRs were all differently expressed between BC and normal samples. Using consensus clustering based on the five prognostic CRRs, BC patients were classified into two cuproptosis-clusters (C1 and C2). C2 had a significant survival advantage and higher immune infiltration levels than C1. According to the Cox and LASSO regression analyses, a novel cuproptosis-related prognostic signature was developed to predict the prognosis of BC effectively. The high- and low-risk groups were divided based on the risk scores. Kaplan-Meier survival analysis indicated that the high-risk group had shorter overall survival (OS) than the low-risk group in the training, test and entire cohorts. GSEA indicated that the immune-related pathways were significantly enriched in the low-risk group. According to the CIBERSORT and ESTIMATE analyses, patients in the high-risk group had higher infiltrating levels of antitumor lymphocyte cell subpopulations and higher immune score than the low-risk group. The typical immune checkpoints were all elevated in the high-risk group. Furthermore, the high-risk group showed a better immunotherapy response than the low-risk group based on the Tumor Immune Dysfunction and Exclusion (TIDE) and Immunophenoscore (IPS). In conclusion, we identified two cuproptosis-clusters with different prognoses using consensus clustering in BC. We also developed a cuproptosis-related prognostic signature and nomogram, which could indicate the outcome, the tumor immune microenvironment, as well as the response to immunotherapy.

Spatial interplay of tissue hypoxia and T-cell regulation in ductal carcinoma in situ

Hypoxia promotes aggressive tumor phenotypes and mediates the recruitment of suppressive T cells in invasive breast carcinomas. We investigated the role of hypoxia in relation to T-cell regulation in ductal carcinoma in situ (DCIS). We designed a deep learning system tailored for the tissue architecture complexity of DCIS, and compared pure DCIS cases with the synchronous DCIS and invasive components within invasive ductal carcinoma cases. Single-cell classification was applied in tandem with a new method for DCIS ductal segmentation in dual-stained CA9 and FOXP3, whole-tumor section digital pathology images. Pure DCIS typically has an intermediate level of colocalization of FOXP3+ and CA9+ cells, but in invasive carcinoma cases, the FOXP3+ (T-regulatory) cells may have relocated from the DCIS and into the invasive parts of the tumor, leading to high levels of colocalization in the invasive parts but low levels in the synchronous DCIS component. This may be due to invasive, hypoxic tumors evolving to recruit T-regulatory cells in order to evade immune predation. Our data support the notion that hypoxia promotes immune tolerance through recruitment of T-regulatory cells, and furthermore indicate a spatial pattern of relocalization of T-regulatory cells from DCIS to hypoxic tumor cells. Spatial colocalization of hypoxic and T-regulatory cells may be a key event and useful marker of DCIS progression.

Hub genes associated with immune cell infiltration in breast cancer, identified through bioinformatic analyses of multiple datasets

OBJECTIVE

The aim of this study was to identify hub genes associated with immune cell infiltration in breast cancer through bioinformatic analyses of multiple datasets.

METHODS

Nonparametric (NOISeq) and robust rank aggregation-ranked parametric (EdgeR) methods were used to assess robust differentially expressed genes across multiple datasets. Protein-protein interaction network, GO, KEGG enrichment, and sub-network analyses were performed to identify immune-associated hub genes in breast cancer. Immune cell infiltration was evaluated with the CIBERSORT, XCELL, and TIMER methods. The association between the hub gene-based risk signature and survival was determined through Kaplan-Meier survival analysis, multivariate Cox analysis, and a nomogram with external verification.

RESULTS

We identified 163 robust differentially expressed genes in breast cancer through applying both nonparametric and parametric methods to multiple GEO (n = 2,212) and TCGA (n = 1,045) datasets. Integrated bioinformatic analyses further identified 10 hub genes: CXCL10, CXCL9, CXCL11, SPP1, POSTN, MMP9, DPT, COL1A1, ADAMDEC1, and RGS1. The 10 hub-gene-based risk signature significantly correlated with the prognosis of patients with breast cancer. Moreover, these hub genes were strongly associated with the extent of infiltration of CD4+ T cells, CD8+ T cells, neutrophils, macrophages, and myeloid dendritic cells into breast tumors.

CONCLUSIONS

Integrated analyses of multiple databases led to the discovery of 10 robust hub genes that together may serve as a risk factor characteristic of the immune microenvironment in breast cancer.

