An immune response gene expression module identifies a good prognosis subtype in estrogen receptor negative breast cancer

Spatial transcriptomics reveals substantial heterogeneity in triple-negative breast cancer with potential clinical implications

While triple-negative breast cancer (TNBC) is known to be heterogeneous at the genomic and transcriptomic levels, spatial information on tumor organization and cell composition is still lacking. Here, we investigate TNBC tumor architecture including its microenvironment using spatial transcriptomics on a series of 92 patients. We perform an in-depth characterization of tumor and stroma organization and composition using an integrative approach combining histomorphological and spatial transcriptomics. Furthermore, a detailed molecular characterization of tertiary lymphoid structures leads to identify a gene signature strongly associated to disease outcome and response to immunotherapy in several tumor types beyond TNBC. A stepwise clustering analysis identifies nine TNBC spatial archetypes, further validated in external datasets. Several spatial archetypes are associated with disease outcome and characterized by potentially actionable features. In this work, we provide a comprehensive insight into the complexity of TNBC ecosystem with potential clinical relevance, opening avenues for treatment tailoring including immunotherapy.

High CTLA-4 gene expression is an independent good prognosis factor in breast cancer patients, especially in the HER2-enriched subtype

BACKGROUND

Breast cancer (BC) is the most common cancer in women and the leading cause of cancer-related death worldwide. This heterogeneous disease has been historically considered a non-immunogenic type of cancer. However, recent advances in immunotherapy have increased the interest in knowing the role of the immune checkpoints (IC) and other immune regulation pathways in this neoplasia.

METHODS

In this retrospective study, we evaluated the correlation of mRNA expression of CTLA-4, PDCD1 (PD1), CD274 (PD-L1), PDCD1LG2 (PD-L2), CD276 (B7-H3), JAK2, and FOXO1 with clinicopathological factors and BC patient's outcome by real-time quantitative polymerase chain reaction (qPCR).

RESULTS

Our results showed that immunoregulatory gene expression depends on BC immunophenotype being CTLA-4 and PDCD1 (PD1) overexpressed on triple-negative/basal-like (TN/BL) and luminal B/HER2-positive phenotypes, respectively, and CD276 (B7-H3), JAK2 and FOXO1 associated with both luminal A and luminal B/HER2-negative tumors. In addition, we found that these genes can also be related to aggressive and non-aggressive clinicopathological characteristics in BC. Finally, survival analysis showed that CTLA-4 expression levels emerge as a significant independent factor of good prognosis in BC patients, especially in the HER2-enriched subtype.

CONCLUSION

Considering all these data, we can conclude that the expression of immunoregulatory genes depends on tumor phenotype and has potential clinical implications in BC patients.

Differential Abundance of DNA Damage Sensors and Innate Immune Signaling Proteins in Inositol Polyphosphate 4-Phosphatase Type II-Negative Triple-Negative Breast Cancer Classified by Immunotype

The influence of neoplastic cells on the tumor microenvironment is poorly understood. In this study, eight patient samples representing two immunotypes of triple-negative breast cancer (TNBC), defined by quantitative histologic criteria as T-cell desert and T-cell infiltrated (TCI), were compared via label-free quantitative protein mass spectrometry of material extracted directly from targeted regions of formalin-fixed, paraffin-embedded tissue sections. Of 2934 proteins quantitated, 439 were significantly differentially abundant, among which 361 were overabundant in TCI-TNBC. The 361-protein group included proteins involved in major histocompatibility complex-I antigen processing and presentation, viral defense, DNA damage response, and innate immune signaling. Immunohistochemical validation of selected proteins showed good positive correlation between neoplastic cell histoscores and label-free quantitation. Extension of immunohistochemical analysis to a total of 58 inositol polyphosphate 4-phosphatase type II-negative TNBC confirmed elevated levels of the DNA damage sensor interferon-γ-inducible protein 16, inflammasome adaptor apoptosis-associated speck-like protein containing a CARD (ASC), and pore-forming protein gasdermin D in TCI-TNBC neoplastic cells. By contrast, cGMP-AMP synthase inhibitor barrier to autointegration factor (BAF) was elevated in the neoplastic cells of T-cell desert TNBC. These findings demonstrate a previously unknown correlation between the degree of T-cell infiltration in inositol polyphosphate 4-phosphatase type II-negative TNBC and the levels, in cognate neoplastic cells, of proteins that modulate innate immune signaling in response to DNA damage.

Differential chromatin accessibility and transcriptional dynamics define breast cancer subtypes and their lineages

Breast cancer (BC) is defined by distinct molecular subtypes with different cells of origin. The transcriptional networks that characterize the subtype-specific tumor-normal lineages are not established. In this work, we applied bulk, single-cell and single-nucleus multi-omic techniques as well as spatial transcriptomics and multiplex imaging on 61 samples from 37 patients with BC to show characteristic links in gene expression and chromatin accessibility between BC subtypes and their putative cells of origin. Regulatory network analysis of transcription factors underscored the importance of BHLHE40 in luminal BC and luminal mature cells and KLF5 in basal-like tumors and luminal progenitor cells. Furthermore, we identify key genes defining the basal-like (SOX6 and KCNQ3) and luminal A/B (FAM155A and LRP1B) lineages. Exhausted CTLA4-expressing CD8+ T cells were enriched in basal-like BC, suggesting an altered means of immune dysfunction. These findings demonstrate analysis of paired transcription and chromatin accessibility at the single-cell level is a powerful tool for investigating cancer lineage and highlight transcriptional networks that define basal and luminal BC lineages.

PD-L1 protein expression in breast cancer

AIMS

The immune checkpoint marker, Programmed cell death-ligand 1 (PD-L1), is expressed by both cancer epithelial cells and tumour-infiltrating immune cells (TICs) thus constituting a potential target for immunotherapy. This is of particular interest in triple negative breast cancer. In this study, we assessed the prognostic value of PD-L1 expression in tumour epithelial cells and TICs in a series of patients with breast cancer with long-term follow-up, and associations between PD-L1 expression and histopathological type and grade, proliferation and molecular subtype.

METHODS

Using immunohistochemistry for PD-L1 in tissue microarrays, we assessed PD-L1 expression in 821 tumours. Expression of PD-L1 was assessed separately in the epithelial and stromal compartments and classified as <1%, ≥1% to <10% or ≥10% positive staining cells. We correlated PD-L1 expression in tumour epithelial cells and TICs with tumour characteristics using Pearson's χ2 test, and prognosis by cumulative incidence of death from breast cancer and Cox regression analyses.

RESULTS

We found membranous staining in ≥1% of tumour epithelial cells in 53/821 cases (6.5%). Of these, 21 (2.6%) were ≥10%. Among TICs, staining (≥1%) was seen in 144/821 cases (17.6%). Of these, 62 were ≥10% (7.6%). PD-L1 was associated with high histopathological grade and proliferation, and the medullary and metaplastic patterns. In TICs, PD-L1 ≥1% found in 22/34 (34.4%) human epidermal growth factor receptor 2 type and 29/58 (50%) basal phenotype. An independent association between PD-L1 expression and prognosis was not observed.

CONCLUSIONS

PD-L1 is expressed more frequently in TICs than tumour epithelial cells. Expression in TICs is associated with aggressive tumour characteristics and non-luminal tumours but not with prognosis.

Integrated immuno-transcriptomic analysis of ovarian cancer identifies a four-chemokine-dominated subtype with antitumor immune-active phenotype and favorable prognosis

BACKGROUND

Ovarian cancer (OV) is a heterogeneous disease but has traditionally been treated as an immunologically cold malignancy. The relationship between the immune-active cancer phenotype typified by a T helper 1 (Th-1) immune response and clinical outcome in OV remains uncertain.

METHODS

A cohort-scale compendium of transcriptomic data from 2850 OV samples from 19 individual datasets was compiled for integrative immuno-transcriptomic analysis. The immunological constant of rejection was used as a metric to assess the Th-1/cytotoxic response orientation and investigate the clinical-biological significance of immune polarization towards a Th-1 immune response. Single-cell RNA sequencing data from 39 OV samples were analyzed to elucidate the variability of the immune microenvironment, and immunohistochemical validation was performed on 39 samples from the Harbin Medical University Cancer Hospital.

RESULTS

Our results demonstrated the prognostic significance of a Th-1/cytotoxic immune profile within the tumor microenvironment (TME) using the immunological constant of rejection classification to OV samples. Specifically, patients with tumors expressing high levels of ICR markers showed significantly improved survival. A gene panel consisting of four chemokines (CXCL9, CXCL10, CXCL11 and CXCL13) was identified as critical players in mediating the establishment of an active T-cell-inflamed antitumor phenotype. This 4-chemokine signature, which was extensively validated in external multicenter cohorts through transcriptomic profiling and in an independent in-house cohort through immunohistochemistry, introduced a novel immune classification in OV and identified a chemokine-dominated subtype associated with an active antitumor immune phenotype and favorable prognosis. Single-cell transcriptomic analysis revealed that chemokine-dominated tumors increase CXCR3 + NK and T cell recruitment to the TME primarily through the overexpression of macrophage-derived CXCL9/10/11.

