Clinical Implications of Tumor-Infiltrating Immune Cells in Breast Cancer

Single-cell RNA sequencing reveals localized tumour ablation and intratumoural immunostimulant delivery potentiate T cell mediated tumour killing

Background

Metastatic breast cancer poses great challenge in cancer treatment. N‐dihydrogalactochitosan (GC) is a novel immunoadjuvant that stimulates systemic immune responses when administered intratumourally following local tumour ablation. A combination of photothermal therapy (PTT) and GC, referred to as localized ablative immunotherapy (LAIT), extended animal survival and generates an activated B cell phenotype in MMTV‐PyMT mouse mammary tumour microenvironment (TME). However, how T cell populations respond to LAIT remains to be elucidated.

Methods

Using depletion antibodies, we studied the contributions of CD8⁺ and CD4⁺ T cells to the therapeutic effect of LAIT. Using single‐cell RNA‐sequencing (scRNAseq), we analysed tumour‐infiltrating T cell heterogeneity and dissected their transcriptomes upon treatments of PTT, GC, and LAIT (PTT+GC).

Results

Loss of CD8⁺ T cells after LAIT abrogated the therapeutic benefits of LAIT. Ten days after treatment, proportions of CD8⁺ and CD4⁺ T cells in untreated TME were 19.2% and 23.0%, respectively. Upon LAIT, both proportions were increased to 25.5% and 36.2%, respectively. In particular, LAIT increased the proportions of naïve and memory cells from a resting state to an activated state. LAIT consistently induced the expression of co‐stimulatory molecules, type I IFN responsive genes, and a series of antitumor cytokines, Ifng, Tnf, Il1, and Il17 in CD8⁺ and CD4⁺ T cells. LAIT also induced immune checkpoints Pdcd1, Ctla4, and Lag3 expression, consistent with T cell activation. Relevant to clinical translation, LAIT also upregulated genes in CD8⁺ and CD4⁺ T cells that positively correlated with extended survival of breast cancer patients.

Conclusions

Overall, our results reveal that LAIT prompts immunological remodelling of T cells by inducing broad proinflammatory responses and inhibiting suppressive signalling to drive antitumour immunity.

CTHRC1 is a Potential Prognostic Biomarker and Correlated with Macrophage Infiltration in Breast Cancer

Background

Tumor immune cell infiltration is closely associated with the occurrence and development of tumors. Collagen triple helix repeats containing 1 (CTHRC1), a regulator of collagen expression and cell migration, is involved in the metastasis and invasion of tumors. However, the role of CTHRC1 in breast cancer remains unclear. This study aimed to investigate the prognostic value of CTHRC1, and further explore its association with immune infiltration in breast cancer.

Methods

CTHRC1 expression pattern and prognostic value were analyzed using ONCOMINE, PrognoScan, GEPIA, and Kaplan–Meier Plotter databases. We then detected CTHRC1 mRNA levels in breast cancer tissues and paired normal breast tissues by Q-PCR. Subsequently, the University of California Santa Cruz (UCSC) database was used to determine the methylation status of CTHRC1. Furthermore, CTHRC1 mutations were investigated using the Catalogue of Somatic mutations in Cancer (COSMIC) and cBioPortal databases. We also assessed the correlation between CTHRC1 expression and immune cell infiltration using TIMER. In addition, The relationship of CTHRC1 expression with the immune marker sets of various immune cells was evaluated using GEPIA and TIMER.

Results

CTHRC1 was highly expressed in a variety of tumors, including breast cancer. Elevated CTHRC1 expression was related to a poor prognosis. Notably, CTHRC1 expression was significantly associated with macrophage infiltration, especially the immune infiltration gene marker set of M2. Copy number variations, DNA mutations and methylation states might be potential mechanisms for regulating CTHRC1 expression. Protein digestion and absorption, human papillomavirus infection, ECM-receptor interaction, focal adhesion, and PI3K-Akt signaling pathways were identified as the potential CTHRC1-driven signaling pathways.

Conclusion

These findings suggest that CTHRC1 could be a promising immune-related biomarker for the treatment of breast cancer patients.

Potential Pro-Tumorigenic Effect of Bisphenol A in Breast Cancer via Altering the Tumor Microenvironment

Simple Summary

Bisphenol A (BPA) is primarily used to produce polycarbonate plastics, such as water bottles. Exposure to BPA has been shown to increase the growth of breast cancer cells that depend on estrogen for growth due to its ability to mimic estrogen. More recent studies have suggested that BPA also affects the cellular and non-cellular components that compose tumor microenvironments (TMEs), namely the environment around a tumor, thereby potentially promoting breast cancer growth via altering the TME. The TME plays an essential role in cancer development and promotion. Therefore, it is crucial to understand the effect of BPA on breast TMEs to assess its role in the risk of breast cancer adequately. This review examines the potential effects of BPA on immune cells, fibroblasts, extracellular matrices, and adipocytes to highlight their roles in mediating the carcinogenic effect of BPA, and thereby proposes considerations for the risk assessment of BPA exposure.

Abstract

BPA, a chemical used in the preparation of polycarbonate plastics, is an endocrine disruptor. Exposure to BPA has been suggested to be a risk factor for breast cancer because of its potential to induce estrogen receptor signaling in breast cancer cells. More recently, it has been recognized that BPA also binds to the G protein-coupled estrogen receptor and other nuclear receptors, in addition to estrogen receptors, and acts on immune cells, adipocytes, and fibroblasts, potentially modulating the TME. The TME significantly impacts the behavior of cancer cells. Therefore, understanding how BPA affects stromal components in breast cancer is imperative to adequately assess the association between exposure to BPA and the risk of breast cancer. This review examines the effects of BPA on stromal components of tumors to highlight their potential role in the carcinogenic effect of BPA. As a result, I propose considerations for the risk assessment of BPA exposure and studies needed to improve understanding of the TME-mediated, breast cancer-promoting effect of BPA.

Prognostic Characteristics of Immune-Related Genes and the Related Regulatory Axis in Patients With Stage N+M0 Breast Cancer

Breast cancer (BRCA) has the highest incidence rate among female tumours. The function of the immune system affects treatment efficacy and prognosis in patients with BRCA. However, the exact role of immune-related genes (IRGs) in stage N+M0 BRCA is unknown. We constructed a predictive risk scoring model with five IRGs (CDH1, FGFR3, INHBA, S100B, and SCG2) based on the clinical, mutation, and RNA sequencing data of individuals with stage N+M0 BRCA sourced from The Cancer Genome Atlas. Results from the Shandong Cancer Hospital and Institute validation cohort suggested that regardless of clinical stage, tumour size, or the number of lymph node metastases, this model was able to reliably discriminate low-risk patients from high-risk ones and assess the prognosis of patients with stage N+M0 BRCA, and low-risk patients could benefit more from immunotherapy than high-risk patients. In addition, significant inter-group variations in immunocyte infiltration and the tumour microenvironment were observed. Moreover, risk score and age were found to be independent factors in multivariate COX regression analysis, which influenced the outcome of patients with stage N+M0 BRCA. Based on the above findings, we plotted a prognostic nomogram. Finally, we constructed a lncRNA KCNQ1OT1-LINC00665-TUG1/miR-9-5p/CDH1 regulatory axis of the ceRNA network to explore the mechanism of BRCA progression. In summary, we conducted a systemic and extensive bioinformatics investigation and established an IRG-based prognostic scoring model. Finally, we constructed a ceRNA regulatory axis that might play a significant role in BRCA development. More research is required to confirm this result. Scoring system-based patient grouping can help predict the outcome of patients with stage N+M0 BRCA more effectively and determine their sensitivity to immunotherapies, which will aid the development of personalised therapeutic strategies and inspire the research and development of novel medications.

Unraveling the mechanism of alkaloids from Sophora alopecuroides Linn combined with immune checkpoint blockade in the treatment of non-small cell lung cancer based on systems pharmacology

Quinolizidine alkaloids, as essential active ingredients extracted from Sophora alopecuroides Linn (SAL), have been proven to be pharmacologically active in a variety of cancers including non-small cell lung cancer (NSCLC). However, whether these alkaloids have substantial benefits in combination with immune checkpoint blockade (ICB) for the treatment of NSCLC is unknown. Here, we explore the potential of these alkaloids in combination with ICB therapy based on a systems pharmacology and bioinformatics approach. We found that 37 alkaloids in SAL have highly similar characteristics in the molecular skeleton, pharmacological properties, and targets. The expression of targets of these alkaloids are significantly correlated with the infiltration level of tumor infiltrating lymphocytes and the expression levels of multiple immune checkpoints in NSCLC. They share similar molecular mechanisms in antitumor immunity. Sophocarpine (Sop) is one of the most representative constituents of these alkaloids. We demonstrated that the Sop promotes PD-L1 expression to improve the effects of PD-L1 blockade treatment via the ADORA1-ATF3 axis. In conclusion, our study identified these alkaloids as promising candidates for the treatment of NSCLC, either alone or in combination with ICB, with potential value for drug development and may provide a promising strategy for improving the survival of NSCLC patients.

