Immune gene expression and response to chemotherapy in advanced breast cancer

Zebularine potentiates anti-tumor immunity by inducing tumor immunogenicity and improving antigen processing through cGAS-STING pathway

DNA methylation is an important epigenetic mechanism involved in the anti-tumor immune response, and DNA methyltransferase inhibitors (DNMTi) have achieved impressive therapeutic outcomes in patients with certain cancer types. However, it is unclear how inhibition of DNA methylation bridges the innate and adaptive immune responses to inhibit tumor growth. Here, we report that DNMTi zebularine reconstructs tumor immunogenicity, in turn promote dendritic cell maturation, antigen-presenting cell activity, tumor cell phagocytosis by APCs, and efficient T cell priming. Further in vivo and in vitro analyses reveal that zebularine stimulates cGAS-STING-NF-κB/IFNβ signaling to enhance tumor cell immunogenicity and upregulate antigen processing and presentation machinery (AgPPM), which promotes effective CD4+ and CD8+ T cell-mediated killing of tumor cells. These findings support the use of combination regimens that include DNMTi and immunotherapy for cancer treatment.

Minimally invasive biopsy-based diagnostics in support of precision cancer medicine

Precision cancer medicine (PCM) to support the treatment of solid tumors requires minimally invasive diagnostics. Here, we describe the development of fine-needle aspiration biopsy-based (FNA) molecular cytology which will be increasingly important in diagnostics and adaptive treatment. We provide support for FNA-based molecular cytology having a significant potential to replace core needle biopsy (CNB) as a patient-friendly potent technique for tumor sampling for various tumor types. This is not only because CNB is a more traumatic procedure and may be associated with more complications compared to FNA-based sampling, but also due to the recently developed molecular methods used with FNA. Recent studies show that image-guided FNA in combination with ultrasensitive molecular methods also offers opportunities for characterization of the tumor microenvironment which can aid therapeutic decisions. Here we provide arguments for an increased implementation of molecular FNA-based sampling as a patient-friendly diagnostic method, which may, due to its repeatability, facilitate regular sampling that is needed during different treatment lines, to provide tumor information, supporting treatment decisions, shortening lead times in healthcare, and benefit healthcare economics.

Relevance Analysis of TPM2 and Clinicopathological Characteristics in Breast Cancer

Background

The function of tropomyosin 2 (TPM2) in breast cancer is still far understudied. In this study, we aim to explore the roles of TPM2 in breast cancer progression.

Methods

This research included 155 breast cancer tissues. The expression of TPM2 was analyzed by immunohistochemical staining and grading. The mRNA expression of TPM2 in pan-cancer was analyzed with The Cancer Genome Atlas (TCGA) data plate form. The differential expression of TPM2 protein and the differential promoter methylation level of TPM2 between breast cancer tissues and normal breast tissues were analyzed by the UALCAN online database. The relationship between TPM2 and signaling pathways was interpreted by Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA) pathway enrichment analyses. The survival curve of TPM2 was analyzed across the Kaplan-Meier plotter online database. Furthermore, the relationship between TPM2 expression and infiltrating macrophages was validated through in vitro co-culture experiments.

Results

TPM2 expression was significantly down-regulated in breast cancer samples. In addition, TPM2 expression was correlated with lymph node metastasis and high-grade histopathological morphology. The receiver operating characteristic (ROC) curve indicated that TPM2 expression could well distinguish between normal breast tissue and breast cancer tissue. TPM2 may have potential value in breast cancer diagnosis. Bioinformatics analysis illustrated that TPM2 was mainly involved in extracellular matrix organization, collagen fibril organization, cell junction assembly, focal adhesion, cAMP signaling pathway, estrogen signaling pathway, Wnt signaling pathway, and adaptive immune system. TPM2 expression was correlated with immune infiltrating cells and immune checkpoint molecules. Our in vitro co-culture experiments showed that the M2 macrophages could upregulate the expression of TPM2.