CONCLUSIONS

This study provides new insights into understanding immune heterogeneity within the TME and paves the way for tailoring appropriate therapeutic interventions for patients with differing immune profiles.

Myeloid‑derived suppressor cells as targets of emerging therapies and nanotherapies (Review)

Breast cancer (BC) is the leading cause of cancer-related mortality among women worldwide. Immunotherapies are a promising approach in cancer treatment, particularly for aggressive forms of BC with high mortality rates. However, the current eligibility for immunotherapy remains limited to a limited fraction of patients with BC. Myeloid-derived suppressor cells (MDSCs), originating from myeloid cells, are known for their dual role in immunosuppression and tumor promotion, significantly affecting patient outcomes by fostering the formation of premetastatic niches. Consequently, targeting MDSCs has emerged as a promising avenue for further exploration in therapeutic interventions. Leveraging nanotechnology-based drug delivery systems, which excel in accumulating drugs within tumors via passive or active targeting mechanisms, are a promising strategy for the use of MDSCs in the treatment of BC. The present review discusses the immunosuppressive functions of MDSCs, their role in BC, and the diverse strategies for targeting them in cancer therapy. Additionally, the present review discusses future advancements in BC treatments focusing on MDSCs. Furthermore, it elucidates the mechanisms underlying MDSC activation, recruitment and differentiation in BC progression, highlighting the clinical characteristics that render MDSCs suitable candidates for the therapy and targeted nanotherapy of BC.

Understanding tissue-resident macrophages unlocks the potential for novel combinatorial strategies in breast cancer

Tissue-resident macrophages (TRMs) are an integral part of the innate immune system, but their biology is not well understood in the context of cancer. Distinctive resident macrophage populations are identified in different organs in mice using fate mapping studies. They develop from the yolk sac and self-maintain themselves lifelong in specific tissular niches. Similarly, breast-resident macrophages are part of the mammary gland microenvironment. They reside in the breast adipose tissue stroma and close to the ductal epithelium and help in morphogenesis. In breast cancer, TRMs may promote disease progression and metastasis; however, precise mechanisms have not been elucidated. TRMs interact intimately with recruited macrophages, cytotoxic T cells, and other immune cells along with cancer cells, deciding further immunosuppressive or cytotoxic pathways. Moreover, triple-negative breast cancer (TNBC), which is generally associated with poor outcomes, can harbor specific TRM phenotypes. The influence of TRMs on adipose tissue stroma of the mammary gland also contributes to tumor progression. The complex crosstalk between TRMs with T cells, stroma, and breast cancer cells can establish a cascade of downstream events, understanding which can offer new insight for drug discovery and upcoming treatment choices. This review aims to acknowledge the previous research done in this regard while exploring existing research gaps and the future therapeutic potential of TRMs as a combination or single agent in breast cancer.

Development and validation of a reliable DNA copy-number-based machine learning algorithm (CopyClust) for breast cancer integrative cluster classification

The Integrative Cluster subtypes (IntClusts) provide a framework for the classification of breast cancer tumors into 10 distinct groups based on copy number and gene expression, each with unique biological drivers of disease and clinical prognoses. Gene expression data is often lacking, and accurate classification of samples into IntClusts with copy number data alone is essential. Current classification methods achieve low accuracy when gene expression data are absent, warranting the development of new approaches to IntClust classification. Copy number data from 1980 breast cancer samples from METABRIC was used to train multiclass XGBoost machine learning algorithms (CopyClust). A piecewise constant fit was applied to the average copy number profile of each IntClust and unique breakpoints across the 10 profiles were identified and converted into ~ 500 genomic regions used as features for CopyClust. These models consisted of two approaches: a 10-class model with the final IntClust label predicted by a single multiclass model and a 6-class model with binary reclassification in which four pairs of IntClusts were combined for initial multiclass classification. Performance was validated on the TCGA dataset, with copy number data generated from both SNP arrays and WES platforms. CopyClust achieved 81% and 79% overall accuracy with the TCGA SNP and WES datasets, respectively, a nine-percentage point or greater improvement in overall IntClust subtype classification accuracy. CopyClust achieves a significant improvement over current methods in classification accuracy of IntClust subtypes for samples without available gene expression data and is an easily implementable algorithm for IntClust classification of breast cancer samples with copy number data.

Breast Tumor Metastasis and Its Microenvironment: It Takes Both Seed and Soil to Grow a Tumor and Target It for Treatment

Metastasis remains a major challenge in treating breast cancer. Breast tumors metastasize to organ-specific locations such as the brain, lungs, and bone, but why some organs are favored over others remains unclear. Breast tumors also show heterogeneity, plasticity, and distinct microenvironments. This contributes to treatment failure and relapse. The interaction of breast cancer cells with their metastatic microenvironment has led to the concept that primary breast cancer cells act as seeds, whereas the metastatic tissue microenvironment (TME) is the soil. Improving our understanding of this interaction could lead to better treatment strategies for metastatic breast cancer. Targeted treatments for different subtypes of breast cancers have improved overall patient survival, even with metastasis. However, these targeted treatments are based upon the biology of the primary tumor and often these patients' relapse, after therapy, with metastatic tumors. The advent of immunotherapy allowed the immune system to target metastatic tumors. Unfortunately, immunotherapy has not been as effective in metastatic breast cancer relative to other cancers with metastases, such as melanoma. This review will describe the heterogeneic nature of breast cancer cells and their microenvironments. The distinct properties of metastatic breast cancer cells and their microenvironments that allow interactions, especially in bone and brain metastasis, will also be described. Finally, we will review immunotherapy approaches to treat metastatic breast tumors and discuss future therapeutic approaches to improve treatments for metastatic breast cancer.

Canonical Kaiso target genes define a functional signature that associates with breast cancer survival and the invasive lobular carcinoma histological type

Invasive lobular carcinoma (ILC) is a low- to intermediate-grade histological breast cancer type caused by mutational inactivation of E-cadherin function, resulting in the acquisition of anchorage independence (anoikis resistance). Most ILC cases express estrogen receptors, but options are limited in relapsed endocrine-refractory disease as ILC tends to be less responsive to standard chemotherapy. Moreover, ILC can relapse after >15 years, an event that currently cannot be predicted. E-cadherin inactivation leads to p120-catenin-dependent relief of the transcriptional repressor Kaiso (ZBTB33) and activation of canonical Kaiso target genes. Here, we examined whether an anchorage-independent and ILC-specific transcriptional program correlated with clinical parameters in breast cancer. Based on the presence of a canonical Kaiso-binding consensus sequence (cKBS) in the promoters of genes that are upregulated under anchorage-independent conditions, we defined an ILC-specific anoikis resistance transcriptome (ART). Converting the ART genes into human orthologs and adding published Kaiso target genes resulted in the Kaiso-specific ART (KART) 33-gene signature, used subsequently to study correlations with histological and clinical variables in primary breast cancer. Using publicly available data for ERPOS Her2NEG breast cancer, we found that expression of KART was positively associated with the histological ILC breast cancer type (p < 2.7E-07). KART expression associated with younger patients in all invasive breast cancers and smaller tumors in invasive ductal carcinoma of no special type (IDC-NST) (<2 cm, p < 6.3E-10). We observed associations with favorable long-term prognosis in both ILC (hazard ratio [HR] = 0.51, 95% CI = 0.29-0.91, p < 3.4E-02) and IDC-NST (HR = 0.79, 95% CI = 0.66-0.93, p < 1.2E-04). Our analysis thus defines a new mRNA expression signature for human breast cancer based on canonical Kaiso target genes that are upregulated in E-cadherin deficient ILC. The KART signature may enable a deeper understanding of ILC biology and etiology. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Differential chromatin accessibility and transcriptional dynamics define breast cancer subtypes and their lineages

Breast cancer is a heterogeneous disease, and treatment is guided by biomarker profiles representing distinct molecular subtypes. Breast cancer arises from the breast ductal epithelium, and experimental data suggests breast cancer subtypes have different cells of origin within that lineage. The precise cells of origin for each subtype and the transcriptional networks that characterize these tumor-normal lineages are not established. In this work, we applied bulk, single-cell (sc), and single-nucleus (sn) multi-omic techniques as well as spatial transcriptomics and multiplex imaging on 61 samples from 37 breast cancer patients to show characteristic links in gene expression and chromatin accessibility between breast cancer subtypes and their putative cells of origin. We applied the PAM50 subtyping algorithm in tandem with bulk RNA-seq and snRNA-seq to reliably subtype even low-purity tumor samples and confirm promoter accessibility using snATAC. Trajectory analysis of chromatin accessibility and differentially accessible motifs clearly connected progenitor populations with breast cancer subtypes supporting the cell of origin for basal-like and luminal A and B tumors. Regulatory network analysis of transcription factors underscored the importance of BHLHE40 in luminal breast cancer and luminal mature cells, and KLF5 in basal-like tumors and luminal progenitor cells. Furthermore, we identify key genes defining the basal-like ( PRKCA , SOX6 , RGS6 , KCNQ3 ) and luminal A/B ( FAM155A , LRP1B ) lineages, with expression in both precursor and cancer cells and further upregulation in tumors. Exhausted CTLA4-expressing CD8+ T cells were enriched in basal-like breast cancer, suggesting altered means of immune dysfunction among breast cancer subtypes. We used spatial transcriptomics and multiplex imaging to provide spatial detail for key markers of benign and malignant cell types and immune cell colocation. These findings demonstrate analysis of paired transcription and chromatin accessibility at the single cell level is a powerful tool for investigating breast cancer lineage development and highlight transcriptional networks that define basal and luminal breast cancer lineages.