Prognostic value of tumor-infiltrating CD163+macrophage in patients with metastatic gastric cancer undergoing multidisciplinary treatment

BACKGROUND

The multidisciplinary treatment including induction chemotherapy plus conversion surgery (CS) has attracted attention as a new strategy to improve the outcome of metastatic gastric cancer (MGC). However, it is unclear which patients achieve a good response to chemotherapy and successful CS. Tumor-infiltrating immune cells (TIICs) have been reported to be both prognostic and predictive biomarkers not only in immunotherapy but also in chemotherapy in many cancer types. However, there have been no reports on the usefulness of TIICs as biomarkers in conversion surgery for MGC. The aim of the present study was to evaluate the association between the TIICs and treatment outcome for the multidisciplinary treatment in MGC.

METHODS

We retrospectively analyzed 68 MGC patients who received docetaxel plus cisplatin plus S-1 (DCS) therapy between April 2006 and March 2019 in our institute. The number of tumor-infiltrating CD4+, CD8+, Foxp3+lymphocytes, CD68+, CD163+macrophages in pre-treatment endoscopic biopsy samples were evaluated to investigate their predictive value for multidisciplinary treatment.

RESULTS

Fifty patients underwent CS following DCS therapy (CS group), whereas 18 patients underwent DCS therapy alone (non-CS group). The median survival time (MST) of CS group was 33.3 months, which was significantly longer than the MST of 9.0 months in non-CS group (p < 0.01). The number of CD163+macrophages was extracted as an independent prognostic factor for overall survival in all patients. There were more cases of high infiltration of CD163+macrophages in non-CS group than in CS group. Furthermore, in CS group, pathological responders to DCS therapy showed low infiltration of CD163+ macrophages, and high infiltration of CD8+lymphocyte. CD163 low group showed a significant prolonged survival compared with CD163 high group in patients who underwent CS (p = 0.02).

CONCLUSIONS

The pre-treatment CD163+macrophages infiltration would be a pivotal biomarker for predicting prognosis and pathological response to multidisciplinary treatment among TIICs in MGC. Thus, for patients with low CD163+macrophage infiltration in pre-treatment biopsy sample, diagnostic imaging should be performed frequently during chemotherapy to avoid missing the optimal timing for CS, and CS should be aggressively considered as a treatment option if curative resection is deemed feasible.

Immune cell infiltration and immunotherapy in hepatocellular carcinoma

Hepatocellular carcinoma is a highly malignant tumor and patients yield limited benefits from the existing treatments. The application of immune checkpoint inhibitors is promising but the results described in the literature are not favorable. It is therefore urgent to systematically analyze the immune microenvironment of HCC and screen the population best suited for the application of immune checkpoint inhibitors to provide a basis for clinical treatment. In this study, we collected The Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC)-related data sets to evaluate the immune microenvironment and immune cell infiltration (ICI) in HCC. Three independent ICI subtypes showing significant differences in survival were identified. Further, TCGA-LIHC immunophenoscore (IPS) was used to identify the differentially expressed genes between high- and low-IPS in HCC, so as to identify the immune gene subtypes in HCC tumors. The ICI score model for HCC was constructed, whereby we divided HCC samples into high- and low-score groups based on the median ICI score. The differences between these groups in genomic mutation load and immunotherapy benefit in HCC were examined in detail to provide theoretical support for accurate immunotherapy strategy in HCC. Finally, four genes were screened, which could accurately predict the subtype based on the tumor immune infiltration score. The findings may provide a basis and simplify the process for screening clinical drugs suitable for relevant subgroups.

Effector memory cytotoxic CD3+/CD8+/CD45RO+ T cells are predictive of good survival and a lower risk of recurrence in triple-negative breast cancer

Triple-negative breast cancer (TNBC) with high tumour-infiltrating lymphocytes (TILs) has been associated with a promising prognosis. To better understand the prognostic value of immune cell subtypes in TNBC, we characterised TILs and the interaction between tumour cells and immune cell subtypes. A total of 145 breast cancer tissues were stained by multiplex immunofluorescence (mIF), including panel 1 (PD-L1, PD-1, CD3, CD8, CD68 and CK) and panel 2 (Foxp3, Granzyme B, CD45RO, CD3, CD8 and CK). Phenotypes were analysed and quantified by pathologists using InForm software. We found that in the ER-negative (ER <1% and HER2-negative) group and the ER/PR-low positive (ER 1-9% and HER2-negative) group, 11.2% and 7.1% of patients were PD-L1⁺ by the tumour cell score, 29.0% and 28.6% were PD-L1⁺ by the modified immune cell score and 30.8% and 32.1% were PD-L1⁺ by the combined positive score. We combined ER-negative and ER/PR-low positive cases for the survival analysis since a 10% cut-off is often used in clinical practice for therapeutic purposes. The densities of PD-L1⁺ tumour cells (HR: 0.366, 95% CI: 0.138-0.970; p = 0.043) within the tumour compartment and CD3⁺ immune cells in the total area (tumour and stromal compartments combined) (HR: 0.213, 95% CI: 0.070-0.642; p = 0.006) were favourable prognostic biomarkers for overall survival (OS) in TNBC. The density of effector/memory cytotoxic T cells (CD3⁺CD8⁺CD45RO⁺) in the tumour compartment was an independent prognostic biomarker for OS (HR: 0.232, 95% CI: 0.086-0.628; p = 0.004) and DFS (HR: 0.183, 95% CI: 0.1301-0.744; p = 0.009) in TNBC. Interestingly, spatial data suggested that patients with a higher density of PD-L1⁺ tumour cells had shorter cell-cell distances from tumour cells to cytotoxic T cells (p < 0.01). In conclusion, we found that phenotyping tumour immune cells by mIF is highly informative in understanding the immune microenvironment in TNBC. PD-L1⁺ tumour cells, total T cells and effector/memory cytotoxic T cells are promising prognostic biomarkers in TNBC.

Investigating the Prognostic Relevance of Tumor Immune Microenvironment and Immune Gene Assembly in Breast Carcinoma Subtypes

We hypothesized that different BC subtypes are characterized by spatially distinct tumor immune microenvironment (TIME) and that immune gene assembly of metastatic (Met) and non-metastatic (Ctrl) BCs vary across subtypes. Peritumoral, stromal and intratumoral TIL was assessed on 309 BC cases. Hot, cold and immune-excluded groups were defined, and the prognostic role of this classification was assessed. CD4+/CD8+ positivity was analyzed in 75 cases in four systematically predefined tumor regions. Immune gene expression of Met and Ctrl HER2-negative BCs was compared by using NanoString nCounter technology. The amount of TIL infiltration varied greatly within all BC subtypes. Two-third of the cases were cold tumors with no significant survival difference compared to hot tumors. A lower CD4+/CD8+ ratio at the stromal internal tumor region was significantly associated with longer distant metastasis-free survival. The differentially expressed immune genes between Met and Ctrl varied across the studied BC subtypes with TNBC showing distinct features from the luminal subtypes. The TIME is characterized by a considerable heterogeneity; however, low level of TILs does not equate to disease progression. The differences in immune gene expression observed between Met and Ctrl breast carcinomas call attention to the important role of altered immune function in BC progression.

Multifunctional Role of Lipids in Modulating the Tumorigenic Properties of 4T1 Breast Cancer Cells

Tumor growth and progression are linked to an altered lipid metabolism in the tumor microenvironment (TME), including tumor cells and tumor-associated macrophages (TAMs). A growing number of lipid metabolism targeting drugs have shown efficacy in anti-tumor therapy. In addition, exogenously applied lipids and lipid analogues have demonstrated anti-tumor activities in several cancers, including breast cancer. In this study, we investigated the anti-tumor efficacies of the natural lipids palmitic acid (PA), sphingomyelin (SM), ceramide (Cer) and docosahexaenoic acid (DHA) on breast cancer cells. All tested lipids reduced the malignancy of breast cancer cells in vitro by impairing cell proliferation, migration and invasiveness. PA showed superior anti-tumor properties, as it additionally impaired cancer cell viability by inducing apoptosis, without affecting healthy cells. Co-culture experiments further demonstrated that Cer and PA reduced the immunosuppressive phenotype of M2 macrophages and the M2 macrophage-promoted the epithelial–mesenchymal transition (EMT) and migration of breast cancer cells. At the molecular level, this coincided with the up-regulation of E-cadherin. Our results highlight a powerful role for exogenously applied PA and Cer in reducing breast cancer tumorigenicity by simultaneously targeting cancer cells and M2 macrophages. Our findings support the notion that lipids represent alternative biocompatible therapeutic agents for breast cancer.

Differential Survival and Therapy Benefit of Patients with Breast Cancer Are Characterized by Distinct Epithelial and Immune Cell Microenvironments

PURPOSE

Extensive work in preclinical models has shown that microenvironmental cells influence many aspects of cancer cell behavior, including metastatic potential and their sensitivity to therapeutics. In the human setting, this behavior is mainly correlated with the presence of immune cells. Here, in addition to T cells, B cells, macrophages, and mast cells, we identified the relevance of nonimmune cell types for breast cancer survival and therapy benefit, including fibroblasts, myoepithelial cells, muscle cells, endothelial cells, and seven distinct epithelial cell types.