Conclusion

TPM2 may play key roles in breast cancer occurrence and development, especially in cancer metastasis. TPM2 may be a potential biomarker for breast cancer diagnosis.

Integrative landscape analysis of prognostic model biomarkers and immunogenomics of disulfidptosis-related genes in breast cancer based on LASSO and WGCNA analyses

BACKGROUND

Disulfidptosis is a novel type of programmed cell death. However, the value of disulfidptosis-related genes (DRGs) in the prediction of breast cancer prognosis is unclear.

METHODS

RNA-seq data of 1231 patients, together with information on patient clinical characteristics and prognosis, were downloaded from TCGA. DRGs were identified between cancerous and non-cancerous tissues. The LASSO algorithm was used to assign half of the samples to the training set. Risk scores were used for construction of a prognostic model for risk stratification and prognosis prediction, and the clinical applicability was examined using a line diagram. The relationships between risk scores, immune cell infiltration, molecular subtypes, and responses to immunotherapy and chemotherapy were examined.

RESULTS

We identified and obtained four DRG-related prognostic lncRNAs (AC009097.2, AC133552.5, YTHDF3-AS1, and AC084824.5), which were used for establishing the risk model. Longer survival was associated with low risk. The DRG-associated lncRNAs were found to independently predict patient prognosis. The AUCs under the ROCs for one-, three-, and 5-year survival in the training cohort were 0.720, 0.687, and 0.692, respectively. The model showed that the high-risk patients had reduced overall survival as well as high tumor mutation burdens. Furthermore, high-risk patients showed increased sensitivity to therapeutic drugs, including docetaxel, paclitaxel, and oxaliplatin.

CONCLUSION

The risk score model was effective for predicting both prognosis and sensitivity to therapeutic drugs, suggesting its possible usefulness for the management of patients with breast cancer.

It's high-time to re-evaluate the value of induced-chemotherapy for reinforcing immunotherapy in colorectal cancer

Immunotherapy has made significant advances in the treatment of colorectal cancer (CRC), revolutionizing the therapeutic landscape and highlighting the indispensable role of the tumor immune microenvironment. However, some CRCs have shown poor response to immunotherapy, prompting investigation into the underlying reasons. It has been discovered that certain chemotherapeutic agents possess immune-stimulatory properties, including the induction of immunogenic cell death (ICD), the generation and processing of non-mutated neoantigens (NM-neoAgs), and the B cell follicle-driven T cell response. Based on these findings, the concept of inducing chemotherapy has been introduced, and the combination of inducing chemotherapy and immunotherapy has become a standard treatment option for certain cancers. Clinical trials have confirmed the feasibility and safety of this approach in CRC, offering a promising method for improving the efficacy of immunotherapy. Nevertheless, there are still many challenges and difficulties ahead, and further research is required to optimize its use.

Promotion of ICD via Nanotechnology

Immunotherapy represents the most promising treatment strategy for cancer, but suffers from compromised therapeutic efficiency due to low immune activity of tumor cells and an immunosuppressive microenvironment, which significantly hampers the clinical translations of this treatment strategy. To promote immunotherapy with desired therapeutic efficiency, immunogenic cell death (ICD), a particular type of death capable of reshaping body's antitumor immune activity, has drawn considerable attention due to the potential to stimulate a potent immune response. Still, the potential of ICD effect remains unsatisfactory because of the intricate tumor microenvironment and multiple drawbacks of the used inducing agents. ICD has been thoroughly reviewed so far with a general classification of ICD as a kind of immunotherapy strategy and repeated discussion of the related mechanism. However, there are no published reviews, to the authors' knowledge, providing a systematic summarization on the enhancement of ICD via nanotechnology. For this purpose, this review first discusses the four stages of ICD according to the development mechanisms, followed by a comprehensive description on the use of nanotechnology to enhance ICD in the corresponding four stages. The challenges of ICD inducers and possible solutions are finally summarized for future ICD-based enhanced immunotherapy.