B-cells and regulatory T-cells in the microenvironment of HER2+ breast cancer are associated with decreased survival: a real-world analysis of women with HER2+ metastatic breast cancer

BACKGROUND

Despite major improvements in treatment of HER2-positive metastatic breast cancer (MBC), only few patients achieve complete remission and remain progression free for a prolonged time. The tumor immune microenvironment plays an important role in the response to treatment in HER2-positive breast cancer and could contain valuable prognostic information. Detailed information on the cancer-immune cell interactions in HER2-positive MBC is however still lacking. By characterizing the tumor immune microenvironment in patients with HER2-positive MBC, we aimed to get a better understanding why overall survival (OS) differs so widely and which alternative treatment approaches may improve outcome.

METHODS

We included all patients with HER2-positive MBC who were treated with trastuzumab-based palliative therapy in the Netherlands Cancer Institute between 2000 and 2014 and for whom pre-treatment tissue from the primary tumor or from metastases was available. Infiltrating immune cells and their spatial relationships to one another and to tumor cells were characterized by immunohistochemistry and multiplex immunofluorescence. We also evaluated immune signatures and other key pathways using next-generation RNA-sequencing data. With nine years median follow-up from initial diagnosis of MBC, we investigated the association between tumor and immune characteristics and outcome.

RESULTS

A total of 124 patients with 147 samples were included and evaluated. The different technologies showed high correlations between each other. T-cells were less prevalent in metastases compared to primary tumors, whereas B-cells and regulatory T-cells (Tregs) were comparable between primary tumors and metastases. Stromal tumor-infiltrating lymphocytes in general were not associated with OS. The infiltration of B-cells and Tregs in the primary tumor was associated with unfavorable OS. Four signatures classifying the extracellular matrix of primary tumors showed differential survival in the population as a whole.

CONCLUSIONS

In a real-world cohort of 124 patients with HER2-positive MBC, B-cells, and Tregs in primary tumors are associated with unfavorable survival. With this paper, we provide a comprehensive insight in the tumor immune microenvironment that could guide further research into development of novel immunomodulatory strategies.

Comprehensive analysis of the lncRNAs-related immune gene signatures and their correlation with immunotherapy in lung adenocarcinoma

BACKGROUND

Long non-coding RNAs (lncRNAs)-related immune genes (lrRIGs) play a crucial role in the development and progression of lung adenocarcinoma (LUAD). However, reliable prognostic signatures based on lrRIGs have not yet been identified.

METHODS

We screened lrRIGs associated with the prognosis of LUAD using The Cancer Genome Atlas (TCGA) database and then established a novel prognostic nine-gene signature composed of CD79A, INHA, SHC3, LIFR, TNFRSF11A, GPI, F2RL1, SEMA7A and WFDC2 through bioinformatic approaches. A risk score derived from this gene signature was used to divide LUAD patients into the low- and high-risk groups. The latter was confirmed to have markedly worse overall survival (O.S.). A nomogram was developed using the risk score and other independent prognostic elements, demonstrating excellent performance in predicting the O.S. rate of LUAD patients.

RESULTS

We observed that the infiltration of diverse immune cell subtypes and response to immunotherapy and chemotherapy significantly differed between the low- and high-risk groups.

CONCLUSIONS

Overall, stratification based on this gene signature could be used to guide better therapeutic management and improve outcomes for LUAD patients.

Systemic Therapy for Metastatic Triple Negative Breast Cancer: Current Treatments and Future Directions

Until recently, despite its heterogenous biology, metastatic triple negative breast cancer (TNBC) was treated as a single entity, with successive lines of palliative chemotherapy being the only systemic option. Significant gene expression studies have demonstrated the diversity of TNBC, but effective differential targeting of the four main (Basal-like 1 and 2, mesenchymal and luminal androgen receptor) molecular sub-types has largely eluded researchers. The introduction of immunotherapy, currently useful only for patients with PD-L1 positive cancers, led to the stratification of first-line therapy using this immunohistochemical biomarker. Germline BRCA gene mutations can also be targeted with PARP inhibitors in both the adjuvant and metastatic settings. In contrast, the benefit of the anti-Trop-2 antibody-drug conjugate (ADC) Sacituzumab govitecan (SG) does not appear confined to patients with tumours expressing high levels of Trop-2, leading to its potential utility for any patient with an estrogen receptor (ER)-negative, HER2-negative advanced breast cancer (ABC). Most recently, low levels of HER2 expression, detected in up to 60% of TNBC, predicts benefit from the potent HER2-directed antibody-drug conjugate trastuzumab deruxtecan (T-DXd), defining an additional treatment option for this sub-group. Regrettably, despite recent advances, the median survival of TNBC continues to lag far behind the approximately 5 years now expected for patients with ER-positive or HER2-positive breast cancers. We review the data supporting immunotherapy, ADCs, and targeted agents in subgroups of patients with TNBC, and current clinical trials that may pave the way to further advances in this challenging disease.

Characterization of the immune environment in pregnancy-associated breast cancer

Pregnancy-associated breast cancer (PrBC) is a rare and clinically challenging condition. Specific immune mechanisms and pathways are involved in maternal-fetal tolerance and tumor-host immunoediting. The comprehension of the molecular processes underpinning this immune synergy in PrBC is needed to improve patients' clinical management. Only a few studies focused on the immune biology of PrBC and attempted to identify bona fide biomarkers. Therefore, clinically actionable information remains extremely puzzling for these patients. In this review article, we discuss the current knowledge on the immune environment of PrBC, in comparison with pregnancy-unrelated breast cancer and in the context of maternal immune changes during pregnancy. A particular emphasis is given to the actual role of potential immune-related biomarkers for PrBC clinical management.

Expression-Based Diagnosis, Treatment Selection, and Drug Development for Breast Cancer

There is currently no gene expression assay that can assess if premalignant lesions will develop into invasive breast cancer. This study sought to identify biomarkers for selecting patients with a high potential for developing invasive carcinoma in the breast with normal histology, benign lesions, or premalignant lesions. A set of 26-gene mRNA expression profiles were used to identify invasive ductal carcinomas from histologically normal tissue and benign lesions and to select those with a higher potential for future cancer development (ADHC) in the breast associated with atypical ductal hyperplasia (ADH). The expression-defined model achieved an overall accuracy of 94.05% (AUC = 0.96) in classifying invasive ductal carcinomas from histologically normal tissue and benign lesions (n = 185). This gene signature classified cancer development in ADH tissues with an overall accuracy of 100% (n = 8). The mRNA expression patterns of these 26 genes were validated using RT-PCR analyses of independent tissue samples (n = 77) and blood samples (n = 48). The protein expression of PBX2 and RAD52 assessed with immunohistochemistry were prognostic of breast cancer survival outcomes. This signature provided significant prognostic stratification in The Cancer Genome Atlas breast cancer patients (n = 1100), as well as basal-like and luminal A subtypes, and was associated with distinct immune infiltration and activities. The mRNA and protein expression of the 26 genes was associated with sensitivity or resistance to 18 NCCN-recommended drugs for treating breast cancer. Eleven genes had significant proliferative potential in CRISPR-Cas9/RNAi screening. Based on this gene expression signature, the VEGFR inhibitor ZM-306416 was discovered as a new drug for treating breast cancer.

Identification of immunosuppressive signature subtypes and prognostic risk signatures in triple-negative breast cancer

Purpose

Immune checkpoint blockade (ICB) therapy has transformed the treatment of triple-negative breast cancer (TNBC) in recent years. However, some TNBC patients with high programmed death-ligand 1 (PD-L1) expression levels develop immune checkpoint resistance. Hence, there is an urgent need to characterize the immunosuppressive tumor microenvironment and identify biomarkers to construct prognostic models of patient survival outcomes in order to understand biological mechanisms operating within the tumor microenvironment.

Patients and methods

RNA sequence (RNA-seq) data from 303 TNBC samples were analyzed using an unsupervised cluster analysis approach to reveal distinctive cellular gene expression patterns within the TNBC tumor microenvironment (TME). A panel of T cell exhaustion signatures, immunosuppressive cell subtypes and clinical features were correlated with the immunotherapeutic response, as assessed according to gene expression patterns. The test dataset was then used to confirm the occurrence of immune depletion status and prognostic features and to formulate clinical treatment recommendations. Concurrently, a reliable risk prediction model and clinical treatment strategy were proposed based on TME immunosuppressive signature differences between TNBC patients with good versus poor survival status and other clinical prognostic factors.