EXPERIMENTAL DESIGN

Using single-cell sequencing data, we generated reference profiles for all these cell types. We used these reference profiles in deconvolution algorithms to optimally detangle the cellular composition of more than 3,500 primary breast tumors of patients that were enrolled in the SCAN-B and MATADOR clinical trials, and for which bulk mRNA sequencing data were available.

RESULTS

This large data set enables us to identify and subsequently validate the cellular composition of microenvironments that distinguish differential survival and treatment benefit for different treatment regimens in patients with primary breast cancer. In addition to immune cells, we have identified that survival and therapy benefit are characterized by various contributions of distinct epithelial cell types.

CONCLUSIONS

From our study, we conclude that differential survival and therapy benefit of patients with breast cancer are characterized by distinct microenvironments that include specific populations of immune and epithelial cells.

Doxorubicin sensitizes breast cancer cells to natural killer cells in connection with increased Fas receptors

Breast cancer (BC) is the most common cancer in women. Although standard treatments are successful in patients with BC diagnosed at an early stage, an alternative treatment is required for patients with advanced-stage disease who do not respond to these treatments. The concept of using chemotherapy to sensitize cancer cells to become susceptible to immunotherapy was recently introduced and may be used as an alternative treatment for BC. The chemotherapeutic drug doxorubicin has been reported to sensitize cancer cells; however, the efficacy to sensitize the solid spheroids, in addition to its underlying mechanism regarding how doxorubicin sensitizes BC, has not previously been explored. In the present study, the effectiveness of a combined treatment of doxorubicin and natural killer-92 (NK-92) cells against BC in either 2D or 3D spheroid models, and its association with Fas receptor (FasR) expression, was demonstrated. The BC (MCF7) cell line expressing a higher level of FasR was more sensitive to NK-92 cell killing than the MDA-MB-231 cell line, which expressed a lower level of FasR. A sublethal dose of doxorubicin caused a significant improvement in NK cytotoxicity. Concordantly, a significant reduction in cell viability was observed in the doxorubicin-treated MCF7 spheroids. Notably, flow cytometric analysis revealed significantly increased FasR expression in the MCF7 cells, suggesting the underlying sensitization mechanism of doxorubicin in BC was related to the FasR upregulation. The present findings supported the use of combined doxorubicin and NK immunotherapy in BC treatment.

Our evolving understanding of how 27-hydroxycholesterol influences cancer

Cholesterol has been implicated in the pathophysiology and progression of several cancers now, although the mechanisms by which it influences cancer biology are just emerging. Two likely contributing mechanisms are the ability for cholesterol to directly regulate signaling molecules within the membrane, and certain metabolites acting as signaling molecules. One such metabolite is the oxysterol 27-hydroxycholesterol (27HC), which is a primary metabolite of cholesterol synthesized by the enzyme Cytochrome P450 27A1 (CYP27A1). Physiologically, 27HC is involved in the regulation of cholesterol homeostasis and contributes to cholesterol efflux through liver X receptor (LXR) and inhibition of de novo cholesterol synthesis through the insulin-induced proteins (INSIGs). 27HC is also a selective modulator of the estrogen receptors. An increasing number of studies have identified its importance in cancer progression of various origins, especially in breast cancer. In this review, we discuss the physiological roles of 27HC targeting these two nuclear receptors and the subsequent contribution to cancer progression. We describe how 27HC promotes tumor growth directly through cancer-intrinsic factors, and indirectly through its immunomodulatory roles which lead to decreased immune surveillance and increased tumor invasion. This review underscores the importance of the cholesterol metabolic pathway in cancer progression and the potential therapeutic utility of targeting this metabolic pathway.

Five hypoxia and immunity related genes as potential biomarkers for the prognosis of osteosarcoma

Osteosarcoma accounts for a frequently occurring cancer of the primary skeletal system. In osteosarcoma cells, a hypoxic microenvironment is commonly observed that drives tumor growth, progression, and heterogeneity. Hypoxia and tumor-infiltrating immune cells might be closely related to the prognosis of osteosarcoma. In this study, we aimed to determine the biomarkers and therapeutic targets related to hypoxia and immunity through bioinformatics methods to improve the clinical prognosis of patients. We downloaded the gene expression data of osteosarcoma samples and normal samples in the UCSC Xena database and GTEx database, respectively, and downloaded the validation dataset (GSE21257) in the GEO database. Subsequently, we performed GO enrichment analysis and KEGG pathway enrichment analysis on the data of the extracted osteosarcoma hypoxia-related genes. Through univariate COX regression analysis, lasso regression analysis, multivariate COX regression analysis, etc., we established a predictive model for the prognosis of osteosarcoma. Five genes, including ST3GAL4, TRIM8, STC2, TRPS1, and FAM207A, were found by screening. In particular, we analyzed the immune cell composition of each gene based on the five genes through the CIBERSORT algorithm and verified each gene at the cell and tissue level. Our findings are valuable for the clinical diagnosis and treatment of this disease.

Breast Cancer Classification from Ultrasound Images Using Probability-Based Optimal Deep Learning Feature Fusion

After lung cancer, breast cancer is the second leading cause of death in women. If breast cancer is detected early, mortality rates in women can be reduced. Because manual breast cancer diagnosis takes a long time, an automated system is required for early cancer detection. This paper proposes a new framework for breast cancer classification from ultrasound images that employs deep learning and the fusion of the best selected features. The proposed framework is divided into five major steps: (i) data augmentation is performed to increase the size of the original dataset for better learning of Convolutional Neural Network (CNN) models; (ii) a pre-trained DarkNet-53 model is considered and the output layer is modified based on the augmented dataset classes; (iii) the modified model is trained using transfer learning and features are extracted from the global average pooling layer; (iv) the best features are selected using two improved optimization algorithms known as reformed differential evaluation (RDE) and reformed gray wolf (RGW); and (v) the best selected features are fused using a new probability-based serial approach and classified using machine learning algorithms. The experiment was conducted on an augmented Breast Ultrasound Images (BUSI) dataset, and the best accuracy was 99.1%. When compared with recent techniques, the proposed framework outperforms them.

Identification of key tumor stroma-associated transcriptional signatures correlated with survival prognosis and tumor progression in breast cancer

BACKGROUND

The aberrant expression of stromal gene signatures in breast cancer has been widely studied. However, the association of stromal gene signatures with tumor immunity, progression, and clinical outcomes remains lacking.

METHODS

Based on eight breast tumor stroma (BTS) transcriptomics datasets, we identified differentially expressed genes (DEGs) between BTS and normal breast stroma. Based on the DEGs, we identified dysregulated pathways and prognostic hub genes, hub oncogenes, hub protein kinases, and other key marker genes associated with breast cancer. Moreover, we compared the enrichment levels of stromal and immune signatures between breast cancer patients with bad and good clinical outcomes. We also investigated the association between tumor stroma-related genes and breast cancer progression.

RESULTS

The DEGs included 782 upregulated and 276 downregulated genes in BTS versus normal breast stroma. The pathways significantly associated with the DEGs included cytokine-cytokine receptor interaction, chemokine signaling, T cell receptor signaling, cell adhesion molecules, focal adhesion, and extracellular matrix-receptor interaction. Protein-protein interaction network analysis identified the stromal hub genes with prognostic value in breast cancer, including two oncogenes (COL1A1 and IL21R), two protein kinases encoding genes (PRKACA and CSK), and a growth factor encoding gene (PLAU). Moreover, we observed that the patients with bad clinical outcomes were less enriched in stromal and antitumor immune signatures (CD8 + T cells and tumor-infiltrating lymphocytes) but more enriched in tumor cells and immunosuppressive signatures (MDSCs and CD4 + regulatory T cells) compared with the patients with good clinical outcomes. The ratios of CD8 + /CD4 + regulatory T cells were lower in the patients with bad clinical outcomes. Furthermore, we identified the tumor stroma-related genes, including MCM4, SPECC1, IMPA2, and AGO2, which were gradually upregulated through grade I, II, and III breast cancers. In contrast, COL14A1, ESR1, SLIT2, IGF1, CH25H, PRR5L, ABCA6, CEP126, IGDCC4, LHFP, MFAP3, PCSK5, RAB37, RBMS3, SETBP1, and TSPAN11 were gradually downregulated through grade I, II, and III breast cancers. It suggests that the expression of these stromal genes has an association with the progression of breast cancers. These progression-associated genes also displayed an expression association with recurrence-free survival in breast cancer patients.

CONCLUSIONS

This study identified tumor stroma-associated biomarkers correlated with deregulated pathways, tumor immunity, tumor progression, and clinical outcomes in breast cancer. Our findings provide new insights into the pathogenesis of breast cancer.