Multiplex protein analysis and ensemble machine learning methods of fine needle aspirates from prostate cancer patients reveal potential diagnostic signatures associated with tumour grade

BACKGROUND

Improved molecular diagnosis is needed in prostate cancer (PC). Fine needle aspiration (FNA) is a minimally invasive biopsy technique, less traumatic compared to core needle biopsy, and could be useful for diagnosis of PC. Molecular biomarkers (BMs) in FNA-samples can be assessed for prediction, eg of immunotherapy efficacy before treatment as well as at treatment decision time points during disease progression.

METHODS

In the present pilot study, the expression levels of 151 BM proteins were analysed by proximity extension assay in FNA-samples from 16 patients, including benign prostate lesions (n = 3) and cancers (n = 13). An ensemble data analysis strategy was applied using several machine learning models.

RESULTS

Twelve potentially predictive BM proteins correlating with International Society of Urological Pathology grade groups were identified, among them vimentin, tissue factor pathway inhibitor 2, and integrin beta-5. The validity of the results was supported by network analysis that showed functional associations between most of the identified putative BMs. We also showed that multiple immune checkpoint targets can be assessed (eg PD-L1, CD137, and Galectin-9), which may support the selection of immunotherapy in advanced PC. Results are promising but need further validation in a larger cohort.

CONCLUSIONS

Our pilot study represents a "proof of concept" and shows that multiplex profiling of potential diagnostic and predictive BM proteins is feasible on tumour material obtained by FNA sampling of prostate cancer. Moreover, our results demonstrate that an ensemble data analysis strategy may facilitate the identification of BM signatures in pilot studies when the patient cohort is limited.

CGB5, INHBA and TRAJ19 Hold Prognostic Potential as Immune Genes for Patients with Gastric Cancer

BACKGROUND

Gastric cancer (GC) seriously threatens people's health and life quality worldwide.

AIM

The current study sought to explore prognostic immune genes and their regulatory network in GC.

METHODS

First, expression data in GC and normal samples were analyzed based on bioinformatics analysis. Immune-related genes were identified and confirmed with univariate/multivariate Cox analysis and receiver-operating characteristic curve. The upstream transcription factors of immune genes were subsequently predicted, and their regulatory network was constructed. GC and adjacent normal tissues were obtained from 76 patients with GC to determine the expression patterns of immune genes and their correlation with overall prognosis. CD8⁺ T-cell infiltration of patients with high or low risk was detected by means of immunohistochemistry.

RESULTS

Bioinformatics analysis highlighted 3689 differentially expressed genes in GC, including 87 immune genes, 8 of which were significantly associated with patient survival. CGB5 and INHBA were high-risk genes, while TRAJ19 was identified as a low-risk gene, all of which were found to be regulated by 11 different transcription factors. Furthermore, CGB5 and INHBA exhibited negative correlation with the prognosis of GC patients; however, TRAJ19 was positively correlated with GC patient prognosis. The incidence of lymph node metastasis was higher, the pathological stage was advanced and the infiltrated CD8⁺ T cells were fewer in the high-risk GC group.

CONCLUSIONS

Overall, our findings identified the key roles of CGB5, INHBA and TRAJ19 in prognosis GC patients, serving as an important gene set for prognostic prediction.

Predictive value of immune genomic signatures from breast cancer cohorts containing data for both response to neoadjuvant chemotherapy and prognosis after surgery

BACKGROUND

Previous studies of immune genomic signatures (IGSs) in breast cancer have attempted to predict the response to chemotherapy or prognosis and were performed using different patient cohorts. The purpose of this study was to evaluate the predictive functions of various IGSs using the same patient cohort that included data for response to chemotherapy as well as the prognosis after surgery.

METHODS

We applied five previously described IGS models in a public dataset of 508 breast cancer patients treated with neoadjuvant chemotherapy. The prognostic and predictive values of each model were evaluated, and their correlations were compared.