Results

Significantly enriched TNBC microenvironment T cell depletion signatures were detected in the analyzed RNA-seq data. A high proportion of certain immunosuppressive cell subtypes, 9 inhibitory checkpoints and enhanced anti-inflammatory cytokine expression profiles were noted in 21.4% of TNBC patients that led to the designation of this group of immunosuppressed patients as the immune depletion class (IDC). Although IDC group TNBC samples contained tumor-infiltrating lymphocytes present at high densities, IDC patient prognosis was poor. Notably, PD-L1 expression was relatively elevated in IDC patients that indicated their cancers were resistant to ICB treatment. Based on these findings, a set of gene expression signatures predicting IDC group PD-L1 resistance was identified then used to develop risk models for use in predicting clinical therapeutic outcomes.

Conclusion

A novel TNBC immunosuppressive tumor microenvironment subtype associated with strong PD-L1 expression and possible resistance to ICB treatment was identified. This comprehensive gene expression pattern may provide fresh insights into drug resistance mechanisms for use in optimizing immunotherapeutic approaches for TNBC patients.

Identification of Breast Cancer Subtypes by Integrating Genomic Analysis with the Immune Microenvironment

Objectives: We aim to identify the breast cancer (BC) subtype clusters and the crucial gene classifier prognostic signatures by integrating genomic analysis with the tumor immune microenvironment (TME). Methods: Data sets of BC were derived from the Cancer Genome Atlas (TCGA), METABRIC, and Gene Expression Omnibus (GEO) databases. Unsupervised consensus clustering was carried out to obtain the subtype clusters of BC patients. Weighted gene coexpression network analysis (WGCNA), least absolute shrinkage and selection operator (LASSO), and univariate and multivariate regression analysis were employed to obtain the gene classifier signatures and their biological functions, which were validated by the BC dataset from the METABRIC database. Additionally, to evaluate the overall survival rates of BC patients, Kaplan-Meier survival analysis was carried out. Moreover, to assess how BC subtype clusters are related to the TME, single-cell analysis was performed. Finally, the drug sensitivity and the immune cell infiltration for different phenotypes of BC patients were also calculated by the CIBERSORT and ESTIMATE algorithms. Results : TCGA-BC samples were divided into three subtype clusters, S1, S2, and S3, among which the prognosis of S2 was poor and that of S1 and S3 were better. Three key pathways and 10 crucial prognostic-related gene signatures are screened. Finally, single-cell analysis suggests that S1 samples have the most types of immune cells, S2 with more sensitivity to tumor treatment drugs are enriched with more neutrophils, and more multilymphoid progenitor cells are involved in subtype cluster S3. Conclusions: Our novelty was to identify the BC subtype clusters and the gene classifier signatures employing a large-amount dataset combined with multiple bioinformatics methods. All of the results provide a basis for clinical precision treatment of BC.

Relationship between tumor microbiota transcriptional activity and gene expression in breast cancer

BACKGROUND

A few studies have reported the distribution of the microbiota in breast cancer tissues, but few reports have compared the microbiota in different subtypes of breast cancer tissue. Moreover, no study has reported on the relationship between the microbiota and gene expression in breast tumor.

METHODS

Sections of formalin-fixed paraffin-embedded (FFPE) tissue were prepared from the breast tumors of 70 patients and were subjected to microarray analysis to identify gene expression profiles. The same total RNA samples were also used to analyze the microbiota activity in tumor tissues by performing 16 S rRNA sequencing and internal transcribed spacer (ITS) sequencing of reverse transcript cDNA with Illumina Miseq. Pearson's correlation coefficient was used for calculating the correlation between microbial relative activity and gene expression.

RESULTS

The microbiota transcriptional activity of 70 FFPE samples mainly consisted of the phyla Bacteroidetes, Firmicutes and Proteobacteria. Prevotella_9, Bacteroides and Alloprevotella were the most active genera in ER+/HER2-, ER+/HER2 + and ER-/HER2 + tumors, while triple-negative samples exhibited a higher activity of Lactobacillus. In ER-negative samples (triple-negative and ER-/HER2+), 479 genes, including the breast carcinogenesis genes phospholipase A2, histone cluster 2, Crk-like, and cyclin D1, were significantly positive associated with the activity of Lactobacillus.

CONCLUSION

This was the first study to clarify an association between the breast tumor microbiota transcriptional activity and the expression of carcinogenesis genes in ER-negative breast cancer. Changes in the microbiota of breast tissue induced by external factors might be one of the key causes of ER negative breast cancer.

Single-cell and spatial transcriptome analyses revealed cell heterogeneity and immune environment alternations in metastatic axillary lymph nodes in breast cancer

BACKGROUND

Tumor heterogeneity plays essential roles in developing cancer therapies, including therapies for breast cancer (BC). In addition, it is also very important to understand the relationships between tumor microenvironments and the systematic immune environment.

METHODS

Here, we performed single-cell, VDJ sequencing and spatial transcriptome analyses on tumor and adjacent normal tissue as well as axillar lymph nodes (LNs) and peripheral blood mononuclear cells (PBMCs) from 8 BC patients.

RESULTS

We found that myeloid cells exhibited environment-dependent plasticity, where a group of macrophages with both M1 and M2 signatures possessed high tumor specificity spatially and was associated with worse patient survival. Cytotoxic T cells in tumor sites evolved in a separate path from those in the circulatory system. T cell receptor (TCR) repertoires in metastatic LNs showed significant higher consistency with TCRs in tumor than those in nonmetastatic LNs and PBMCs, suggesting the existence of common neo-antigens across metastatic LNs and primary tumor cites. In addition, the immune environment in metastatic LNs had transformed into a tumor-like status, where pro-inflammatory macrophages and exhausted T cells were upregulated, accompanied by a decrease in B cells and neutrophils. Finally, cell interactions showed that cancer-associated fibroblasts (CAFs) contributed most to shaping the immune-suppressive microenvironment, while CD8⁺ cells were the most signal-responsive cells.

CONCLUSIONS

This study revealed the cell structures of both micro- and macroenvironments, revealed how different cells diverged in related contexts as well as their prognostic capacities, and displayed a landscape of cell interactions with spatial information.

Immunotherapy in breast cancer: an overview of current strategies and perspectives

Recent progress in immunobiology has led the way to successful host immunity enhancement against breast cancer. In triple-negative breast cancer, the combination of cancer immunotherapy based on PD-1/PD-L1 immune checkpoint inhibitors with chemotherapy was effective both in advanced and early setting phase 3 clinical trials. These encouraging results lead to the first approvals of immune checkpoint inhibitors in triple-negative breast cancer and thus offer new therapeutic possibilities in aggressive tumors and hard-to-treat populations. Furthermore, several ongoing trials are investigating combining immunotherapies involving immune checkpoint inhibitors with conventional therapies and as well as with other immunotherapeutic strategies such as cancer vaccines, CAR-T cells, bispecific antibodies, and oncolytic viruses in all breast cancer subtypes. This review provides an overview of immunotherapies currently under clinical development and updated key results from clinical trials. Finally, we discuss the challenges to the successful implementation of immune treatment in managing breast cancer and their implications for the design of future clinical trials.

Upregulated X-C motif chemokine ligand 2 (XCL2) is associated with poor prognosis and increased immune infiltration in clear cell renal cell carcinoma

BACKGROUND

Clear cell renal cell carcinoma (ccRCC) is one of the most popular malignant carcinomas in the genitourinary system. As a novel tumor-related gene, X-C Motif Chemokine Ligand 2 (XCL2) was up-regulated in ccRCC. The current study aims to reveal the functional activity of XCL2 in ccRCC.

METHODS

The transcriptome profiling, clinical parameters, and simple nucleotide variation profiles of ccRCC samples were obtained from the Cancer Genome Atlas (TCGA) database. The survival analysis, multivariate/univariate Cox analysis, correlation analysis, gene set enrichment analysis (GSEA), and tumor mutation burden (TMB) analysis were performed. Next, immune cell infiltration and immune functions were analyzed. Finally, the functions of XCL2 were investigated in Caki-1 and 786-O cells.

RESULTS

Upregulated XCL2 was associated with worse overall survival of ccRCC and correlated to age, grade, stage, and T stage. Age, grade, and XCL2 were independent prognostic factors. Significant enrichment in apoptosis, DNA replication, and immune response was demonstrated by GSEA. XCL2 was not only tightly associated with immune cell infiltration, but also significantly linked with several immune functions. Moreover, patients, who had higher XCL2 expression, owned higher levels of TMB. Interestingly, XCL2 was positively correlated with common immune checkpoints. In vitro, XCL2 could inhibit apoptosis, and promote proliferation, migration, invasion, and epithelial-mesenchymal transition (EMT) of Caki-1 and 786-O cells.

CONCLUSIONS

In general, the current study suggested that XCL2 may participate in the progression of ccRCC. Importantly, XCL2 may be a potential new target of immunotherapy.