Hydroxysteroid 17-Beta Dehydrogenase 6 Is a Prognostic Biomarker and Correlates with Immune Infiltrates in Hepatocellular Carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is a common malignancy worldwide with poor outcomes. Therefore, it is important to identify a valuable prognostic biomarker for HCC. The present study aimed to identify novel prognostic biomarkers for HCC and evaluate the potential role of hub genes in HCC.

METHODS

Weighted gene co-expression network analysis and protein-protein interaction analysis were performed to identify important potential prognostic genes. The expression of hub genes was confirmed by the GEPIA, Oncomine, UALCAN, and HPA database. Furthermore, survival analysis of hub genes was performed using the Kaplan-Meier plotter database. Finally, we investigated the association between hub genes and immune factors in HCC through GSEA, the TIMER, and TISIDB database.

RESULTS

HSD17B6 expression was significantly lower in HCC than in normal tissues. Low HSD17B6 expression is associated with poorer overall survival and progression-free survival in HCC patients, particularly at medium disease stages (stage II and III or grade III). HSD17B6 showed a strong correlation with tumor-infiltrating B cells, CD4 + and CD8 + T cells, macrophages, neutrophils, and dendritic cells. Somatic copy number alteration might be the main cause of the negative correlation between HSD17B6 expression and immune infiltration. HSD17B6 expression in HCC negatively correlated with the expression of several immune cell markers, including exhausted T cell markers, PD-1 and CTLA-4, suggesting its role in regulating tumor immunity.

CONCLUSIONS

HSD17B6 is a potential prognostic biomarker that determines cancer progression and is correlated with tumor immune cells infiltration in HCC.

Leptin Receptor Overlapping Transcript (LEPROT) Is Associated with the Tumor Microenvironment and a Prognostic Predictor in Pan-Cancer

Background

Leptin receptor overlapping transcript (LEPROT) is reported to be involved in metabolism regulation and energy balance as well as molecular signaling of breast cancer and osteosarcoma. LEPROT is expressed in various tissue and is suggested to be involved in cancer developments but with contradictory roles. The comprehensive knowledge of the effects of LEPROT on cancer development and progression across pan-cancer is still missing.

Methods

The expressions of LEPROT in cancers were compared with corresponding normal tissues across pan-cancer types. The relationships between expression and methylation of LEPROT were then demonstrated. The correlations of LEPROT with the tumor microenvironment (TME), including immune checkpoints, tumor immune cells infiltration (TII), and cancer-associated fibroblasts (CAFs), were also investigated. Co-expression analyses and functional enrichments were conducted to suggest the most relevant genes and the mechanisms of the effects in cancers for LEPROT. Finally, the correlations of LEPROT with patient survival and immunotherapy response were explored.

Results

LEPROT expression was found to be significantly aberrant in 15/19 (78.9%) cancers compared with corresponding normal tissues; LEPROT was downregulated in 12 cancers and upregulated in three cancers. LEPROT expressions were overall negatively correlated with its methylation alterations. Moreover, LEPROT was profoundly correlated with the TME, including immune checkpoints, TIIs, and CAFs. According to co-expression analyses and functional enrichments, the interactions of LEPROT with the TME may be mediated by the interleukin six signal transducer/the Janus kinase/signal transducers and activators of the transcription signaling pathway. Prognostic values may exist for LEPROT to predict patient survival and immunotherapy response in a context-dependent way.

Conclusions

LEPROT affects cancer development by interfering with the TME and regulating inflammatory or immune signals. LEPROT may also serve as a potential prognostic marker or a target in cancer therapy. This is the first study to investigate the roles of LEPROT across pan-cancer.

Bioinformatic Analysis of Immune Significance of RYR2 Mutation in Breast Cancer

BACKGROUND

Currently, immunotherapy is widely used for breast cancer (BC) patients, and tumor mutation burden (TMB) is regarded as a valuable independent predictor of response to immunotherapy. However, specific gene mutations and their relationship with TMB and tumor-infiltrating immune cells in BC are not fully understood.

METHODS

Comprehensive bioinformatic analyses were performed using data from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) datasets. Survival curves were analyzed via Kaplan-Meier analysis. Univariate and multivariate Cox regression analyses were used for prognosis analysis. Gene set enrichment analysis (GSEA) was performed to explore regulatory mechanisms and functions. The CIBERSORT algorithm was used to calculate the tumor-infiltrating immune cell fractions.

RESULTS

We analyzed somatic mutation data of BC from TCGA and ICGC datasets and found that 19 frequently mutated genes were reported in both cohorts, namely, SPTA1, TTN, MUC17, MAP3K1, CDH1, FAT3, SYNE1, FLG, HMCN1, RYR2 (ryanodine receptor 2), GATA3, MUC4, PIK3CA, KMT2C, TP53, PTEN, ZFHX4, MUC16, and USH2A. Among them, we observed that RYR2 mutation was significantly associated with higher TMB and better clinical prognosis. Moreover, GSEA revealed that RYR2 mutation-enriched signaling pathways were related to immune-associated pathways. Furthermore, based on the CIBERSORT algorithm, we found that RYR2 mutation enhanced the antitumor immune response by enriching CD8+ T cells, activated memory CD4+ T cells, and M1 macrophages.

CONCLUSION

RYR2 is frequently mutated in BC, and its mutation is related to increased TMB and promotes antitumor immunity; thus, RYR2 may serve as a valuable biomarker to predict the immune response.

Prognostic impact of tertiary lymphoid structures in breast cancer prognosis: a systematic review and meta-analysis

BACKGROUND

Tertiary lymphoid structures (TLSs), organizationally resemble lymph nodes, are frequently present in breast cancer (BCa). It is usually, but not always, associated with a positive prognosis or immunotherapy response in cancer patients. This meta-analysis was performed to assess the prognostic and clinical impact of TLSs in BCa.

METHODS

We conducted a systematic search in PubMed, Embase, Cochrane Library, Web of Science, China National Knowledge Infrastructure, and WanFang Database to obtain eligible research data up to May 30, 2021. This meta-analysis is focusing on the studies evaluated the prognostic value of TLSs and the associated clinicopathologic indicators, related gene expression and survival. STATA software 16.0 software was used to assess the prognostic significance and clinical impact of TLSs.

RESULTS

Nine studies involved with 2281 cases were incorporated in this meta-analysis, in which four of them evaluated the prognostic value of TLSs. There are 6 studies assessed the relationship of TLSs and 4 studies investigated the clinicopathologic parameters as well as the key gene expression, respectively. The results showed the presence of TLSs were predicting a better OS (HR = 0.61, 95% CI: 0.51-0.73, p < 0.001) and DFS (HR = 0.40, 95% CI: 0.17-0.93, p < 0.001) of BCa patients. It also revealed that the presence of TLSs was significantly correlated with tumor differentiation (p < 0.001), pTNM stage (p < 0.001), lymph node metastasis (p < 0.001), and TILs density (p < 0.001) of BCa, and the expression of Her2 (p < 0.001), ER (p < 0.001), PR (p < 0.001) and Ki67 (p = 0.009) of the tumor cell.

CONCLUSION

Our results indicated that high levels of TLSs could predict a favorable prognosis for BCa. Moreover, the TLSs were significantly correlated with the clinicopathological indicators and the critical gene expression of BCa, indicating its potential clinical impact on BCa patients.

Multi-resolution characterization of molecular taxonomies in bulk and single-cell transcriptomics data

As high-throughput genomics assays become more efficient and cost effective, their utilization has become standard in large-scale biomedical projects. These studies are often explorative, in that relationships between samples are not explicitly defined a priori, but rather emerge from data-driven discovery and annotation of molecular subtypes, thereby informing hypotheses and independent evaluation. Here, we present K2Taxonomer, a novel unsupervised recursive partitioning algorithm and associated R package that utilize ensemble learning to identify robust subgroups in a 'taxonomy-like' structure. K2Taxonomer was devised to accommodate different data paradigms, and is suitable for the analysis of both bulk and single-cell transcriptomics, and other '-omics', data. For each of these data types, we demonstrate the power of K2Taxonomer to discover known relationships in both simulated and human tissue data. We conclude with a practical application on breast cancer tumor infiltrating lymphocyte (TIL) single-cell profiles, in which we identified co-expression of translational machinery genes as a dominant transcriptional program shared by T cells subtypes, associated with better prognosis in breast cancer tissue bulk expression data.