RESULTS

We observed a high proportion of expression concordance among the IGS models (r: 0.56-1). Higher scores of IGSs were detected in aggressive breast cancer subtypes (basal and HER2-enriched) (P < 0.001). Four of the five IGSs could predict chemotherapy responses and two could predict 5-year relapse-free survival in cases with hormone receptor-positive (HR +) tumors. However, the models showed no significant differences in their predictive abilities for hormone receptor-negative (HR-) tumors.

CONCLUSIONS

IGSs are, to some extent, useful for predicting prognosis and chemotherapy response; moreover, they show substantial agreement for specific breast cancer subtypes. However, it is necessary to identify more compelling biomarkers for both prognosis and response to chemotherapy in HR- and HER2 + cases.

Expression patterns and prognostic implications of tumor-infiltrating lymphocytes dynamics in early breast cancer patients receiving neoadjuvant therapy: A systematic review and meta-analysis

PURPOSE

High levels of tumor-infiltrating lymphocytes (TILs) are associated with better outcomes in early breast cancer and higher pathological response rates to neoadjuvant chemotherapy especially in the triple-negative (TNBC) and HER2+ subtypes. However, the dynamic changes in TILs levels after neoadjuvant treatment (NAT) are less studied. This systematic review and meta-analysis aimed to investigate the patterns and role of TILs dynamics change in early breast cancer patients receiving NAT.

METHODS

Medline, Embase, Web of Science Core Collection and PubMed Central databases were searched for eligible studies. Data were extracted independently by two researchers and discordances were resolved by a third. Pooled TILs rates pre- & post-treatment (overall and per subtype), pooled rates of ΔTILs and direction of change after NAT as well as correlation of ΔTILs with survival outcomes were generated in the outcome analysis.

RESULTS

Of 2116 identified entries, 34 studies fulfilled the criteria and provided adequate data for the outcomes of interest. A decreased level of TILs was observed after NAT in paired samples across all subtypes. The effect of NAT on TILs was most prominent in TNBC subtype with a substantial change, either increase or decrease, in 79.3% (95% CI 61.7-92.6%) of the patients as well as in HER2+ disease (14.4% increased vs 46.2% decreased). An increase in ΔTILs in TNBC was associated with better disease-free/relapse-free survival in pooled analysis (univariate HR = 0.59, 95% CI: 0.37-0.95, p = 0.03).

CONCLUSION

This meta-analysis illustrates the TILs dynamics during NAT for breast cancer and indicates prognostic implications of ΔTILs in TNBC. The potential clinical utility of the longitudinal assessment of TILs during neoadjuvant therapy warrants further validation.

NUSAP1 and PCLAF (KIA0101) Downregulation by Neoadjuvant Therapy is Associated with Better Therapeutic Outcomes and Survival in Breast Cancer

Purpose. To evaluate whether changes in genomic expression that occur beginning with breast cancer (BC) diagnosis and through to tumor resection after neoadjuvant chemotherapy (NCT) reveal biomarkers that can help predict therapeutic response and survival. Materials and Methods. We determined gene expression profiles based on microarrays in tumor samples from 39 BC patients who showed pathologic complete response (pCR) or therapeutic failure (non-pCR) after NCT (cyclophosphamide-doxorubicin/epirubicin). Based on unsupervised clustering of gene expression, together with functional enrichment analyses of differentially expressed genes, we selected NUSAP1, PCLAF, MME, and DST. We evaluated the NCT response and the expression of these four genes in BC histologic subtypes. In addition, we study the presence of tumor-infiltrating lymphocytes. Finally, we analyze the correlation between NUSAP1 and PCLAF against disease-free survival (DFS) and overall survival (OS). Results. A signature of 43 differentially expressed genes discriminated pCR from non-pCR patients (|fold change >2|, false discovery rate <0.05) only in biopsies taken after surgery. Patients achieving pCR showed downregulation of NUSAP1 and PCLAF in tumor tissues and increased DFS and OS, while overexpression of these genes correlated with poor therapeutic response and OS. These genes are involved in the regulation of mitotic division. Conclusions. The downregulation of NUSAP1 and PCLAF after NCT is associated with the tumor response to chemotherapy and patient survival.