Targeting the stage-specific embryonic antigen (SSEA)-0 tumor neoantigen

Recognition of abnormal glycosylation in virtually any cancer type has raised a great interest in the glycan-based tumor biomarkers. Our team explored carbohydrate microarrays as a broad-spectrum immunoassay to probe the immunologically potent tumor glycan targets. This effort has led to the identification of a blood group precursor antigen SSEA-0 as a conserved breast cancer (BCA) marker. Since this immunogenic O-core glycan is normally hidden as a cryptic antigen but becomes overexpressed and surface-exposed by metastatic breast cancer cells (MBCA), its potential as a novel immunological target for precision immunotherapy against tumor metastasis warrants a focused investigation.

Expression and Signaling Pathways of Nerve Growth Factor (NGF) and Pro-NGF in Breast Cancer: A Systematic Review

Breast cancer represents the most common type of cancer and is the leading cause of death due to cancer among women. Thus, the prevention and early diagnosis of breast cancer is of primary urgency, as well as the development of new treatments able to improve its prognosis. Nerve Growth Factor (NGF) is a neurotrophic factor involved in the regulation of neuronal functions through the binding of the Tropomyosin receptor kinase A (TrkA) and the Nerve Growth Factor receptor or Pan-Neurotrophin Receptor 75 (NGFR/p75NTR). In addition, its precursor (pro-NGF) can extert biological activity by forming a trimeric complex with NGFR/p75NTR and sortilin, or by binding to TrkA receptors with low affinity. Several examples of in vitro and in vivo evidence show that NGF is both synthesized and released by breast cancer cells, and has mitogen, antiapoptotic and angiogenic effects on these cells through the activation of different signaling cascades that involve TrkA and NGFR/p75NTR receptors. Conversely, pro-NGF signaling has been related to breast cancer invasion and metastasis. Other studies suggested that NGF and its receptors could represent a good diagnostic and prognostic tool, as well as promising therapeutic targets for breast cancer. In this paper, we comprehensively summarize and systematically review the current experimental evidence on this topic. INPLASY ID: INPLASY2022100017.

Identification of a prognostic risk-scoring model and risk signatures based on glycosylation-associated cluster in breast cancer

Breast cancer is a heterogeneous disease whose subtypes represent different histological origins, prognoses, and therapeutic sensitivity. But there remains a strong need for more specific biomarkers and broader alternatives for personalized treatment. Our study classified breast cancer samples from The Cancer Genome Atlas (TCGA) into three groups based on glycosylation-associated genes and then identified differentially expressed genes under different glycosylation patterns to construct a prognostic model. The final prognostic model containing 23 key molecules achieved exciting performance both in the TCGA training set and testing set GSE42568 and GSE58812. The risk score also showed a significant difference in predicting overall clinical survival and immune infiltration analysis. This work helped us to understand the heterogeneity of breast cancer from another perspective and indicated that the identification of risk scores based on glycosylation patterns has potential clinical implications and immune-related value for breast cancer.

Prognostic and Predictive Significance of Stromal Tumor-Infiltrating Lymphocytes (sTILs) in ER-Positive/HER2-Negative Postmenopausal Breast Cancer Patients

The clinical impact of tumor-infiltrating lymphocytes (TILs) is less known for breast cancer patients with the estrogen receptor-positive (ER+)/human epidermal growth factor receptor-negative (HER−) subtype. Here, we explored the prognostic and predictive value of TILs regarding distant recurrence-free interval (DRFI) and breast cancer-specific survival (BCSS) in 763 postmenopausal patients randomized to receive tamoxifen vs. no systemic treatment. TILs were assessed in whole section tumor samples stained with H&E and divided into low (<10%), intermediate (10−39%), or high (≥40%). High TILs were associated with poor prognostic variables and good prognoses for all patients, but not within the ER+/HER2− group. Within the ER+/HER2− group, high gene expression of CD19 and PD-L1 and high IMMUNE1 score indicated good prognosis in multivariable analysis while high CD8 and CD19 gene expression and high IMMUNE1 score were associated with less tamoxifen benefit. These results indicate that within the ER+/HER2− subtype there could be subsets of patients where expression of specific TIL markers might be used to reveal candidates for immune therapy interventions upon failure of the endocrine therapy.

Recursive integration of synergised graph representations of multi-omics data for cancer subtypes identification

Cancer subtypes identification is one of the critical steps toward advancing personalized anti-cancerous therapies. Accumulation of a massive amount of multi-platform omics data measured across the same set of samples provides an opportunity to look into this deadly disease from several views simultaneously. Few integrative clustering approaches are developed to capture shared information from all the views to identify cancer subtypes. However, they have certain limitations. The challenge here is identifying the most relevant feature space from each omic view and systematically integrating them. Both the steps should lead toward a global clustering solution with biological significance. In this respect, a novel multi-omics clustering algorithm named RISynG (Recursive Integration of Synergised Graph-representations) is presented in this study. RISynG represents each omic view as two representation matrices that are Gramian and Laplacian. A parameterised combination function is defined to obtain a synergy matrix from these representation matrices. Then a recursive multi-kernel approach is applied to integrate the most relevant, shared, and complementary information captured via the respective synergy matrices. At last, clustering is applied to the integrated subspace. RISynG is benchmarked on five multi-omics cancer datasets taken from The Cancer Genome Atlas. The experimental results demonstrate RISynG’s efficiency over the other approaches in this domain.

Prognostic Capability of TNBC 3-Gene Score among Triple-Negative Breast Cancer Subtypes

Background: Triple-negative breast cancer (TNBC) is a complex and molecularly heterogeneous entity, with the poorest outcome compared with other breast cancer subtypes. Previously, we developed a TNBC 3-gene score with a significant prognostic capability. This study aims to test the 3-gene score in the different TNBC subtypes. Methods: Data from 204 TNBC patients treated with neoadjuvant chemotherapy were retrieved from public datasets and pooled (GSE25066, GSE58812, and GSE16446). After removing batch effects, cases were classified into Lehman’s TNBC subtypes and then the TNBC 3-gene score was used to evaluate the risk of distant recurrence in each subgroup. In addition, the association with tumor-infiltrating lymphocyte (TILs) levels was evaluated in a retrospective group of 72 TNBC cases. Results: The TNBC 3-gene score was able to discriminate patients with different risks within the pooled cohort (HR = 2.41 for high vs. low risk; 95%CI: 1.50−3.86). The score showed predictive capability in the immunomodulatory subtype (HR = 4.16; 95%CI: 1.63−10.60) and in the mesenchymal stem-like subtype (HR = 18.76; 95%CI: 1.68−208.97). In the basal-like 1, basal-like-2, and mesenchymal subtypes, the observed differential risk patterns showed no statistical significance. The score had poor predictive capability in the luminal androgen receptor subtype (p = 0.765). In addition, a low TNBC 3-gene score was related to a high level of TIL infiltration (p < 0.001). Conclusions: The TNBC 3-gene score is able to predict the risk of distant recurrence in TNBC patients, specifically in the immunomodulatory and mesenchymal stem-like subtype. Despite a small sample size in each subgroup, an improved prognostic capability was seen in TNBC subtypes with tumor-infiltrating components.

Clustering Molecular Subtypes in Breast Cancer, Immunohistochemical Parameters and Risk of Axillary Nodal Involvement

(1) Background: To establish similarities in the risk of axillary lymph node metastasis between different groups of women with breast cancer according to immunohistochemical (IHC) parameters. (2) Methods: Data was collected retrospectively, from 2000 to 2013, of 1058 node-positive breast tumours. All patients were divided according to the St Gallen 2013 criteria and IHC features. The proportion of axillary involvement (pN > pN0; pN > pN1mi; pN > pN1) was calculated for each group. Similarities in axillary nodal dissemination were explored by cluster analysis and association between IHC and risk of axillary disease was studied with multivariate analysis. (3) Results: Among clinico-pathological surrogates of intrinsic subtypes, axillary involvement was more frequent in Luminal-B like HER2 negative (45.8%) and less frequent in Luminal-B HER2 positive (33.8%; p = 0.044). Axillary macroscopic involvement was more frequent in Luminal-B like HER2 negative (37.9%) and HER2 positive (37.8%) and less frequent in Luminal-B HER2 positive (25.5%) and Luminal-A like (25.6%; p = 0.002). Axillary involvement ≥pN2 was significantly less frequent in Luminal-A like (7.4%; p < 0.001). Luminal-A with Luminal-B HER2 positive, and triple-negative with Erb-B2 overexpressing tumours were clustered together regarding any axillary involvement, macroscopic disease or ≥pN2. Among the defined subgroups, axillary metastases were more frequent when Ki67 was higher. In a multivariate analysis, Ki67>14% were associated with a risk of axillary metastases (HR: 1.31; 95% CI, 1.51−6.80; p < 0.037). (4) Conclusions: there are two lymphatic drainage pathways of the breast according to the expression of hormone receptor-related genes. Positive-ER tumors are associated with lower axillary involvement and negative-ER tumors and Ki67 > 14% with higher nodal involvement.