A novel lactate metabolism-related signature predicts prognosis and tumor immune microenvironment of breast cancer

Background: Lactate, an intermediate product of glycolysis, has become an essential regulator of tumor maintenance, development, and metastasis. Lactate can drive tumors by changing the microenvironment of tumor cells. Because of lactate's important role in cancer, we aim to find a novel prognostic signature based on lactate metabolism-related genes (LMRGs) of breast cancer (BC). Methods: RNA-sequencing data and clinical information of BC were enrolled from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. We obtained LMRGs from the Molecular Signature Database v7.4 and articles, and then we compared candidate genes with TCGA data to get differential genes. Univariate analysis and most minor absolute shrinkage and selector operator (LASSO) Cox regression were employed to filter prognostic genes. A novel lactate metabolism-related risk signature was constructed using a multivariate Cox regression analysis. The signature was validated by time-dependent ROC curve analyses and Kaplan-Meier analyses in TCGA and GEO cohorts. Then, we further investigated in depth the function of the model's immune microenvironment. Results: We constructed a 3-LMRG-based risk signature. Kaplan-Meier curves confirmed that high-risk score subgroups had a worse prognosis in TCGA and GEO cohorts. Then a nomogram to predict the probability of survival for BC was constructed. We also performed Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway function analysis. The function analysis showed that the lactate metabolism-related signature was significantly related to immune response. A significant correlation was observed between prognostic LMRGs and tumor mutation burden, checkpoints, and immune cell infiltration. An mRNA-miRNA network was built to identify an miR-203a-3p/LDHD/LYRM7 regulatory axis in BC. Conclusion: In conclusion, we constructed a novel 3-LMRG signature and nomogram that can be used to predict the prognosis of BC patients. In addition, the signature is closely related to the immune microenvironment, which may provide new insight into future anticancer therapies.

Unusual Association of NF-κB Components in Tumor-Associated Macrophages (TAMs) Promotes HSPG2-Mediated Immune-Escaping Mechanism in Breast Cancer

The cellular heterogeneity of the tumor environment of breast cancer (BC) is extremely complex and includes different actors such as neoplastic, stromal, and immunosuppressive cells, which contribute to the chemical and mechanical modification of the environment surrounding the tumor-exasperating immune-escaping mechanisms. In addition to molecular signals that make the tumor microenvironment (TME) unacceptable for the penetrance of the immune system, the physical properties of tumoral extracellular matrix (tECM) also have carved out a fundamental role in the processes of the protection of the tumor niche. Tumor-associated macrophages (TAMs), with an M2 immunosuppressive phenotype, are important determinants for the establishment of a tumor phenotype excluded from T cells. NF-κB transcription factors orchestrate innate immunity and represent the common thread between inflammation and cancer. Many studies have focused on canonical activation of NF-κB; however, activation of non-canonical signaling predicts poor survival and resistance to therapy. In this scenario, we demonstrated the existence of an unusual association of NF-κB components in TAMs that determines the deposition of HSPG2 that affects the stiffness of tECM. These results highlight a new mechanism counterbalanced between physical factors and a new perspective of mechano-pathology to be targeted to counteract immune evasion in BC.

Triple-Negative Breast Cancer Analysis Based on Metabolic Gene Classification and Immunotherapy

Triple negative breast cancer (TNBC) has negative expression of ER, PR and HER-2. TNBC shows high histological grade and positive rate of lymph node metastasis, easy recurrence and distant metastasis. Molecular typing based on metabolic genes can reflect deeper characteristics of breast cancer and provide support for prognostic evaluation and individualized treatment. Metabolic subtypes of TNBC samples based on metabolic genes were determined by consensus clustering. CIBERSORT method was applied to evaluate the score distribution and differential expression of 22 immune cells in the TNBC samples. Linear discriminant analysis (LDA) established a subtype classification feature index. Kaplan-Meier (KM) and receiver operating characteristic (ROC) curves were generated to validate the performance of prognostic metabolic subtypes in different datasets. Finally, we used weighted correlation network analysis (WGCNA) to cluster the TCGA expression profile dataset and screen the co-expression modules of metabolic genes. Consensus clustering of the TCGA cohort/dataset obtained three metabolic subtypes (MC1, MC2, and MC3). The ROC analysis showed a high prognostic performance of the three clusters in different datasets. Specifically, MC1 had the optimal prognosis, MC3 had a poor prognosis, and the three metabolic subtypes had different prognosis. Consistently, the immune characteristic index established based on metabolic subtypes demonstrated that compared with the other two subtypes, MC1 had a higher IFNγ score, T cell lytic activity and lower angiogenesis score, T cell dysfunction and rejection score. TIDE analysis showed that MC1 patients were more likely to benefit from immunotherapy. MC1 patients were more sensitive to immune checkpoint inhibitors and traditional chemotherapy drugs Cisplatin, Paclitaxel, Embelin, and Sorafenib. Multiclass AUC based on RNASeq and GSE datasets were 0.85 and 0.85, respectively. Finally, based on co-expression network analysis, we screened 7 potential gene markers related to metabolic characteristic index, of which CLCA2, REEP6, SPDEF, and CRAT can be used to indicate breast cancer prognosis. Molecular classification related to TNBC metabolism was of great significance for comprehensive understanding of the molecular pathological characteristics of TNBC, contributing to the exploration of reliable markers for early diagnosis of TNBC and predicting metastasis and recurrence, improvement of the TNBC staging system, guiding individualized treatment.