Specialized Pro-Resolving Mediators Mitigate Cancer-Related Inflammation: Role of Tumor-Associated Macrophages and Therapeutic Opportunities

Inflammation is a fundamental physiological response orchestrated by innate immune cells to restore tissue homeostasis. Specialized pro-resolving mediators (SPMs) are involved in active resolution of inflammation but when inflammation is incomplete, chronic inflammation creates a favorable environment that fuels carcinogenesis and cancer progression. Conventional cancer therapy also strengthens cancer-related inflammation by inducing massive tumor cell death that activate surrounding immune-infiltrating cells such as tumor-associated macrophages (TAMs). Macrophages are key actors of both inflammation and its active resolution due to their plastic phenotype. In line with this high plasticity, macrophages can be hijacked by cancer cells to support tumor progression and immune escape, or therapy resistance. Impaired resolution of cancer-associated inflammation supported by TAMs may thus reinforces tumor progression. From this perspective, recent evidence suggests that stimulating macrophage's pro-resolving functions using SPMs can promote inflammation resolution in cancer and improve anticancer treatments. Thus, TAMs' re-education toward an antitumor phenotype by using SPMs opens a new line of attack in cancer treatment. Here, we review SPMs' anticancer capacities with special attention regarding their effects on TAMs. We further discuss how this new therapeutic approach could be envisioned in cancer therapy.

A Novel Prognostic Biomarker of Luminal Breast Cancer: High CD39 Expression Is Related to Poor Survival

Background

CD39 is one of the functional surface markers for T regulatory cells, the prognostic role and immune-related effects of CD39 in luminal breast cancer (BC) patients has not been evaluated yet. The aim of the current study was to explore the association between CD39 expression and clinic pathological characteristics and the prognosis in luminal BC patients.

Methods

Clinical information and RNA-sequencing (RNA-Seq) expression data were extracted from The Cancer Genome Atlas (TCGA). Patients were divided into a high or low CD39 expression group by the optimal cutoff value (4.18) identified from the receiver operating characteristic curve analysis. The relationships between CD39 expression and clinic pathological features were evaluated by the corresponding statistical tests. Survival analyses were applied to evaluate the overall survival between the high and low CD39 expression groups in luminal BC. Furthermore, Gene Expression Omnibus datasets were used for external data validation. Gene set enrichment analysis (GSEA) was also performed, and CIBERSORT was used to analyze the immune cell populations.

Results

Analysis of 439 cases of tumor data showed that CD39 was overexpressed in luminal BC. The multivariable analysis suggested that CD39 expression was an independent prognostic factor for luminal BC patients. GSEA suggested that CD39 might play an important role in luminal BC progression through immune regulation. Analysis of immune cell patterns revealed high CD39 expression correlated to a higher proportion of CD8⁺ T cells and M2 macrophages.

Conclusion

This study demonstrates that CD39 expression correlates with the prognosis of luminal BC through TCGA database mining. Further studies are warranted further to elucidate this potential novel therapeutic strategy for BC.

Making Sense of Genetic Information: The Promising Evolution of Clinical Stratification and Precision Oncology Using Machine Learning

Precision medicine is a medical approach to administer patients with a tailored dose of treatment by taking into consideration a person's variability in genes, environment, and lifestyles. The accumulation of omics big sequence data led to the development of various genetic databases on which clinical stratification of high-risk populations may be conducted. In addition, because cancers are generally caused by tumor-specific mutations, large-scale systematic identification of single nucleotide polymorphisms (SNPs) in various tumors has propelled significant progress of tailored treatments of tumors (i.e., precision oncology). Machine learning (ML), a subfield of artificial intelligence in which computers learn through experience, has a great potential to be used in precision oncology chiefly to help physicians make diagnostic decisions based on tumor images. A promising venue of ML in precision oncology is the integration of all available data from images to multi-omics big data for the holistic care of patients and high-risk healthy subjects. In this review, we provide a focused overview of precision oncology and ML with attention to breast cancer and glioma as well as the Bayesian networks that have the flexibility and the ability to work with incomplete information. We also introduce some state-of-the-art attempts to use and incorporate ML and genetic information in precision oncology.

The Immunology of Hormone Receptor Positive Breast Cancer

Immune checkpoint blockade (ICB) has revolutionized the treatment of cancer patients. The main focus of ICB has been on reinvigorating the adaptive immune response, namely, activating cytotoxic T cells. ICB has demonstrated only modest benefit against advanced breast cancer, as breast tumors typically establish an immune suppressive tumor microenvironment (TME). Triple-negative breast cancer (TNBC) is associated with infiltration of tumor infiltrating lymphocytes (TILs) and patients with TNBC have shown clinical responses to ICB. In contrast, hormone receptor positive (HR+) breast cancer is characterized by low TIL infiltration and minimal response to ICB. Here we review how HR+ breast tumors establish a TME devoid of TILs, have low HLA class I expression, and recruit immune cells, other than T cells, which impact response to therapy. In addition, we review emerging technologies that have been employed to characterize components of the TME to reveal that tumor associated macrophages (TAMs) are abundant in HR+ cancer, are highly immune-suppressive, associated with tumor progression, chemotherapy and ICB-resistance, metastasis and poor survival. We reveal novel therapeutic targets and possible combinations with ICB to enhance anti-tumor immune responses, which may have great potential in HR+ breast cancer.

Precision Oncology Beyond Genomics: The Future Is Here-It Is Just Not Evenly Distributed

Cancer is a multifactorial disease with increasing incidence. There are more than 100 different cancer types, defined by location, cell of origin, and genomic alterations that influence oncogenesis and therapeutic response. This heterogeneity between tumors of different patients and also the heterogeneity within the same patient's tumor pose an enormous challenge to cancer treatment. In this review, we explore tumor heterogeneity on the longitudinal and the latitudinal axis, reviewing current and future approaches to study this heterogeneity and their potential to support oncologists in tailoring a patient's treatment regimen. We highlight how the ideal of precision oncology is reaching far beyond the knowledge of genetic variants to inform clinical practice and discuss the technologies and strategies already available to improve our understanding and management of heterogeneity in cancer treatment. We will focus on integrating multi-omics technologies with suitable in vitro models and their proficiency in mimicking endogenous tumor heterogeneity.

Identification of three molecular subtypes based on immune infiltration in ovarian cancer and its prognostic value

BACKGROUND

Increasing studies suggest that tumor immune infiltration is a relative factor of prognosis in ovarian cancer (OvCa). The present study explored the composition of tumor-infiltrating immune cells (TIICs) in OvCa using CIBERSORT algorithm and further assessed their values for prognosis and therapeutic strategies by molecular subtypes.

METHODS

Publicly available databases including The Cancer Genome Atlas (TCGA) and GTEx were searched. Ovarian tumor samples were available from TCGA, and normal ovarian samples were obtained from the GTEx dataset. The relative proportions of immune cell profiling in OvCa and normal samples were evaluated by CIBERSORT algorithm. Association between each immune cell subtype and survival was inferred by the fractions of 22 immune cell types. "CancerSubtypes" R-package was employed to identify the three types of molecular classification and analyze the functional enrichment in each subclass. Response to immunotherapy and anticancer drug targets was predicted via TIDE algorithm and GDSC dataset.

RESULTS

Substantial variation reflecting individual difference was identified between cancer and normal tissues in the immune infiltration profiles. T cells CD4 memory activated, macrophages M1 were associated with improved overall survival (OS) as evaluated by univariate Cox regression and multivariate Cox. Three subtypes were identified by ´CancerSubtypes' R-package and every sub-cluster possessed specific immune cell characterization. Meanwhile, Cluster II exhibited poor prognosis and sensitive response to immunotherapy.

CONCLUSIONS

The cellular component of immune infiltration shows remarkable variation in OvCa. Profiling of immune infiltration is useful in prediction of prognosis of OvCa. The results from profiling might be considered in therapeutic modulation.

Follistatin-like 1 deficiency impairs T cell development to promote lung metastasis of triple negative breast cancer

Our study aims to detect the underlying mechanism of the suppressive effect of Follistatin-like 1 (FSTL1) on lung metastasis of triple negative breast cancer (TNBC). We found that FSTL1 had no effect on the proliferation and metastasis of 4T1 cells in vitro, while in the tumor-bearing Fstl1 heterozygous (Fstl1^+/-) mice, the number of anti-tumor T lymphocytes in the lung was significantly reduced with the increase in lung metastasis. Impaired development of T cells can cause dysfunction of adaptive immune system, which promotes cancer metastasis. Therefore the effect of FSTL1 on T cell development was further investigated. Lower population of T cells in periphery and decreased proliferation of CD4^- CD8^- double negative (DN) thymocytes and impairment development of T cells were found in Fstl1^+/- mice. Furthermore, high expression of FSTL1 in medullary thymus epithelial (mTEC) cells and decreased mRNA expression of inducible costimulator on activated T-cell ligand (Icosl) in mTEC^{sh Fstl1} were detected. Combining other studies that the generation of ICOSL by mTEC cells promotes CD4⁺ single positive (SP) thymocytes to produce IL-2, which promotes T cell development. Our results indicate FSTL1 deficiency in mTEC cells impairs T cell development to promote the lung metastasis of TNBC.

Prognostic Signatures Based on Thirteen Immune-Related Genes in Colorectal Cancer

Background

The immunosuppressive microenvironment is closely related to tumorigenesis and cancer development, including colorectal cancer (CRC). The aim of the current study was to identify new immune biomarkers for the diagnosis and treatment of CRC.