Accurate determination of CRISPR-mediated gene fitness in transplantable tumours

Assessing tumour gene fitness in physiologically-relevant model systems is challenging due to biological features of in vivo tumour regeneration, including extreme variations in single cell lineage progeny. Here we develop a reproducible, quantitative approach to pooled genetic perturbation in patient-derived xenografts (PDXs), by encoding single cell output from transplanted CRISPR-transduced cells in combination with a Bayesian hierarchical model. We apply this to 181 PDX transplants from 21 breast cancer patients. We show that uncertainty in fitness estimates depends critically on the number of transplant cell clones and the variability in clone sizes. We use a pathway-directed allelic series to characterize Notch signaling, and quantify TP53 / MDM2 drug-gene conditional fitness in outlier patients. We show that fitness outlier identification can be mirrored by pharmacological perturbation. Overall, we demonstrate that the gene fitness landscape in breast PDXs is dominated by inter-patient differences.

Potential of chimeric antigen receptor (CAR)-redirected immune cells in breast cancer therapies: Recent advances

Despite substantial developments in conventional treatments such as surgery, chemotherapy, radiotherapy, endocrine therapy, and molecular-targeted therapy, breast cancer remains the leading cause of cancer mortality in women. Currently, chimeric antigen receptor (CAR)-redirected immune cell therapy has emerged as an innovative immunotherapeutic approach to ameliorate survival rates of breast cancer patients by eliciting cytotoxic activity against cognate tumour-associated antigens expressing tumour cells. As a crucial component of adaptive immunity, T cells and NK cells, as the central innate immune cells, are two types of pivotal candidates for CAR engineering in treating solid malignancies. However, the biological distinctions between NK cells- and T cells lead to differences in cancer immunotherapy outcomes. Likewise, optimal breast cancer removal via CAR-redirected immune cells requires detecting safe target antigens, improving CAR structure for ideal immune cell functions, promoting CAR-redirected immune cells filtration to the tumour microenvironment (TME), and increasing the ability of these engineered cells to persist and retain within the immunosuppressive TME. This review provides a concise overview of breast cancer pathogenesis and its hostile TME. We focus on the CAR-T and CAR-NK cells and discuss their significant differences. Finally, we deliver a summary based on recent advancements in the therapeutic capability of CAR-T and CAR-NK cells in treating breast cancer.

CISH Expression Is Associated with Metastasis-Free Interval in Triple-Negative Breast Cancer and Refines the Prognostic Value of PDL1 Expression

Strategies are being explored to increase the efficiency of immune checkpoint inhibitors (ICIs) targeting PD1/PDL1 in triple-negative breast cancer (TNBC), including combination with therapies inhibiting intracellular immune checkpoints such as CISH (Cytokine-induced SH2 protein). Correlation between CISH expression and TNBC features is unknown. We retrospectively analyzed CISH expression in 1936 clinical TNBC samples and searched for correlations with clinical variables, including metastasis-free interval (MFI). Among TNBCs, 44% were identified as "CISH-up" and 56% "CISH-down". High expression was associated with pathological axillary lymph node involvement, more adjuvant chemotherapy, and Lehmann's immunomodulatory and luminal AR subtypes. The "CISH-up" class showed longer 5-year MFI (72%) than the "CISH-down" class (60%; p = 2.8 × 10-2). CISH upregulation was associated with activation of IFNα and IFNγ pathways, antitumor cytotoxic immune response, and signatures predictive for ICI response. When CISH and PDL1 were upregulated together, the 5-year MFI was 81% versus 52% when not upregulated (p = 6.21 × 10-6). The two-gene model provided more prognostic information than each gene alone and maintained its prognostic value in multivariate analysis. CISH expression is associated with longer MFI in TNBC and refines the prognostic value of PDL1 expression. Such observation might reinforce the therapeutic relevance of combining CISH inhibition with an anti-PD1/PDL1 ICI.

A pan-tissue DNA methylation atlas enables in silico decomposition of human tissue methylomes at cell-type resolution

Bulk-tissue DNA methylomes represent an average over many different cell types, hampering our understanding of cell-type-specific contributions to disease development. As single-cell methylomics is not scalable to large cohorts of individuals, cost-effective computational solutions are needed, yet current methods are limited to tissues such as blood. Here we leverage the high-resolution nature of tissue-specific single-cell RNA-sequencing datasets to construct a DNA methylation atlas defined for 13 solid tissue types and 40 cell types. We comprehensively validate this atlas in independent bulk and single-nucleus DNA methylation datasets. We demonstrate that it correctly predicts the cell of origin of diverse cancer types and discovers new prognostic associations in olfactory neuroblastoma and stage 2 melanoma. In brain, the atlas predicts a neuronal origin for schizophrenia, with neuron-specific differential DNA methylation enriched for corresponding genome-wide association study risk loci. In summary, the DNA methylation atlas enables the decomposition of 13 different human tissue types at a high cellular resolution, paving the way for an improved interpretation of epigenetic data.

This resource presents an in silico generated DNA methylation atlas that can be used for cell-type deconvolution of human tissues.

Comparative analysis of molecular signatures reveals a hybrid approach in breast cancer: Combining the Nottingham Prognostic Index with gene expressions into a hybrid signature

The diagnosis of breast cancer—including determination of prognosis and prediction—has been traditionally based on clinical and pathological characteristics such as tumor size, nodal status, and tumor grade. The decision-making process has been expanded by the recent introduction of molecular signatures. These signatures, however, have not reached the highest levels of evidence thus far. Yet they have been brought to clinical practice based on statistical significance in prospective as well as retrospective studies. Intriguingly, it has also been reported that most random sets of genes are significantly associated with disease outcome. These facts raise two highly relevant questions: What information gain do these signatures procure? How can one find a signature that is substantially better than a random set of genes? Our study addresses these questions. To address the latter question, we present a hybrid signature that joins the traditional approach with the molecular one by combining the Nottingham Prognostic Index with gene expressions in a data-driven fashion. To address the issue of information gain, we perform careful statistical analysis and comparison of the hybrid signature, gene expression lists of two commercially available tests as well as signatures selected at random, and introduce the Signature Skill Score—a simple measure to assess improvement on random signatures. Despite being based on in silico data, our research is designed to be useful for the decision-making process of oncologists and strongly supports association of random signatures with outcome. Although our study shows that none of these signatures can be considered as the main candidate for providing prognostic information, it also demonstrates that both the hybrid signature and the gene expression list of the OncotypeDx signature identify patients who may not require adjuvant chemotherapy. More importantly, we show that combining signatures substantially improves the identification of patients who do not need adjuvant chemotherapy.

Clinical and Molecular Characteristics of ER-Positive Ultralow Risk Breast Cancer Tumors Identified by the 70-Gene Signature

The metastatic potential of estrogen receptor (ER)-positive breast cancers is heterogenous and distant recurrences occur months to decades after primary diagnosis. We have previously shown that patients with tumors classified as ultralow risk by the 70-gene signature have a minimal long-term risk of fatal breast cancer. Here, we evaluate the previously unexplored underlying clinical and molecular characteristics of ultralow risk tumors in 538 ER-positive patients from the Stockholm tamoxifen randomized trial (STO-3). Out of the 98 ultralow risk tumors, 89% were luminal A molecular subtype, whereas 26% of luminal A tumors were of ultralow risk. Compared with other ER-positive tumors, ultralow risk tumors were significantly (Fisher's test, P<0.05) more likely to be of smaller tumor size, lower grade, progesterone receptor (PR)-positive, human epidermal growth factor 2 (HER2)-negative and have low Ki-67 levels (proliferation-marker). Moreover, ultralow risk tumors showed significantly lower expression scores of multi-gene modules associated with the AKT/mTOR-pathway, proliferation (AURKA), HER2/ERBB2-signaling, IGF1-pathway, PTEN-loss, and immune response (IMMUNE1 and IMMUNE2), and higher expression scores of the PIK3CA-mutation-associated module. Furthermore, 706 genes were significantly (FDR<0.001) differentially expressed in ultralow risk tumors, including lower expression of genes involved in immune response, PI3K/Akt/mTOR-pathway, histones, cell cycle, DNA repair, apoptosis, and higher expression of genes coding for epithelial-to-mesenchymal transition, and homeobox proteins, among others. In conclusion, ultralow risk tumors, associated with minimal long-term risk of fatal disease, differ from other ER-positive tumors, including luminal A molecular subtype tumors. Identification of these characteristics is important to improve our prediction of non-fatal versus fatal breast cancer. This article is protected by copyright. All rights reserved.

A Novel IGLC2 Gene Linked With Prognosis of Triple-Negative Breast Cancer

BACKGROUND

Immunoglobulin-related genes are associated with the favorable prognosis of triple-negative breast cancer (TNBC) patients. We aimed to analyze the function and prognostic value of immunoglobulin lambda constant 2 (IGLC2) in TNBC patients.

METHODS

We knocked down the gene expression of IGLC2 (IGLC2-KD) in MDA-MB-231 cells to evaluate the proliferation, migration, and invasion of tumors via 3-(4,5-Dimethythiazol-2-yl)-2,5-diphenyl tetrazolium bromide assay, wound healing, and transwell cell migration assay respectively. Relapse-free survival (RFS) and distant metastasis-free survival (DMFS) analyses were conducted using the KM plotter online tool. The GSE76275 data set was used to analyze the association of IGLC2 and clinical characteristics. A pathway enrichment analysis was conducted using the next-generation sequencing data of wild-type and IGLC2-KD MDA-MB-231 cells.