Heparin and Heparin-Based Drug Delivery Systems: Pleiotropic Molecular Effects at Multiple Drug Resistance of Osteosarcoma and Immune Cells

One of the main problems of modern health care is the growing number of oncological diseases both in the elderly and young population. Inadequately effective chemotherapy, which remains the main method of cancer control, is largely associated with the emergence of multidrug resistance in tumor cells. The search for new solutions to overcome the resistance of malignant cells to pharmacological agents is being actively pursued. Another serious problem is immunosuppression caused both by the tumor cells themselves and by antitumor drugs. Of great interest in this context is heparin, a biomolecule belonging to the class of glycosaminoglycans and possessing a broad spectrum of biological activity, including immunomodulatory and antitumor properties. In the context of the rapid development of the new field of “osteoimmunology,” which focuses on the collaboration of bone and immune cells, heparin and delivery systems based on it may be of intriguing importance for the oncotherapy of malignant bone tumors. Osteosarcoma is a rare but highly aggressive, chemoresistant malignant tumor that affects young adults and is characterized by constant recurrence and metastasis. This review describes the direct and immune-mediated regulatory effects of heparin and drug delivery systems based on it on the molecular mechanisms of (multiple) drug resistance in (onco) pathological conditions of bone tissue, especially osteosarcoma.

Tumor-Infiltrating Lymphocytes Improve Magee Equation-Based Prediction of Pathologic Complete Response in HR-Positive/HER2-Negative Breast Cancer

OBJECTIVES

Magee equation 3 (ME3) is predictive of the pathologic complete response (pCR) to neoadjuvant chemotherapy (NAC) in patients with hormone receptor (HR)-positive, human epidermal growth factor receptor 2 (HER2)-negative breast cancer but with insufficient predictive performance. This study was designed to improve predictive ability by combining ME3 with additional clinicopathologic markers.

METHODS

We retrospectively enrolled 460 patients with HR-positive/HER2-negative breast cancer from 2 centers. We obtained baseline characteristics, the ME3 score, and the number of stromal tumor-infiltrating lymphocytes (sTILs). After performing a logistic regression analysis, a predictive nomogram was built and validated externally.

RESULTS

ME3 score (adjusted odds ratio [OR], 1.14 [95% confidence interval (CI), 1.10-1.17]; P < .001) and TILs (adjusted OR, 5.21 [95% CI, 3.33-8.14]; P < .001) were independently correlated with pCR. The nomogram (named ME3+) was established using ME3 and sTILs, and it demonstrated an area under the curve of 0.816 and 0.862 in internal and external validation, respectively, outperforming the ME3 score alone. sTILs and ME3 scores were also found to be positively correlated across the entire cohort (P < .001).

CONCLUSIONS

The combination of sTILs and ME3 score potentially shows better performance for predicting pCR than ME3 alone. Larger validations are required for widespread application of ME3+ nomogram in NAC settings for HR-positive/HER2-negative breast cancer.

Dissecting Tumor-Immune Microenvironment in Breast Cancer at a Spatial and Multiplex Resolution

The tumor immune microenvironment (TIME) is an important player in breast cancer pathophysiology. Surrogates for antitumor immune response have been explored as predictive biomarkers to immunotherapy, though with several limitations. Immunohistochemistry for programmed death ligand 1 suffers from analytical problems, immune signatures are devoid of spatial information and histopathological evaluation of tumor infiltrating lymphocytes exhibits interobserver variability. Towards improved understanding of the complex interactions in TIME, several emerging multiplex in situ methods are being developed and gaining much attention for protein detection. They enable the simultaneous evaluation of multiple targets in situ, detection of cell densities/subpopulations as well as estimations of functional states of immune infiltrate. Furthermore, they can characterize spatial organization of TIME—by cell-to-cell interaction analyses and the evaluation of distribution within different regions of interest and tissue compartments—while digital imaging and image analysis software allow for reproducibility of the various assays. In this review, we aim to provide an overview of the different multiplex in situ methods used in cancer research with special focus on breast cancer TIME at the neoadjuvant, adjuvant and metastatic setting. Spatial heterogeneity of TIME and importance of longitudinal evaluation of TIME changes under the pressure of therapy and metastatic progression are also addressed.