Characterization of the Immune Microenvironment in Inflammatory Breast Cancer Using Multiplex Immunofluorescence

INTRODUCTION

Inflammatory breast cancer (IBC) is an aggressive form of breast cancer with a poorly characterized immune microenvironment.

METHODS

We used a five-colour multiplex immunofluorescence panel, including CD68, CD4, CD8, CD20, and FOXP3 for immune microenvironment profiling in 93 treatment-naïve IBC samples.

RESULTS

Lower grade tumours were characterized by decreased CD4+ cells but increased accumulation of FOXP3+ cells. Increased CD20+ cells correlated with better response to neoadjuvant chemotherapy and increased CD4+ cells infiltration correlated with better overall survival. Pairwise analysis revealed that both ER+ and triple-negative breast cancer were characterized by co-infiltration of CD20 + cells with CD68+ and CD4+ cells, whereas co-infiltration of CD8+ and CD68+ cells was only observed in HER2+ IBC. Co-infiltration of CD20+, CD8+, CD4+, and FOXP3+ cells, and co-existence of CD68+ with FOXP3+ cells correlated with better therapeutic responses, while resistant tumours were characterized by co-accumulation of CD4+, CD8+, FOXP3+, and CD68+ cells and co-expression of CD68+ and CD20+ cells. In a Cox regression model, response to therapy was the most significant factor associated with improved patient survival.

CONCLUSION

Those results reveal a complex unique pattern of distribution of immune cell subtypes in IBC and provide an important basis for detailed characterization of molecular pathways that govern the formation of IBC immune landscape and potential for immunotherapy.

A Pyroptosis-Related Gene Panel for Predicting the Prognosis and Immune Microenvironment of Cervical Cancer

Cervical cancer (CC) is one of the most common malignant tumors of the female reproductive system. And the immune system disorder in patients results in an increasing incidence rate and mortality rate. Pyroptosis is an immune system-related programmed cell death pathway that produces systemic inflammation by releasing pro-inflammatory intracellular components. However, the diagnostic significance of pyroptosis-related genes (PRGs) in CC is still unclear. Therefore, we identified 52 PRGs from the TCGA database and screened three Differentially Expressed Pyroptosis-Related Genes (DEPRGs) in the prognosis of cervical cancer: CHMP4C, GZMB, TNF. The least absolute shrinkage and selection operator (LASSO) regression analysis and multivariate COX regression analysis were then used to construct a gene panel based on the three prognostic DEPRGs. The patients were divided into high-and low-risk groups based on the median risk score of the panel. According to the Kaplan-Meier curve, there was a substantial difference in survival rates between the two groups, with the high-risk group’s survival rate being significantly lower than the low-risk group’s. The PCA and t-SNE analyses revealed that the panel was able to differentiate patients into high-and low-risk groups. The area under the ROC curve (AUC) shows that the prognostic panel has high sensitivity and specificity. The risk score could then be employed as an independent prognostic factor using univariate and multivariate COX regression analyses paired with clinical data. The analyses of GO and KEGG functional enrichment of differentially expressed genes (DEGs) in the high-and low-risk groups revealed that these genes were primarily engaged in immune response and inflammatory cell chemotaxis. To illustrate immune cell infiltration in CC patients further, we used ssGSEA to compare immune-related cells and immune pathway activation between the high-and low-risk groups. The link between three prognostic DEPRGs and immune-related cells was still being discussed after evaluating immune cell infiltration in the TCGA cohort with “CIBERSORT.” In addition, the GEPIA database and qRT-PCR analysis were used to verify the expression levels of prognostic DEPRGs. In conclusion, PRGs are critical in tumor immunity and can be utilized to predict the prognosis of CC.