Materials and Methods

CRC data were downloaded from the Gene Expression Omnibus and The Cancer Genome Atlas databases. Sequences of immune-related genes (IRGs) were obtained from the ImmPort and InnateDB databases. Gene set enrichment analysis (GSEA) and transcription factor regulation analysis were used to explore potential mechanisms. An immune-related classifier for CRC prognosis was conducted using weighted gene co-expression network analysis (WGCNA), Cox regression analysis, and least absolute shrinkage and selection operator (LASSO) analysis. ESTIMATE and CIBERSORT algorithms were used to explore the tumor microenvironment and immune infiltration in the high-risk CRC group and the low-risk CRC group.

Results

By analyzing the IRGs that were significantly associated with CRC in the module, a set of 13 genes (CXCL1, F2RL1, LTB4R, GPR44, ANGPTL5, BMP5, RETNLB, MC1R, PPARGC1A, PRKDC, CEBPB, SYP, and GAB1) related to the prognosis of CRC were identified. An IRG-based prognostic signature that can be used as an independent potentially prognostic indicator was generated. The ROC curve analysis showed acceptable discrimination with AUCs of 0.68, 0.68, and 0.74 at 1-, 3-, and 5- year follow-up respectively. The predictive performance was validated in the train set. The potential mechanisms and functions of prognostic IRGs were analyzed, i.e., NOD-like receptor signaling, and transforming growth factor beta (TGFβ) signaling. Besides, the stromal score and immune score were significantly different in high-risk group and low-risk group (p=4.6982e-07, p=0.0107). Besides, the proportions of resting memory CD4⁺ T cells was significantly higher in the high-risk groups.

Conclusions

The IRG-based classifier exhibited strong predictive capacity with regard to CRC. The survival difference between the high-risk and low-risk groups was associated with tumor microenvironment and immune infiltration of CRC. Innovative biomarkers for the prediction of CRC prognosis and response to immunological therapy were identified in the present study.

Identification of a Transcription Factor Signature That Can Predict Breast Cancer Survival

BACKGROUND

The expression pattern of transcription factors (TFs) can be used to develop potential prognostic biomarkers for cancer. In this study, we aimed to identify and validate a TF signature for predicting disease-free survival (DFS) of breast cancer (BRCA) patients.

METHODS

Lasso and the Cox regression analyses were applied to construct a TF signature based on a gene expression dataset from TCGA. The prognosis value of the TF signature was investigated in the TCGA database, and its reliability was further validated in 3 independent datasets from Gene Expression Omnibus (GEO). The prognosis performance of the TF signature was compared with 4 previously published gene signatures. To investigate the association between the TF signature and hallmarks of cancer, Gene Set Enrichment Analysis (GSEA) was carried out. The correlations of the TF signature and the levels of immune infiltration were also investigated.

RESULTS

An 11-TF prognostic signature was constructed with good survival prediction performance for BRCA patients. By using the risk score model based on the 11-TF signature, BRCA patients were stratified into low- and high-risk groups and showed good and poor disease-free survival (DFS), respectively. The risk score was an independent prediction indicator when adjusting for other clinicopathological factors. Furthermore, the 11-TF signature had a better survival prediction performance compared to 4 previously published gene signatures. Moreover, the risk score was a cancer hallmark. Finally, a high-risk score was associated with higher infiltration of M0 and M2 macrophages and was associated with a lower infiltration of resting memory CD4+ T cells and CD8+ T cells.

CONCLUSION

The findings in this study identified and validated a novel prognostic TF signature, which is an independent biomarker for the prediction of DFS in BRCA patients.

Metabolic heterogeneity and immunocompetence of infiltrating immune cells in the breast cancer microenvironment (Review)

Breast cancer is one of the most common malignancies in women and is characterized by active immunogenicity. Immune cell infiltration plays an important role in the development of breast cancer. The degree of infiltration influences both the response to and effect of treatment. However, immune infiltration is a complex process. Differences in oxygen partial pressure, blood perfusion and nutrients in the tumor microenvironment (TME) suggest that infiltrating immune cells in different sites experience different microenvironments with corresponding changes in the metabolic mode, that is, immune cell metabolism is heterogenous in the TME. Furthermore, the present review found that lipid metabolism can support the immunosuppressive microenvironment in breast cancer based on a review of published literature. Research in this field is still ongoing; however, it is vital to understand the metabolic patterns and effects of different microenvironments for antitumor therapy. Therefore, this review discusses the metabolic responses of various immune cells to different microenvironments in breast cancer and provides potentially meaningful insights for tumor immunotherapy.

Development of an Immunogenomic Landscape-Based Prognostic Index of Head and Neck Squamous Cell Carcinoma

Head and neck squamous cell carcinoma (HNSCC) is the eighth leading cancer by incidence worldwide, with approximately 700,000 new cases in 2018 (accounting for 11% of all cancers). The occurrence and development of tumors are closely related to the immunological function of the body and sensitivity to treatment schemes as well as prognosis. It is urgent for clinicians to systematically study patients’ immune gene maps to help select a treatment plan and analyze the potential to cure HNSCC. Here, the transcriptomic data of HNSCC samples were downloaded from The Cancer Genome Atlas (TCGA), and 4,793 genes differentially expressed in normal and cancer tissues of HNSCC were identified, including 1,182 downregulated and 3,611 upregulated genes. From these genes, 400 differentially expressed immune-related genes (IRGs) were extracted, including 95 downregulated genes and 305 upregulated genes. The prognostic values of IRGs were evaluated by univariate Cox analysis, and 236 genes that were significantly related to the overall survival (OS) of patients were identified. The signaling pathways that play roles in the prognosis of IRGs were investigated by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses, and the expression profiles of IRGs and OS in 499 HNSCC patients based on TCGA dataset were integrated. Potential molecular mechanisms and characteristics of these HNSCC-specific IRGs were further explored with the help of a new prognostic index based on IRGs developed by least absolute shrinkage and selection operator (LASSO) Cox analysis. A total of 64 hub genes (IRGs associated with prognosis) were markedly associated with the clinical outcome of HNSCC patients. KEGG functional enrichment analysis revealed that these genes were actively involved in several pathways, e.g., cytokine–cytokine receptor interaction, T-cell receptor signaling, and natural killer cell-mediated cytotoxicity. IRG-based prognostic signatures performed moderately in prognostic predictions. Interestingly, the prognostic index based on IRGs reflected infiltration by several types of immune cells. These data screened several IRGs of clinical significance and revealed drivers of the immune repertoire, demonstrating the importance of a personalized IRG-based immune signature in the recognition, surveillance, and prognosis of HNSCC.

ADRB1 was identified as a potential biomarker for breast cancer by the co-analysis of tumor mutational burden and immune infiltration

Breast cancer (BRCA) has traditionally been considered as having poor immunogenicity and is characterized by relatively low tumor mutational burden (TMB). Improving immunogenicity may improve the response to clinical immunotherapy of BRCA. However, the relationship between TMB, immune infiltration, and prognosis in BRCA remains unclear. We aimed to explore their interrelations and potential biomarkers. In this study, based on somatic mutation data of BRCA from The Cancer Genome Atlas (TCGA), patients were categorized into high and low TMB groups utilizing the TMB values. CIBERSOFT algorithm indicated significant infiltration of activated partial immune cells in high TMB group. Besides, ADRB1 had been identified as a prognosis-related immune gene in the mutant genes by the combination of the ImmPort database and the univariate Cox analysis. ADRB1 mutation was associated with lower TMB and manifested a satisfactory clinical prognosis. Various database applications (Gene Set Enrichment Analysis, Tumor IMmune Estimation Resource, Connectivity Map, KnockTF) supported the selection of treatment strategies targeting ADRB1. In conclusion, TMB was not an independent prognostic factor for BRCA and high TMB was more likely to activate a partial immune response. ADRB1 was identified as a potential biomarker and may provide new insights for co-therapy of BRCA.

Prognostic impact of regulatory T cell in head and neck squamous cell carcinoma: A systematic review and meta-analysis

OBJECTIVES

The impact of regulatory T (Treg) cells as a prognostic factor of survival in head and neck squamous cell carcinoma (HNSCC) remains controversial. We aimed to evaluate the prognostic value of Treg cells in patients with HNSCC through a meta-analysis.

MATERIALS AND METHODS

Through a literature search in PubMed, Embase, and Cochrane, we included 11 articles in this meta-analysis and investigated the effect of Treg cell level on the survival of patients with HNSCC. Also, we performed a subgroup analysis according to the study sample (blood vs. tumor tissue), primary tumor site, HPV infectivity, or Treg cell marker.

RESULTS

High levels of circulating Treg cells in the peripheral blood of patients with HNSCC can significantly increase the disease specific survival rate of patients. Moreover, subgroup analysis showed that high levels of Treg in peripheral blood were significantly associated with better disease specific survival in patients with oral cancer, a subsite of HNSCC, but not in those with other head and neck subsite. Positivity of HPV infection did not influence the prognosis of patients with HNSCC.

CONCLUSION

Increase in the levels of circulating Treg cells in peripheral blood can be a prognostic factor of survival in patients with oral cancer.