Neutrophil-to-lymphocyte ratio as a prognostic factor for patients with metastatic or recurrent breast cancer treated using capecitabine: a retrospective study

BACKGROUND

Eribulin or capecitabine monotherapy is the next cytotoxic chemotherapy option for patients with metastatic or recurrent breast cancer who have previously received an anthracycline or a taxane. However, it is unclear what factors can guide the selection of eribulin or capecitabine in this setting, and prognostic factors are needed to guide appropriate treatment selection. The neutrophil-to-lymphocyte ratio (NLR) is a prognostic factor for eribulin-treated patients, although it is unclear whether it is a prognostic factor for capecitabine-treated patients. Therefore, we analysed the ability of the NLR to predict oncological outcomes among patients who received capecitabine after previous anthracycline or taxane treatment for breast cancer.

METHODS

We retrospectively reviewed the medical records of patients with metastatic or recurrent breast cancer who had previously received anthracycline or taxane treatment at the National Cancer Center Hospital between 2007 and 2015. Patients were included if they received eribulin or capecitabine monotherapy as first-line, second-line, or third-line chemotherapy. Analyses of overall survival (OS) and progression-free survival (PFS) were performed according to various factors.

RESULTS

Between 2007 and 2015, we identified 125 eligible patients, including 46 patients who received only eribulin, 34 patients who received only capecitabine, and 45 patients who received eribulin and capecitabine. The median follow-up period was 19.1 months. Among eribulin-treated patients, an NLR of <3 independently predicted better OS. Among capecitabine-treated patients, an NLR of <3 independently predicted better PFS but not better OS. In addition, a lymphocyte-to-monocyte ratio of ≥5 was associated with better PFS and OS.

CONCLUSIONS

To the best of our knowledge, this is the first study to evaluate whether the NLR is a prognostic factor for capecitabine-treated patients with metastatic or recurrent breast cancer. However, the NLR only independently predicted PFS in this setting, despite it being a useful prognostic factor for other chemotherapies.

Prognostic immunologic signatures in epithelial ovarian cancer

Epithelial Ovarian Cancer (EOC) is a deadly gynecologic malignancy in which patients frequently develop recurrent disease following initial platinum-taxane chemotherapy. Analogous to many other cancer subtypes, EOC clinical trials have centered upon immunotherapeutic approaches, most notably programmed cell death 1 (PD-1) inhibitors. While response rates to these immunotherapies in EOC patients have been low, evidence suggests that ovarian tumors are immunogenic and that immune-related genomic profiles can serve as prognostic markers. This review will discuss recent advances in the development of immune-based prognostic signatures in EOC that predict patient clinical outcomes, as well as emphasize specific research areas that need to be addressed to drive this field forward.

Interplay between copy number alterations and immune profiles in the early breast cancer Scandinavian Breast Group 2004-1 randomized phase II trial: results from a feasibility study

Emerging data indicate that genomic alterations can shape immune cell composition in early breast cancer. However, there is a need for complementary imaging and sequencing methods for the quantitative assessment of combined somatic copy number alteration (SCNA) and immune profiling in pathological samples. Here, we tested the feasibility of three approaches-CUTseq, for high-throughput low-input SCNA profiling, multiplexed fluorescent immunohistochemistry (mfIHC) and digital-image analysis (DIA) for quantitative immuno-profiling- in archival formalin-fixed paraffin-embedded (FFPE) tissue samples from patients enrolled in the randomized SBG-2004-1 phase II trial. CUTseq was able to reproducibly identify amplification and deletion events with a resolution of 100 kb using only 6 ng of DNA extracted from FFPE tissue and pooling together 77 samples into the same sequencing library. In the same samples, mfIHC revealed that CD4 + T-cells and CD68 + macrophages were the most abundant immune cells and they mostly expressed PD-L1 and PD-1. Combined analysis showed that the SCNA burden was inversely associated with lymphocytic infiltration. Our results set the basis for further applications of CUTseq, mfIHC and DIA to larger cohorts of early breast cancer patients.