Stromal oncostatin M cytokine promotes breast cancer progression by reprogramming the tumor microenvironment

The tumor microenvironment (TME) is reprogrammed by cancer cells and participates in all stages of tumor progression. The contribution of stromal cells to the reprogramming of the TME is not well understood. Here, we provide evidence of the role of the cytokine oncostatin M (OSM) as central node for multicellular interactions between immune and nonimmune stromal cells and the epithelial cancer cell compartment. OSM receptor (OSMR) deletion in a multistage breast cancer model halted tumor progression. We ascribed causality to the stromal function of the OSM axis by demonstrating reduced tumor burden of syngeneic tumors implanted in mice lacking OSMR. Single-cell and bioinformatic analysis of murine and human breast tumors revealed that OSM expression was restricted to myeloid cells, whereas OSMR was detected predominantly in fibroblasts and, to a lower extent, cancer cells. Myeloid-derived OSM reprogrammed fibroblasts to a more contractile and tumorigenic phenotype and elicited the secretion of VEGF and proinflammatory chemokines CXCL1 and CXCL16, leading to increased myeloid cell recruitment. Collectively, our data support the notion that the stromal OSM/OSMR axis reprograms the immune and nonimmune microenvironment and plays a key role in breast cancer progression.

Drug Metabolism for the Identification of Clinical Biomarkers in Breast Cancer

Breast cancer is classified into four major molecular subtypes, and is considered a heterogenous disease. The risk profiles and treatment of breast cancer differ according to these subtypes. Early detection dramatically improves the prospects of successful treatment, resulting in a reduction in overall mortality rates. However, almost 30% of women primarily diagnosed with the early-stage disease will eventually develop metastasis or resistance to chemotherapies. Immunotherapies are among the most promising cancer treatment options; however, long-term clinical benefit has only been observed in a small subset of responding patients. The current strategies for diagnosis and treatment rely heavily on histopathological examination and molecular diagnosis, disregarding the tumor microenvironment and microbiome involving cancer cells. In this review, we aim to praise the use of pharmacogenomics and pharmacomicrobiomics as a strategy to identify potential biomarkers for guiding and monitoring therapy in real-time. The finding of these biomarkers can be performed by studying the metabolism of drugs, more specifically, immunometabolism, and its relationship with the microbiome, without neglecting the information provided by genetics. A larger understanding of cancer biology has the potential to improve patient care, enable clinical decisions, and deliver personalized medicine.

Pyroptosis-related molecular classification and immune microenvironment infiltration in breast cancer: A novel therapeutic target

The underlying role of pyroptosis in breast cancer (BC) remains unknown. Herein, we investigated the correlations of 33 pyroptosis‐related genes (PRGs) with immune checkpoints and immune cell infiltrations in BC patients based on The Cancer Genome Atlas cohort (n = 996) and Gene Expression Omnibus cohort (n = 3,262). Enrichment analysis revealed that these PRGs mainly functioned in pyroptosis, inflammasomes and regulation of autophagy pathway. Four prognostic independent PRGs (CASP9, TIRAP, GSDMC and IL18) were identified. Then, cluster 1/2 was recognized using consensus clustering for these four PRGs. Patients from cluster 1 had a favourable prognosis and diverse immune cell infiltrations. A nomogram was developed based on age, TNM stage, tumour subtype and pyroptosis score. Patients with the high‐risk group exhibited worse 5‐year OS, and the result was consistent in the external cohort. Additionally, high‐risk group patients were associated with downregulated immune checkpoint expression. Further analysis suggested that the high‐risk group patients were associated with a higher IC50 of paclitaxel, doxorubicin, cisplatin, methotrexate and vinorelbine. In summarizing, the pyroptosis score‐based nomogram might serve as an independent prognostic predictor and could guide medication for chemotherapy. Additionally, it may bring novel insight into the regulation of tumour immune microenvironment in BC and help to achieve precision immunotherapy.

Overexpressed CMTM6 Improves Prognosis and Associated With Immune Infiltrates of Ovarian Cancer

Ovarian cancer (OV) is an epithelial malignancy that intrigues people for its high mortality and lack of efficient treatment. Chemokine-like factor (CKLF)–like MARVEL transmembrane domain containing 6 (CMTM6) can be observed in various cancers, but its part in OV remains little known. Hence, the prognostic value and underlying mechanism of CMTM6 in OV were preliminarily evaluated. Here, we determined that CMTM6 expression was higher than that in normal controls. However, the upregulation of CMTM6 was associated with better prognosis. GSEA results suggested that CMTM6 is involved in the immune-related and metabolism-related pathways. GO/KEGG analysis of CMTM6 coexpressed genes was performed to survey the possible regulatory roles of CMTM6 in OV. Subsequently, CMTM6 expression was positively correlated with the infiltration levels of immune cells and the expression of diverse immune cell marker sets. Importantly, CMTM6 may influence prognosis partially by regulating immune infiltration in OV. Last, copy number variations (CNVs) and DNA methylation might prompt the abnormal CMTM6 expression in OV. In conclusion, CMTM6 can serve as a novel prognostic biomarker in patients with OV.