NLRP3 as Putative Marker of Ipilimumab-Induced Cardiotoxicity in the Presence of Hyperglycemia in Estrogen-Responsive and Triple-Negative Breast Cancer Cells

Hyperglycemia, obesity and metabolic syndrome are negative prognostic factors in breast cancer patients. Immune checkpoint inhibitors (ICIs) have revolutionized cancer treatment, achieving unprecedented efficacy in multiple malignancies. However, ICIs are associated with immune-related adverse events involving cardiotoxicity. We aimed to study if hyperglycemia could affect ipilimumab-induced anticancer efficacy and enhance its cardiotoxicity. Human cardiomyocytes and estrogen-responsive and triple-negative breast cancer cells (MCF-7 and MDA-MB-231 cell lines) were exposed to ipilimumab under high glucose (25 mM); low glucose (5.5 mM); high glucose and co-administration of SGLT-2 inhibitor (empagliflozin); shifting from high glucose to low glucose. Study of cell viability and the expression of new putative biomarkers of cardiotoxicity and resistance to ICIs (NLRP3, MyD88, cytokines) were quantified through ELISA (Cayman Chemical) methods. Hyperglycemia during treatment with ipilimumab increased cardiotoxicity and reduced mortality of breast cancer cells in a manner that is sensitive to NLRP3. Notably, treatment with ipilimumab and empagliflozin under high glucose or shifting from high glucose to low glucose reduced significantly the magnitude of the effects, increasing responsiveness to ipilimumab and reducing cardiotoxicity. To our knowledge, this is the first evidence that hyperglycemia exacerbates ipilimumab-induced cardiotoxicity and decreases its anticancer efficacy in MCF-7 and MDA-MB-231 cells. This study sets the stage for further tests on other breast cancer cell lines and primary cardiomyocytes and for preclinical trials in mice aimed to decrease glucose through nutritional interventions or administration of gliflozines during treatment with ipilimumab.

Promising potential of [177Lu]Lu-DOTA-folate to enhance tumor response to immunotherapy-a preclinical study using a syngeneic breast cancer model

PURPOSE

It was previously demonstrated that radiation effects can enhance the therapy outcome of immune checkpoint inhibitors. In this study, a syngeneic breast tumor mouse model was used to investigate the effect of [¹⁷⁷Lu]Lu-DOTA-folate as an immune stimulus to enhance anti-CTLA-4 immunotherapy.

METHODS

In vitro and in vivo studies were performed to characterize NF9006 breast tumor cells with regard to folate receptor (FR) expression and the possibility of tumor targeting using [¹⁷⁷Lu]Lu-DOTA-folate. A preclinical therapy study was performed over 70 days with NF9006 tumor-bearing mice that received vehicle only (group A); [¹⁷⁷Lu]Lu-DOTA-folate (5 MBq; 3.5 Gy absorbed tumor dose; group B); anti-CTLA-4 antibody (3 × 200 μg; group C), or both agents (group D). The mice were monitored regarding tumor growth over time and signs indicating adverse events of the treatment.

RESULTS

[¹⁷⁷Lu]Lu-DOTA-folate bound specifically to NF9006 tumor cells and tissue in vitro and accumulated in NF9006 tumors in vivo. The treatment with [¹⁷⁷Lu]Lu-DOTA-folate or an anti-CTLA-4 antibody had only a minor effect on NF9006 tumor growth and did not substantially increase the median survival time of mice (23 day and 19 days, respectively) as compared with untreated controls (12 days). [¹⁷⁷Lu]Lu-DOTA-folate sensitized, however, the tumors to anti-CTLA-4 immunotherapy, which became obvious by reduced tumor growth and, hence, a significantly improved median survival time of mice (> 70 days). No obvious signs of adverse effects were observed in treated mice as compared with untreated controls.

CONCLUSION

Application of [¹⁷⁷Lu]Lu-DOTA-folate had a positive effect on the therapy outcome of anti-CTLA-4 immunotherapy. The results of this study may open new perspectives for future clinical translation of folate radioconjugates.

Elevated expression of FREM1 in breast cancer indicates favorable prognosis and high-level immune infiltration status

Breast cancer (BC) poses one of the major threats to female's health worldwide. Immune infiltration in BC is a key representative of the tumor microenvironment and has been proven highly relevant for prognosis. The role of the FREM1 (FRAS1-Related Extracellular Matrix 1) gene in carcinoma has not studied, moreover, the underlying mechanism remains largely unknown. This study aims to investigate the expression profile and potential action of FREM1 on BC progression. We applied series of bioinformatic methods as well as immunohistochemistry (IHC) and immunofluorescence (IF) to analyze FREM1 expression profile, its relationship with clinicopathological characteristics, impact on clinical outcomes, relevant functions, correlation with immune infiltration in BC. The results demonstrated that FREM1 had a dramatically reduced expression in BC tissues, possessed an inverse correlation with stage, age, and metastasis, and exhibited a higher level in invasive lobular breast carcinoma than in ductal one. Furthermore, decreased FREM1 expression was often associated with estrogen receptor (ER)/progesterone receptor (PR) negative and triple negative breast carcinoma (TNBC) status while human epidermal growth factor 2 (Her-2) positive status, and considerably correlated with a worse overall survival (OS) and recurrence-free survival (RFS). Meanwhile, the univariate/multivariate Cox model revealed that low-FREM1 expression can be an independent prognostic factor for BC. Additionally, FREM1 was mainly involved in the cell metabolism and immune cells infiltration. Moreover, IHC and IF demonstrated a positive correlation of its expression with the immune infiltrating levels of CD4⁺ , CD8⁺ T cells, and CD86⁺ M1 macrophages while a negative correlation with CD68⁺ pan-macrophages and CD163⁺ M2 macrophages. These findings suggest that FREM1 can be a potential biomarker for evaluating the immune infiltrating status, and the BC prognosis.

TILRR (FREM1 isoform 2) is a prognostic biomarker correlated with immune infiltration in breast cancer

In atherosclerosis, upregulated TILRR (FREM1 isoform 2) expression increases immune cell infiltration. We hypothesized that TILRR expression is also correlated with cancer progression. By analyzing data from Oncomine and the Tumor Immune Estimation Resource, we found that TILRR mRNA expression was significantly lower in breast cancer tissue than adjacent normal tissue. Kaplan-Meier survival analysis and immunohistochemical staining revealed shortened overall survival and disease-free survival in patients with low TILRR expression. TILRR transcript expression was positively correlated with immune score, immune cell biomarkers and the expression of CXCL10 and CXCL11. TILRR expression was also positively correlated with CD8+ and CD4+ T-cell infiltration. These correlations were verified using the ESTIMATE algorithm, gene set enrichment analysis and Q-PCR. We concluded that impaired TILRR expression is correlated with breast cancer prognosis and immune cell infiltration.

Coagulation factor V is a marker of tumor-infiltrating immune cells in breast cancer

Background

Factor (F) V is an essential cofactor in blood coagulation, however, F5 expression in breast tumors has also been linked to tumor aggressiveness and overall survival. The specific role of FV in breast cancer is yet unknown. We therefore aimed at dissecting the biological relevance of FV in breast cancer.

Methods

Gene expression data from a Scandinavian breast cancer cohort (n = 363) and the cancer genome atlas (TCGA) (n = 981) and 12 replication cohorts were used to search for F5 co-expressed genes, followed by gene ontology analysis. Pathological and bioinformatic tools were used to evaluate immune cell infiltration and tumor purity. T cell activation, proliferation and migration were studied in FV treated Jurkat T cells.

Results

F5 co-expressed genes were mainly associated with immune system processes and cell activation. Tumors with high expression of F5 were more infiltrated with both lymphoid (T cells, NK cells, and B cells) and myeloid cells (macrophages and dendritic cells), and F5 expression was negatively correlated with tumor purity (ρ = -0.32). Confirming a prognostic role, data from the Kaplan-Meier plotter showed that high F5 expression was associated with improved relapse-free survival. The strongest association was observed in basal-like breast cancer (HR = 0.55; 95% CI, 0.42-0.71). Exogenous FV did not substantially affect activation, proliferation or migration of human T cells.

Conclusions

F5 was identified as a novel marker of immune cell infiltration in breast cancer, and the prognostic role of F5 was verified. FV emerge as an interesting immunological biomarker with potential therapeutic relevance for the cancer-inflammation-thrombosis circuit.

Prognostic landscape of tumor-infiltrating immune cells and immune-related genes in the tumor microenvironment of gastric cancer

The tumor microenvironment is closely related to the progression and immune escape of tumor cells. Tumor-infiltrating immune cells (TIICs) and immune-related genes (IRGs) are indispensable components of the tumor microenvironment and have been demonstrated to be highly valuable in determining the prognosis of multiple cancers. To elucidate the prognostic value of TIICs and IRGs in gastric cancer, we conducted a comprehensive analysis focusing on the abundances of 22 types of TIICs and differentially expressed IRGs based on a dataset from The Cancer Genome Atlas (TCGA). The results showed that great composition differences in TIICs and immune cell subfractions were associated with survival outcomes in different stages. Additionally, 29 hub genes were characterized from 345 differentially expressed IRGs and found to be significantly associated with survival outcomes. Then, an independent prognostic indicator based on ten IRGs was successfully constructed after multivariate adjustment for some clinical parameters. Further validation revealed that these hub IRGs could reflect the infiltration levels of immune cells. Thus, our results confirmed the clinical significance of TIICs and IRGs in gastric cancer and may establish a foundation for further exploring immune cell and gene targets for personalized treatment.