Objective Response to First-Line Treatment as a Predictor of Overall Survival in Metastatic Breast Cancer: A Retrospective Analysis from Two Centers over a 25-Year Period

<b><i>Introduction:</i></b> The purpose of this study was to study the efficacy of subsequent treatment lines for metastatic breast cancer (MBC), as well as the association between radiologic objective response rate (ORR) and overall survival (OS). <b><i>Methods:</i></b> In this retrospective study, consecutive patients treated for MBC in two centers in Greece from January 1, 1992, to December 31, 2016, were identified and clinicopathologic data regarding tumor characteristics and administered treatments were collected. The efficacy per treatment line in terms of ORR, progression-free survival (PFS) and OS, as well as the prognostic value of ORR at first line were investigated. <b><i>Results:</i></b> A total of 977 patients with MBC were identified; 950 received any treatment. At first line, ORR was 43.5%, PFS 11.4 months (95% CI 10.4–12.4), and median OS 52.4 months (95% CI 47.7–57.1). Lower ORR and shorter PFS were observed with each subsequent line. Median OS was significantly longer for patients that had an objective response at first line, 61.9 months (95% CI 51.1–69.7) for responders versus 41.3 months (95% CI 44.1–63.3) for nonresponders (<i>p</i> &#x3c; 0.001). In multivariable analysis, failure to achieve an objective response was an independent predictor of poor survival (hazard ratio 1.70, 95% CI 1.34–2.15, <i>p</i> &#x3c; 0.001). <b><i>Conclusion:</i></b> Late treatment lines for MBC seem to have limited efficacy, while response to first-line therapy is associated with long-term survival. The latter should be considered in the treatment strategy of patients with MBC.

Discordance of PD-L1 status between primary and metastatic breast cancer: A systematic review and meta-analysis

INTRODUCTION

Programmed cell death ligand 1 (PD-L1) expression is predictive for benefit from immunotherapy in several human malignancies including triple negative breast cancer. Lower positivity rates but a larger relative benefit from atezolizumab has been implied when PD-L1 status is assessed at metastatic sites. We aimed to study the discordance of PD-L1 expression between primary tumor and metastasis in breast cancer due to its potential clinical utility.

METHODS

Cochrane Library, Embase, Medline and Web of science were searched for studies reporting on PD-L1 expression in primary and metastatic breast cancer, followed by data extraction. Outcomes included pooled PD-L1 positivity rates in tumor cells, immune cells or both in primary tumor and metastasis, PD-L1 discordance between matched primary tumors and metastasis and direction of discordance.

RESULTS

Of 2552 identified entries following de-duplication, 20 studies fulfilled the predefined inclusion criteria. Pooled PD-L1 positivity rate was higher in primary tumors compared to metastasis when assessed in immune cells (51.2% vs 37.1% p < 0.001) and tumor/immune cells (30.1% vs 14.6% p < 0.001), but not in tumor cells (18.7% vs 17.8% p = 0.65). PD-L1 positivity was lowest when assessed in bone metastases (12%) and highest in lymph nodes (60%). Discordance between primary tumors and metastasis was bidirectional, with higher pooled discordance rates when PD-L1 expression was assessed in immune compared to tumor cells (39.5% vs 13.6%, p < 0.001).

CONCLUSION

The observed considerable discordance between PD-L1 status in primary and metastatic breast cancer emphasizes the importance of appropriate tissue sampling when selecting patients for immunotherapy.