Peripheral Blood Transcriptome in Breast Cancer Patients as a Source of Less Invasive Immune Biomarkers for Personalized Medicine, and Implications for Triple Negative Breast Cancer

Transcriptome studies of peripheral blood cells can advance our understanding of the systemic immune response to the presence of cancer and the mechanisms underlying cancer onset and progression. This enables the identification of novel minimally invasive immune biomarkers for early cancer detection and personalized cancer management and may bring forward new immunotherapy options. Recent blood gene expression analyses in breast cancer (BC) identified distinct patient subtypes that differed in the immune reaction to cancer and were distinct from the clinical BC subtypes, which are categorized based on expression of specific receptors on tumor cells. Introducing new BC subtypes based on peripheral blood gene expression profiles may be appropriate, since it may assist in BC prognosis, the identification of patients likely to benefit from immunotherapy, and treatment efficacy monitoring. Triple-negative breast cancer (TNBC) is an aggressive, heterogeneous, and difficult-to-treat disease, and identification of novel biomarkers for this BC is crucial for clinical decision-making. A few studies have reported TNBC-enriched blood transcriptional signatures, mostly related to strong inflammation and augmentation of altered immune signaling, that can differentiate TNBC from other classical BC subtypes and facilitate diagnosis. Future research is geared toward transitioning from expression signatures in unfractionated blood cells to those in immune cell subpopulations.

The role of stromal immune microenvironment in the progression of ductal carcinoma in situ (DCIS) to invasive breast cancer

Aim

The first aim of the study was to compare the scores and types of stromal immune cells in 30 patients with primary DCIS and in the same patients after invasive breast recurrence in order to assess possible differences in both during tumor progression. The second aim was to evaluate possible differences in stromal cells of 30 patients with primary DCIS before progression and in the control group of 11 DCIS patients without recurrence during long-term follow-up.

Material and methods

Evaluation of tumor-infiltrating lymphocytes (TILs) and immunohistochemical stains for immune cell markers CD4, CD8, CD20, CD138, FOXP3, CD163 and TGF beta was performed on the stroma of primary DCIS before progression, invasive breast cancer of the same patients after progression and DCIS without progression.

Results

The comparison of stromal cells in 30 patients with initial DCIS and its invasive recurrence revealed an increased level of CD20 + immune cells (median score 5% vs. 17%, respectively, p < 0.001) and CD163 + cells (median score 1% vs. 5%, respectively, p < 0.001) in invasive breast cancer. The comparison of stromal cells in 30 patients with initial DCIS before recurrence and the control group of 11 patients with DCIS without recurrence showed statistically significant difference for CD138 + cells, which were more prevalent in patients with worse prognosis (median score 0 vs. 2%, respectively, p < 0.001). No similar relationship was found for the other tested cells as well as for TGF-beta.

Conclusions

CD138 + immune cells that were more prevalent in patients with a worse prognosis should be explored in further studies to confirm or exclude their role as a potential biological marker of DCIS invasive recurrence.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13058-021-01494-9.

Vascularity and Dynamic Contrast-Enhanced Breast Magnetic Resonance Imaging

Angiogenesis is a key step in the initiation and progression of an invasive breast cancer. High microvessel density by morphological characterization predicts metastasis and poor survival in women with invasive breast cancers. However, morphologic characterization is subject to variability and only can evaluate a limited portion of an invasive breast cancer. Consequently, breast Magnetic Resonance Imaging (MRI) is currently being evaluated to assess vascularity. Recently, through the new field of radiomics, dynamic contrast enhanced (DCE)-MRI is being used to evaluate vascular density, vascular morphology, and detection of aggressive breast cancer biology. While DCE-MRI is a highly sensitive tool, there are specific features that limit computational evaluation of blood vessels. These include (1) DCE-MRI evaluates gadolinium contrast and does not directly evaluate biology, (2) the resolution of DCE-MRI is insufficient for imaging small blood vessels, and (3) DCE-MRI images are very difficult to co-register. Here we review computational approaches for detection and analysis of blood vessels in DCE-MRI images and present some of the strategies we have developed for co-registry of DCE-MRI images and early detection of vascularization.

Smart exosomes with lymph node homing and immune-amplifying capacities for enhanced immunotherapy of metastatic breast cancer

Tumor-draining lymph nodes (TDLNs) are the primary sites to initiate immune responses against cancer, as well as the origin of metastasis for most breast cancer cases. Reverting the immunosuppression microenvironment in TDLNs is critical to improving the outcome of the malignancy, though still a big technical challenge. In this study, a type of smart exosomes was developed in which the exosome surface was functionally engineered with CD62L (L-selectin, a gene for lymphocyte homing to lymph nodes) and OX40L (CD134L, a gene for effector T cell expansion and regulatory T cell [Treg] inhibition) by forced expression of the genes in the donor cells. Compared with control exosomes, the smart exosomes displayed strong TDLN homing capacity in the 4T1 syngeneic mouse model. Moreover, injection of the smart exosomes activated effector T cells and inhibited Treg induction, thereby amplifying the antitumor immune response and inhibiting tumor development. Together, the engineered smart exosomes provide a novel nanoplatform for TDLN-targeted delivery and cancer immunotherapy.