Beyond Antoni: A Surgeon's Guide to the Vestibular Schwannoma Microenvironment

Introduction Vestibular schwannomas (VS) are histologically benign tumors arising from cranial nerve VIII. Far from a homogenous proliferation of Schwann cells, mounting evidence has highlighted the complex nature of the inflammatory microenvironment in these tumors.

Methods A review of the literature pertaining to inflammation, inflammatory molecular pathways, and immune-related therapeutic targets in VS was performed. Relevant studies published up to June 2020 were identified based on a literature search in the PubMed and MEDLINE databases and the findings were synthesized into a concise narrative review of the topic.

Results The VS microenvironment is characterized by a dense infiltrate of inflammatory cells, particularly macrophages. Significantly higher levels of immune cell infiltration are observed in growing versus static tumors, and there is a demonstrable interplay between inflammation and angiogenesis in growing VS. While further mechanistic studies are required to ascertain the exact role of inflammation in angiogenesis, tumor growth, and Schwann cell control, we are beginning to understand the key molecular pathways driving this inflammatory microenvironment, and how these processes can be monitored and targeted in vivo.

Conclusion Observational research has revealed a complex and heterogeneous tumor microenvironment in VS. The functional landscape and roles of macrophages and other immune cells in the VS inflammatory infiltrate are, however, yet to be established. The antiangiogenic drug bevacizumab has shown the efficacy of targeted molecular therapies in VS and there is hope that agents targeting another major component of the VS microenvironment, inflammation, will also find a place in their future management.

Molecular and Cellular Factors Associated with Racial Disparity in Breast Cancer

Recent studies have demonstrated that racial differences can influence breast cancer incidence and survival rate. African American (AA) women are at two to three fold higher risk for breast cancer than other ethnic groups. AA women with aggressive breast cancers show worse prognoses and higher mortality rates relative to Caucasian (CA) women. Over the last few years, effective treatment strategies have reduced mortality from breast cancer. Unfortunately, the breast cancer mortality rate among AA women remains higher compared to their CA counterparts. The focus of this review is to underscore the racial differences and differential regulation/expression of genetic signatures in CA and AA women with breast cancer. Moreover, immune cell infiltration significantly affects the clinical outcome of breast cancer. Here, we have reviewed recent findings on immune cell recruitment in the tumor microenvironment (TME) and documented its association with breast cancer racial disparity. In addition, we have extensively discussed the role of cytokines, chemokines, and other cell signaling molecules among AA and CA breast cancer patients. Furthermore, we have also reviewed the distinct genetic and epigenetic changes in AA and CA patients. Overall, this review article encompasses various molecular and cellular factors associated with breast cancer disparity that affects mortality and clinical outcome.

An In Vitro Model of Mast Cell Recruitment and Activation by Breast Cancer Cells Supports Anti-Tumoral Responses

Breast cancer (BrC) affects millions of women yearly. Mast cells (MCs) are common components of breast tumors with documented agonistic and antagonistic roles in tumor progression. Understanding the participation of MCs in BrC may lead to new therapies to control tumor growth. In this study, we looked into mechanistic models of MC responses triggered by BrC cells (BrCC), assessing both early degranulation and late transcriptional activities. We used aggressive and non-aggressive BrCC to model the progressive staging of the disease over HMC1 and LAD-2 human MC lines. We found that both MC lines were chemoattracted by all BrCC, but their activation was preferentially induced by aggressive lines, finding differences in their active transcriptional programs, both at basal level and after stimulation. Among those genes with altered expression were down-regulated SPP1, PDCD1, IL17A and TGFB1 and up-regulated KITLG and IFNG. A low expression of SPP1 and a high expression of KITLG and IFNG were associated with increased overall survival of BrC patients from public databases. The set of altered genes is more often associated with tumor stromas enriched with anti-tumoral signals, suggesting that MCs may participate in tumor control.

Systematic profiling of alternative splicing in Helicobacter pylori-negative gastric cancer and their clinical significance

Background

Alternative splicing (AS) may cause structural and functional variations in the protein to promote the proliferation of tumor cells. However, there is no comprehensive analysis of the clinical significance of AS in Helicobacter pylori-negative gastric cancer (HP⁻ GC).

Methods

The clinical, gene expression profile data and AS events of 138 HP⁻ GC patients were obtained from the database named the cancer genome atlas. Differently expressed AS (DEAS) events were determined by a comparison of the PSI values between HP⁻ GC samples and adjacent normal samples. Unsupervised clustering analysis, proportional regression and Kaplan–Meier analysis were used to explore the association between clinical data and immune features and to establish two nomograms about the prognosis of HP⁻ GC. Finally, splicing networks were constructed using Cytoscape.

Results

A total of 48141 AS events and 1041 DEAS events were found in HP⁻ GC. Various functions and pathways of DEAS events parent genes were enriched, such as cell-substrate junction, cell leading edge, focal adhension, and AMPK signaling. Seven overall survival (OS)-related and seven disease-free survival (DFS)-related AS events were used to construct the prognostic signatures. Based on the independent prognostic factors, two nomograms were established and showed excellent performance. Then, splicing regulatory networks among the correlations suggested that splicing factors were significantly associated with prognostic DEASs. Finally, the unsupervised clustering analysis revealed that DEAS-based clusters were associated with clinical characteristics, tumor microenvironment, tumor mutation burden, and immune features.

Conclusion

Seven OS-related and seven DFS-related AS events have been found to be correlated with the prognosis of HP⁻ GC and can be used as prognostic factors to establish an effective nomogram.

microRNAs in the Antitumor Immune Response and in Bone Metastasis of Breast Cancer: From Biological Mechanisms to Therapeutics

Breast cancer is the most common type of cancer in women, and the occurrence of metastasis drastically worsens the prognosis and reduces overall survival. Understanding the biological mechanisms that regulate the transformation of malignant cells, the consequent metastatic transformation, and the immune surveillance in the tumor progression would contribute to the development of more effective and targeted treatments. In this context, microRNAs (miRNAs) have proven to be key regulators of the tumor-immune cells crosstalk for the hijack of the immunosurveillance to promote tumor cells immune escape and cancer progression, as well as modulators of the metastasis formation process, ranging from the preparation of the metastatic site to the transformation into the migrating phenotype of tumor cells. In particular, their deregulated expression has been linked to the aberrant expression of oncogenes and tumor suppressor genes to promote tumorigenesis. This review aims at summarizing the role and functions of miRNAs involved in antitumor immune response and in the metastasis formation process in breast cancer. Additionally, miRNAs are promising targets for gene therapy as their modulation has the potential to support or inhibit specific mechanisms to negatively affect tumorigenesis. With this perspective, the most recent strategies developed for miRNA-based therapeutics are illustrated.

Identification of a six-gene signature associated with tumor mutation burden for predicting prognosis in patients with invasive breast carcinoma

Background

Breast cancer (BC) is one of the most common cancers with high mortality worldwide. In the present study, through bioinformatics analysis, we aimed to identify new biomarkers to predict the survival rate of BC patients.

Methods

Differentially expressed genes (DEGs) between low- and high-tumor mutation burden (TMB) groups were identified by using The Cancer Genome Atlas (TCGA) dataset and integrated analysis. Gene Ontology (GO), Kyoto encyclopedia of genes and genomes (KEGG) enrichment analysis, and the protein-protein interaction (PPI) network, were applied to predict the function of these above DEGs. Then, the Cox proportional hazard model was developed to screen DEGs. Based on the prognostic signature, survival analysis was used on The Cancer Genome Atlas Breast Invasive Carcinoma (TCGA-BRCA) dataset. Finally, the single-sample gene set enrichment (ssGSEA) analysis was employed to estimate immune cells related to this signature.

Results

To create a prognostic signature, 6 DEGs were identified. The results revealed that the survival time of patients with high-risk scores based on the expression of the six-gene signature was dramatically shorter than that of patients with low-risk scores in BC. Furthermore, survival analysis and multivariate cox analysis indicated that the six-gene signature was an independent prognostic factor of BC. Then, we built a nomogram that integrated the clinicopathological factors with the six-gene signature to predict the survival probability of BC patients. We eventually predicted the 20 most vital small molecule drugs by CMap, and Nadolol was considered as the most promising small molecule to treat BC. Moreover, ssGSEA analysis showed that the 6 genes were closely associated with immune cells.

Conclusions

We constructed a six-gene signature associated with TMB that can improve the prognosis prediction and could be seen as a biomarker for BC patients.