RESULTS

The low gene expression of IGLC2 was related to unfavorable RFS, DMFS. The high expression of IGLC2 was exhibited in the basal-like immune-activated (BLIA) TNBC molecular subtype, which was immune-activated and showed excellent response to immune therapy. IGLC2 was positively correlated with programmed death-ligand 1 (PD-L1) as shown by Spearman correlation (r = 0.25, p < 0.0001). IGLC2 had a strong prognostic effect on lymph node-negative TNBC (RFS range: 0.31, q value= 8.2e-05; DMFS = 0.16, q value = 8.2e-05) but had no significance on lymph node-positive ones. The shRNA-mediated silencing of IGLC2 increased the proliferation, migration, and invasion of MDA-MB-231 cells. The results of pathway enrichment analysis showed that IGLC2 is related to the PI3K-Akt signaling pathway, MAPK signaling pathway, and extracellular matrix-receptor interaction. We confirmed that MDA-MB-231 tumor cells expressed IGLC2, subverting the traditional finding of generation by immune cells.

CONCLUSIONS

IGLC2 linked with the proliferation, migration, and invasion of MDA-MB-231 cells. A high expression of IGLC2 was related to favorable prognosis for TNBC patients. IGLC2 may serve as a biomarker for the identification of TNBC patients who can benefit the most from immune checkpoint blockade treatment.

Gene Expression Profiling in Early Breast Cancer-Patient Stratification Based on Molecular and Tumor Microenvironment Features

Patients with early-stage hormone receptor-positive, human epidermal growth factor receptor 2-negative (HER2−) breast cancer (BC) are typically treated with surgery, followed by adjuvant systemic endocrine therapy with or without adjuvant chemotherapy and radiation therapy. Current guidelines regarding the use of adjuvant systemic therapy depend on clinical and pathological factors, such as the morphological assessment of tumor subtype; histological grade; tumor size; lymphovascular invasion; and lymph node status combined with estrogen receptor, progesterone receptor, and HER2 biomarker profiles assessed using immunohistochemistry and in situ hybridization. Additionally, the prognostic and predictive value of tumor-infiltrating lymphocytes and their composition is emerging as a key marker in triple negative (TNBC) and HER2-enriched molecular breast tumor subtypes. However, all these factors do not necessarily reflect the molecular heterogeneity and complexity of breast cancer. In the last two decades, gene expression signatures or profiling (GEP) tests have been developed to predict the risk of disease recurrence and estimate the potential benefit of receiving adjuvant systemic chemotherapy in patients with luminal breast cancer. GEPs have been utilized to help physicians to refine decision-making process, complementing clinicopathological parameters, and can now be used to classify the risk of recurrence and tailoring personalized treatments. Several clinical trials using GEPs validate the increasing value of such assays in different clinical settings, addressing relevant clinical endpoints. Finally, the recent approval of immune checkpoint inhibitors in TNBC and the increasing use of immunotherapy in different molecular BC populations highlight the opportunity to refine current GEPs by including a variety of immune-related genes that may help to improve predicting drug response and finetune prognosis.

Immunologic constant of rejection signature is prognostic in soft-tissue sarcoma and refines the CINSARC signature

BACKGROUND

Soft-tissue sarcomas (STSs) are heterogeneous and aggressive tumors, with high metastatic risk. The immunologic constant of rejection (ICR) 20-gene signature is a signature of cytotoxic immune response. We hypothesized that ICR might improve the prognostic assessment of early-stage STS.

METHODS

We retrospectively applied ICR to 1455 non-metastatic STS and searched for correlations between ICR classes and clinicopathological and biological variables, including metastasis-free survival (MFS).

RESULTS

Thirty-four per cent of tumors were classified as ICR1, 27% ICR2, 24% ICR3, and 15% ICR4. These classes were associated with patients' age, pathological type, and tumor depth, and an enrichment from ICR1 to ICR4 of quantitative/qualitative scores of immune response. ICR1 class was associated with a 59% increased risk of metastatic relapse when compared with ICR2-4 class. In multivariate analysis, ICR classification remained associated with MFS, as well as pathological type and Complexity Index in Sarcomas (CINSARC) classification, suggesting independent prognostic value. A prognostic clinicogenomic model, including the three variables, was built in a learning set (n=339) and validated in an independent set (n=339), showing greater prognostic precision than each variable alone or in doublet. Finally, connectivity mapping analysis identified drug classes potentially able to reverse the expression profile of poor-prognosis tumors, such as chemotherapy and targeted therapies.

CONCLUSION

ICR signature is independently associated with postoperative MFS in early-stage STS, independently from other prognostic features, including CINSARC. We built a robust prognostic clinicogenomic model integrating ICR, CINSARC, and pathological type, and suggested differential vulnerability of each prognostic group to different systemic therapies.

Identification of solute carrier family genes related to the prognosis and tumor-infiltrating immune cells of pancreatic ductal adenocarcinoma

Background

Pancreatic ductal adenocarcinoma (PDAC) has persisted as one of the worst prognostic tumors with a 5-year survival rate of lower than 6%. Although many studies have investigated PDAC, new biomarkers are required to ensure early diagnosis and predict the prognosis of PDAC.

Methods

In this study, we used bioinformatics methods to evaluate differences in the expression of solute carrier (SLC) family genes in tumors and non-tumors. A Kaplan-Meier analysis, least absolute shrinkage and selection operator (LASSO) analysis, and multivariate Cox proportional hazards regression analysis were used to evaluate the relationship between SLC genes and prognosis using The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets. The prognostic signature was constructed depending on the risk score to assess the impact of multiple genes on the prognosis, receiver operating characteristic (ROC) curves and forest plot was constructed to assess the ability to predict the prognosis and effects of clinical variables in both high- and low-risk groups. Tumor-infiltrating immune cells were evaluated using Cell-type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT) in both high- and low-risk groups.

Results

In 32 SLC genes, 9 were significantly associated with the OS after LASSO analysis. SLC19A3 (P=0.007), SLC25A39 (P=0.027), SLC39A11 (P=0.043) were significantly associated with prognosis and included into the prognostic model. CIBERSORT demonstrated that memory B cells (P=0.004), naive B cells (P=0.007), CD8 T cells (P=0.003), activated memory CD4 T cells (P=0.004), and activated NK cells (P=0.019) were significantly higher in the low-risk group. Gene set enrichment analysis (GSEA) showed that potential molecular mechanisms enriched in MYC and p53 signaling pathways.

Conclusions

SLC19A3, SLC25A35, and SLC39A11 were significantly relative to the prognosis of PDAC and changed the tumor microenvironment, as well as the MYC and p53 signaling pathways. The SLC19A3 gene may represent a new tumor suppressor in PDAC.

Development of a 15-Gene Signature Model as a Prognostic Tool in Sex Hormone-Dependent Cancers

Sex hormone dependence is associated with tumor progression and prognosis. Here, we explored the molecular basis of luminal A-like phenotype in sex hormone-dependent cancers. RNA-sequencing data from 8 cancer types were obtained from The Cancer Genome Atlas (TCGA). We investigated the enrichment function of differentially expressed genes (DEGs) in luminal A breast cancer (BRCA). Weighted coexpression network analysis (WGCNA) was used to identify gene modules associated with the luminal A-like phenotype, and we calculated the module's preservation in 8 cancer types. Module hub genes screened using least absolute shrinkage and selection operator (LASSO) were used to construct a gene signature model for the luminal A-like phenotype, and we assessed the model's relationship with prognosis, enriched pathways, and immune infiltration using bioinformatics approaches. Compared to other BRCA subtypes, the enrichment functions of upregulated genes in luminal A BRCA were related to hormone biological processes and receptor activity, and the downregulated genes were associated with the cell cycle and nuclear division. A gene module significantly associated with luminal A BRCA was shared by uterine corpus endometrial carcinoma (UCEC), leading to a similar phenotype. Fifteen hub genes were used to construct a gene signature model for the assessment of the luminal A-like phenotype, and the corrected C-statistics and Brier scores were 0.986 and 0.023, respectively. Calibration plots showed good performance, and decision curve analysis indicated a high net benefit of the model. The 15-gene signature model was associated with better overall survival in BRCA and UCEC and was characterized by downregulation of DNA replication, cell cycle and activated CD4 T cells. In conclusion, our study elucidated that BRCA and UCEC share a similar sex hormone-dependent phenotype and constructed a 15-gene signature model for use as a prognostic tool to quantify the probability of the phenotype.

Cellular dormancy in minimal residual disease following targeted therapy

BACKGROUND

Breast cancer mortality is principally due to tumor recurrence, which can occur following extended periods of clinical remission that may last decades. While clinical latency has been postulated to reflect the ability of residual tumor cells to persist in a dormant state, this hypothesis remains unproven since little is known about the biology of these cells. Consequently, defining the properties of residual tumor cells is an essential goal with important clinical implications for preventing recurrence and improving cancer outcomes.