Monocytes secrete CXCL7 to promote breast cancer progression

Certain immune cells and inflammatory cytokines are essential components in the tumor microenvironment to promote breast cancer progression. To identify key immune players in the tumor microenvironment, we applied highly invasive MDA-MB-231 breast cancer cell lines to co-culture with human monocyte THP-1 cells and identified CXCL7 by cytokine array as one of the increasingly secreted cytokines by THP-1 cells. Further investigations indicated that upon co-culturing, breast cancer cells secreted CSF1 to induce expression and release of CXCL7 from monocytes, which in turn acted on cancer cells to promote FAK activation, MMP13 expression, migration, and invasion. In a xenograft mouse model, administration of CXCL7 antibodies significantly reduced abundance of M2 macrophages in tumor microenvironment, as well as decreased tumor growth and distant metastasis. Clinical investigation further suggested that high CXCL7 expression is correlated with breast cancer progression and poor overall survival of patients. Overall, our study unveils an important immune cytokine, CXCL7, which is secreted by tumor infiltrating monocytes, to stimulate cancer cell migration, invasion, and metastasis, contributing to the promotion of breast cancer progression.

Reconstituting Immune Surveillance in Breast Cancer: Molecular Pathophysiology and Current Immunotherapy Strategies

Over the past 50 years, breast cancer immunotherapy has emerged as an active field of research, generating novel, targeted treatments for the disease. Immunotherapies carry enormous potential to improve survival in breast cancer, particularly for the subtypes carrying the poorest prognoses. Here, we review the mechanisms by which cancer evades immune destruction as well as the history of breast cancer immunotherapies and recent developments, including clinical trials that have shaped the treatment of the disease with a focus on cell therapies, vaccines, checkpoint inhibitors, and oncolytic viruses.

Prognostic value of tumor-infiltrating lymphocytes in estrogen receptor-positive and human epidermal growth factor receptor 2-negative breast cancer

Tumor-infiltrating lymphocytes (TILs) are a significant prognostic factor in triple-negative breast cancer. However, the clinicopathological significance of TILs in estrogen receptor (ER)-positive and human epidermal growth factor receptor 2 (HER2)-negative breast cancer remains unclear. The purpose of the present study was to evaluate the role of TILs in the prognosis of ER-positive and HER2-negative breast cancer. A total of 65 consecutive patients with ER-positive and HER2-negative breast cancer were examined. TILs in stromal tissue (str-TILs) were graded using the International TILs Working Group criteria. The association between several clinicopathological factors and TIL grade were investigated, and the prognostic impact of TILs was compared between luminal A-like and luminal B-like breast cancer. A total of 51 patients (78.5%) had low-grade (0-10%), 11 (16.9%) had intermediate (10-40%) and 3 (4.6%) had high-grade (40-90%) str-TIL levels. There was a significant association between high levels of Ki67 expression and a high str-TIL count. Relapse-free survival was significantly worse in patients with luminal B-like cancer compared with that in patients with luminal A-like cancer. Patients with an intermediate or high str-TIL count had a better prognosis compared with those with a low str-TIL count. All patients with luminal B-like cancer and intermediate or high str-TIL levels developed no recurrence during follow-up. In conclusion, there was a significant correlation between high-grade str-TIL levels and high tumor cell proliferation rate, as well as high levels of Ki67 expression.

Effects of Molecular Iodine/Chemotherapy in the Immune Component of Breast Cancer Tumoral Microenvironment

Molecular iodine (I₂) induces apoptotic, antiangiogenic, and antiproliferative effects in breast cancer cells. Little is known about its effects on the tumor immune microenvironment. We studied the effect of oral (5 mg/day) I₂ supplementation alone (I₂) or together with conventional chemotherapy (Cht+I₂) on the immune component of breast cancer tumors from a previously published pilot study conducted in Mexico. RNA-seq, I₂ and Cht+I₂ samples showed significant increases in the expression of Th1 and Th17 pathways. Tumor immune composition determined by deconvolution analysis revealed significant increases in M0 macrophages and B lymphocytes in both I₂ groups. Real-time RT-PCR showed that I₂ tumors overexpress T-BET (p = 0.019) and interferon-gamma (IFNγ; p = 0.020) and silence tumor growth factor-beta (TGFβ; p = 0.049), whereas in Cht+I₂ tumors, GATA3 is silenced (p = 0.014). Preliminary methylation analysis shows that I₂ activates IFNγ gene promoter (by increasing its unmethylated form) and silences TGFβ in Cht+I₂. In conclusion, our data showed that I₂ supplements induce the activation of the immune response and that when combined with Cht, the Th1 pathways are stimulated. The molecular mechanisms involved in these responses are being analyzed, but preliminary data suggest that methylation/demethylation mechanisms could also participate.

Histamine in cancer immunology and immunotherapy. Current status and new perspectives

Cancer is the second leading cause of death globally and its incidence and mortality are rapidly increasing worldwide. The dynamic interaction of immune cells and tumor cells determines the clinical outcome of cancer. Immunotherapy comes to the forefront of cancer treatments, resulting in impressive and durable responses but only in a fraction of patients. Thus, understanding the characteristics and profiles of immune cells in the tumor microenvironment (TME) is a necessary step to move forward in the design of new immunomodulatory strategies that can boost the immune system to fight cancer. Histamine produces a complex and fine-tuned regulation of the phenotype and functions of the different immune cells, participating in multiple regulatory responses of the innate and adaptive immunity. Considering the important actions of histamine-producing immune cells in the TME, in this review we first address the most important immunomodulatory roles of histamine and histamine receptors in the context of cancer development and progression. In addition, this review highlights the current progress and foundational developments in the field of cancer immunotherapy in combination with histamine and pharmacological compounds targeting histamine receptors.

Quantitative Assessment of the Effects of IL-1ß -511 C>T Variant on Breast Cancer Risk: An Updated Meta-Analysis of 3331 Cases and 3609 Controls

OBJECTIVE

Growing evidence suggests that IL-1β -511C>T, as a functional variant, affects the risk of developing breast cancer (BC); however, the results have not been conclusive. This meta-analysis was conducted to estimate the link between this variant and BC risk.

METHODS

We retrieved available publications on IL-1β -511C>T polymorphism by conducting a comprehensive literature search on the Web of Science, MEDLINE, PubMed, Scopus, and Google scholar databases (last search on February 25, 2020).

RESULTS

The overall analysis indicates that IL-1β -511C>T polymorphism conferred an increased risk of BC under a recessive TT vs CT+CC model by 1.14-fold and showed protection against BC under an overdominant CT vs TT+CC genetic contrast model (odds ratio = 0.84). Stratified analysis based on ethnicity revealed the protective effect of this single-nucleotide polymorphism against BC risk in Caucasian patients.

CONCLUSION

Our data results provide a proof of concept for the association of IL-1β -511C>T with BC risk. Larger, well-designed population-based studies are needed to confirm these findings.

Immune-related biomarkers in triple-negative breast cancer

Breast cancer is a commonly diagnosed female cancer in the world. Triple-negative breast cancer (TNBC) is the most dangerous and biologically aggressive subtype in breast cancer which has a high mortality, high rates of relapse and poor prognosis, representing approximately 15-20% of breast cancers. TNBC has unique and special biological molecular characteristics and higher immunogenicity than other breast cancer types. On the basis of molecular features, TNBC is divided into different subtypes and gets various treatments. Especially, immunotherapy becomes a promising and effective treatment to TNBC. However, not all of the TNBC patients are sensitive to immunotherapy, the need of selecting the patients suitable for immunotherapy is imperative. In this review, we discussed recent discoveries about the immune-related factors of TNBC, including tumor-infiltrating lymphocytes (TILs), programmed death-ligand protein-1 (PD-L1), immune gene signatures, some other emerging biomarkers for immunotherapy effectivity and promising biomarkers for immunotherapy resistance. In addition, we summarized the features of these biomarkers contributing to predict the prognosis and effect of immunotherapy. We hope we can provide some helps or evidences to clinical immunotherapy and combined treatment for TNBC patients.

Dynamic contrast-enhanced breast MRI features correlate with invasive breast cancer angiogenesis

Angiogenesis is a critical component of breast cancer development, and identification of imaging-based angiogenesis assays has prognostic and treatment implications. We evaluated the association of semi-quantitative kinetic and radiomic breast cancer features on dynamic contrast-enhanced (DCE)-MRI with microvessel density (MVD), a marker for angiogenesis. Invasive breast cancer kinetic features (initial peak percent enhancement [PE], signal enhancement ratio [SER], functional tumor volume [FTV], and washout fraction [WF]), radiomics features (108 total features reflecting tumor morphology, signal intensity, and texture), and MVD (by histologic CD31 immunostaining) were measured in 27 patients (1/2016-7/2017). Lesions with high MVD levels demonstrated higher peak SER than lesions with low MVD (mean: 1.94 vs. 1.61, area under the receiver operating characteristic curve [AUC] = 0.79, p = 0.009) and higher WF (mean: 50.6% vs. 22.5%, AUC = 0.87, p = 0.001). Several radiomics texture features were also promising for predicting increased MVD (maximum AUC = 0.84, p = 0.002). Our study suggests DCE-MRI can non-invasively assess breast cancer angiogenesis, which could stratify biology and optimize treatments.