METHODS

To identify conserved features of residual tumor cells, we modeled minimal residual disease using inducible transgenic mouse models for HER2/neu and Wnt1-driven tumorigenesis that recapitulate cardinal features of human breast cancer progression, as well as human breast cancer cell xenografts subjected to targeted therapy. Fluorescence-activated cell sorting was used to isolate tumor cells from primary tumors, residual lesions following oncogene blockade, and recurrent tumors to analyze gene expression signatures and evaluate tumor-initiating cell properties.

RESULTS

We demonstrate that residual tumor cells surviving oncogenic pathway inhibition at both local and distant sites exist in a state of cellular dormancy, despite adequate vascularization and the absence of adaptive immunity, and retain the ability to re-enter the cell cycle and give rise to recurrent tumors after extended latency periods. Compared to primary or recurrent tumor cells, dormant residual tumor cells possess unique features that are conserved across mouse models for human breast cancer driven by different oncogenes, and express a gene signature that is strongly associated with recurrence-free survival in breast cancer patients and similar to that of tumor cells in which dormancy is induced by the microenvironment. Although residual tumor cells in both the HER2/neu and Wnt1 models are enriched for phenotypic features associated with tumor-initiating cells, limiting dilution experiments revealed that residual tumor cells are not enriched for cells capable of giving rise to primary tumors, but are enriched for cells capable of giving rise to recurrent tumors, suggesting that tumor-initiating populations underlying primary tumorigenesis may be distinct from those that give rise to recurrence following therapy.

CONCLUSIONS

Residual cancer cells surviving targeted therapy reside in a well-vascularized, desmoplastic microenvironment at both local and distant sites. These cells exist in a state of cellular dormancy that bears little resemblance to primary or recurrent tumor cells, but shares similarities with cells in which dormancy is induced by microenvironmental cues. Our observations suggest that dormancy may be a conserved response to targeted therapy independent of the oncogenic pathway inhibited or properties of the primary tumor, that the mechanisms underlying dormancy at local and distant sites may be related, and that the dormant state represents a potential therapeutic target for preventing cancer recurrence.

Immune landscape of inflammatory breast cancer suggests vulnerability to immune checkpoint inhibitors

Background. Anti-PD1/PDL1 immune checkpoint inhibitors (ICIs) showed promising results in breast cancer, and exploration of additional actionable immune checkpoints is ongoing. Inflammatory breast cancer (IBC) is an aggressive form of disease, the immune tumor microenvironment (TME) of which is poorly known. We aimed at providing the first comprehensive immune portrait of IBCs. Methods. From the gene expression profiles of 137 IBC and 252 non-IBC clinical samples, we measured the fractions of 22 immune cell types, expression of signatures associated with tertiary lymphoid structures (TLS) and with the response to ICIs (T cell-inflamed signature: TIS) and of 18 genes coding for major actionable immune checkpoints. The IBC/non-IBC comparison was adjusted upon the clinicopathological variables. Results. The immune profiles of IBCs were heterogeneous. CIBERSORT analysis showed profiles rich in macrophages, CD8+ and CD4 + T-cells, with remarkable similarity with melanoma TME. The comparison with non-IBCs showed significant enrichment in M1 macrophages, γδ T-cells, and memory B-cells. IBCs showed higher expression of TLS and TIS signatures. The TIS signature displayed values in IBCs close to those observed in other cancers sensitive to ICIs. Two-thirds of actionable immune genes (HAVCR2/TIM3, CD27, CD70, CTLA4, ICOS, IDO1, LAG3, PDCD1, TNFRSF9, PVRIG, CD274/PDL1, and TIGIT) were overexpressed in IBCs as compared to normal breast and two-thirds were overexpressed in IBCs versus non-IBCs, with very frequent co-overexpression. For most of them, the overexpression was associated with better pathological response to chemotherapy. Conclusion. Our results suggest the potential higher vulnerability of IBC to ICIs. Clinical trials.

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.

Obesity and Androgen Receptor Signaling: Associations and Potential Crosstalk in Breast Cancer Cells

Obesity is an increasing health challenge and is recognized as a breast cancer risk factor. Although obesity-related breast cancer mechanisms are not fully understood, this association has been linked to impaired hormone secretion by the dysfunctional obese adipose tissue (hyperplasic and hypertrophic adipocytes). Among these hormones, altered production of androgens and adipokines is observed, and both, are independently associated with breast cancer development. In this review, we describe and comment on the relationships reported between these factors and breast cancer, focusing on the biological associations that have helped to unveil the mechanisms by which signaling from androgens and adipokines modifies the behavior of mammary epithelial cells. Furthermore, we discuss the potential crosstalk between the two most abundant adipokines produced by the adipose tissue (adiponectin and leptin) and the androgen receptor, an emerging marker in breast cancer. The identification and understanding of interactions among adipokines and the androgen receptor in cancer cells are necessary to guide the development of new therapeutic approaches in order to prevent and cure obesity and breast cancer.

Comprehensive analysis of immune-related prognostic genes in the tumour microenvironment of hepatocellular carcinoma

BACKGROUND

The mortality rate of hepatocellular carcinoma (HCC) remains high worldwide despite surgery and chemotherapy. Immunotherapy is a promising treatment for the rapidly expanding HCC spectrum. Therefore, it is necessary to further explore the immune-related characteristics of the tumour microenvironment (TME), which plays a vital role in tumour initiation and progression.

METHODS

In this research, 866 immune-related differentially expressed genes (DEGs) were identified by integrating the DEGs of samples from The Cancer Genome Atlas (TCGA)-HCC dataset and the immune-related genes from databases (InnateDB; ImmPort). Afterwards, 144 candidate prognostic genes were defined through weighted gene co-expression network analysis (WGCNA).

RESULTS

Seven immune-related prognostic DEGs were identified using the L1-penalized least absolute shrinkage and selection operator (LASSO) Cox proportional hazards (PH) model, and the ImmuneRiskScore model was constructed on this basis. The prognostic index of the ImmuneRiskScore model was then validated in the relevant dataset. Patients were divided into high- and low-risk groups according to the ImmuneRiskScore. Differences in the immune cell infiltration of patients with different ImmuneRiskScore values were clarified, and the correlation of immune cell infiltration with immunotherapy biomarkers was further explored.

CONCLUSION

The ImmuneRiskScore of HCC could be a prognostic marker and can reflect the immune characteristics of the TME. Furthermore, it provides a potential biomarker for predicting the response to immunotherapy in HCC patients.

Intratumoral Plasmid IL12 Expands CD8+ T Cells and Induces a CXCR3 Gene Signature in Triple-negative Breast Tumors that Sensitizes Patients to Anti-PD-1 Therapy

PURPOSE

Triple-negative breast cancer (TNBC) is an aggressive disease with limited therapeutic options. Antibodies targeting programmed cell death protein 1 (PD-1)/PD-1 ligand 1 (PD-L1) have entered the therapeutic landscape in TNBC, but only a minority of patients benefit. A way to reliably enhance immunogenicity, T-cell infiltration, and predict responsiveness is critically needed.

PATIENTS AND METHODS

Using mouse models of TNBC, we evaluate immune activation and tumor targeting of intratumoral IL12 plasmid followed by electroporation (tavokinogene telseplasmid; Tavo). We further present a single-arm, prospective clinical trial of Tavo monotherapy in patients with treatment refractory, advanced TNBC (OMS-I140). Finally, we expand these findings using publicly available breast cancer and melanoma datasets.

RESULTS

Single-cell RNA sequencing of murine tumors identified a CXCR3 gene signature (CXCR3-GS) following Tavo treatment associated with enhanced antigen presentation, T-cell infiltration and expansion, and PD-1/PD-L1 expression. Assessment of pretreatment and posttreatment tissue from patients confirms enrichment of this CXCR3-GS in tumors from patients that exhibited an enhancement of CD8⁺ T-cell infiltration following treatment. One patient, previously unresponsive to anti-PD-L1 therapy, but who exhibited an increased CXCR3-GS after Tavo treatment, went on to receive additional anti-PD-1 therapy as their immediate next treatment after OMS-I140, and demonstrated a significant clinical response.

CONCLUSIONS

These data show a safe, effective intratumoral therapy that can enhance antigen presentation and recruit CD8 T cells, which are required for the antitumor efficacy. We identify a Tavo treatment-related gene signature associated with improved outcomes and conversion of nonresponsive tumors, potentially even beyond TNBC.

CD8(+) T lymphocytes infiltrating breast cancer: A promising new prognostic marker?

Lymphocytic infiltration is often seen in breast cancer and has been suggested as a marker of host anti-tumor response but its importance in prognosis remains controversial. Our recent study demonstrated an association between tumor-infiltrating CD8⁺ T lymphocytes in invasive breast cancer and better prognosis.

"Stealth" tumors: Breast cancer cells shun NK-cells anti-tumor immunity

Breast cancers (BCs) comprise heterogeneous subtypes of various prognoses. An active anti-tumor immune profile usually correlated with a better survival. Two current major challenges of BC research are to understand the inter-relations between BC and anti-tumor immunity, and to identify candidates whose targeting would contribute to enhance anti-tumor efficiency.