STAT3/NF-κB signalling disruption in M2 tumour-associated macrophages is a major target of PLGA nanocarriers/PD-L1 antibody immunomodulatory therapy in breast cancer

Background and Purpose

Inflammation associated with the tumour microenvironment (TME) is critical for cancer development, and immunotherapeutic strategies modulating the immune response in cancer have been crucial. In this study, a methotrexate‐loaded (MTX) poly(lactic‐co‐glycolic acid)‐based (PLGA) drug nanocarrier covered with polyethyleneimine (Pei) and hyaluronic acid (HA) was developed and combined with an PD‐L1 antibody to investigate anti‐cancer and immunomodulatory effects in breast cancer TME.

Experimental Approach

Naked or HA‐coated PeiPLGA‐MTX nanoparticles (NPs) were assessed on 4T1 breast cancer cells grown in culture and in a mouse model of orthotopic tumour growth. Tumours were evaluated by qRT‐PCR and immunohistochemistry. The cell death profile and cell migration were analysed in vitro in 4T1 cells. Polarization of murine macrophages (RAW cells) was also carried out.

Key Results

Naked or HA‐coated PeiPLGA‐MTX NPs used alone or combined with PD‐L1 antibody modified the tumourigenic course by TME immunomodulation, leading to reduction of primary tumour size and metastases. STAT3 and NF‐κB were the major genes downregulated by NPs. In tumor‐associated macrophages (TAM) such regulation switched M2 phenotype (CD163) towards M1 (CD68) and reduced levels of IL‐10, TGF‐β and CCL22. Moreover, malignant cells showed overexpression of FADD, APAF‐1, caspase‐3 and E‐cadherin, and decreased expression of Bcl‐2, MDR‐1, survivin, vimentin, CXCR4 and PD‐L1 after treatment with NPs.

Conclusion and Implications

NPs‐mediated STAT3/NF‐κB signalling axis suppression disrupted crosstalk between immune and malignant cells, reducing immunosuppression and critical pro‐tumour events. These findings provide a promising therapeutic approach capable of guiding the immune TME to suppress the development of breast cancer.

Gene expression patterns associated with tumor-infiltrating CD4+ and CD8+ T cells in invasive breast carcinomas

BACKGROUND

Breast carcinoma is one of the most common tumors in women. The immune microenvironment, especially T cell infiltration, is related to the occurrence and prognosis of breast carcinoma.

OBJECTIVE

This study investigated the gene expression patterns associated with tumor-infiltrating CD4+ and CD8+ T cells in invasive breast carcinomas.

METHODS

The gene expression data and corresponding clinical phenotype data from the Cancer Genome Atlas Breast Invasive Carcinoma (TCGA-BRCA) were downloaded. The stromal and immune score were calculated using ESTIMATE. The differentially expressed genes (DEGs) with a high vs. low stromal score and a high vs. low immune score were screened and then functionally enriched. The tumor-infiltrating immune cells were investigated using the Cibersort algorithm, and the CD4+ and CD8+ T cell-related genes were identified using a Spearman correlation test of infiltrating abundance with the DEGs. Moreover, the miRNA-mRNA pairs and lncRNA-miRNA pairs were predicted to construct the competing endogenous RNAs (ceRNA) network. Kaplan-Meier (K-M) survival curves were also plotted.

RESULTS

In total, 478 DEGs with a high vs. low stromal score and 796 DEGs with a high vs. low immune score were identified. In addition, 39 CD4+ T cell-related genes and 78 CD8+ T cell-related genes were identified; of these, 14 genes were significantly associated with the prognosis of BRCA patients. Moreover, for CD4+ T cell-related genes, the chr22-38_28785274-29006793.1-miR-34a/c-5p-CAPN6 axis was identified from the ceRNA network, whereas the chr22-38_28785274-29006793.1-miR-494-3p-SLC9A7 axis was identified for CD8+ T cell-related genes.

CONCLUSIONS

The chr22-38_28785274-29006793.1-miR-34a/c-5p-CAPN6 axis and the chr22-38_28785274-29006793.1-miR-494-3p-SLC9A7 axis might regulate cellular activities associated with CD4+ and CD8+ T cell infiltration, respectively, in BRCA.