The tumor immune microenvironment and immune-related signature predict the chemotherapy response in patients with osteosarcoma

BACKGROUND

Genome-wide expression profiles have been shown to predict the response to chemotherapy. The purpose of this study was to develop a novel predictive signature for chemotherapy in patients with osteosarcoma.

METHODS

We analysed the relevance of immune cell infiltration and gene expression profiles of the tumor samples of good responders with those of poor responders from the TARGET and GEO databases. Immune cell infiltration was evaluated using a single-sample gene set enrichment analysis (ssGSEA) and the CIBERSORT algorithm between good and poor chemotherapy responders. Differentially expressed genes were identified based on the chemotherapy response. LASSO regression and binary logistic regression analyses were applied to select the differentially expressed immune-related genes (IRGs) and developed a predictive signature in the training cohort. A receiver operating characteristic (ROC) curve analysis was employed to assess and validate the predictive accuracy of the predictive signature in the validation cohort.

RESULTS

The analysis of immune infiltration showed a positive relationship between high-level immune infiltration and good responders, and T follicular helper cells and CD8 T cells were significantly more abundant in good responders with osteosarcoma. Two hundred eighteen differentially expressed genes were detected between good and poor responders, and a five IRGs panel comprising TNFRSF9, CD70, EGFR, PDGFD and S100A6 was determined to show predictive power for the chemotherapy response. A chemotherapy-associated predictive signature was developed based on these five IRGs. The accuracy of the predictive signature was 0.832 for the training cohort and 0.720 for the validation cohort according to ROC analysis.

CONCLUSIONS

The novel predictive signature constructed with five IRGs can be effectively utilized to predict chemotherapy responsiveness and help improve the efficacy of chemotherapy in patients with osteosarcoma.

The immune microenvironment and relation to outcome in patients with advanced breast cancer treated with docetaxel with or without gemcitabine

Preclinical studies suggest that some effects of conventional chemotherapy, and in particular, gemcitabine, are mediated through enhanced antitumor immune responses. The objective of this study was to use material from a randomized clinical trial to evaluate whether patients with preexisting immune infiltrates responded better to treatment with gemcitabine + docetaxel (GD) compared to docetaxel alone. Formalin fixed, paraffin-embedded breast cancer tissues from SBG0102 phase 3 trial patients randomly assigned to treatment with GD or docetaxel were used. Immunohistochemical staining for CD8, FOXP3, LAG3, PD-1, PD-L1 and CD163 was performed. Tumor infiltrating lymphocytes (TILs) and tumor associated macrophages were evaluated. Prespecified statistical analyses were performed in a formal prospective-retrospective design. Time to progression was primary endpoint and overall survival secondary endpoint. Correlations between biomarker status and endpoints were evaluated using the Kaplan–Meier method and Cox proportional hazards models. Biomarker data was obtained for 237 patients. There was no difference in treatment effect according to biomarker status for the whole cohort. In planned subgroup analysis by PAM50 subtype, in non-luminal (basal-like and HER2E) breast cancers FOXP3 was a significant predictor of treatment effect with GD compared to docetaxel, with a HR of 0.22 (0.09–0.52) for tumors with low FOXP3 compared to HR 0.92 (0.47–1.80) for high FOXP3 TILs (P_interaction = 0.01). Immune biomarkers were not predictive of added benefit of gemcitabine in a cohort of mixed breast cancer subtypes. However, in non-luminal breast cancers, patients with low FOXP3+ TILs may have significant benefit from added gemcitabine.

PD-L1 Protein Expression in Middle Eastern Breast Cancer Predicts Favorable Outcome in Triple-Negative Breast Cancer

Programmed cell-death ligand 1 (PD-L1) has been shown to induce potent T-cell mediated anti-tumoral immunity. The significance of PD-L1 expression in the prognosis of breast cancer (BC) remains controversial and its prevalence and prognostic value in breast cancer from Middle Eastern ethnicity is lacking. A total of 1003 unselected Middle Eastern breast cancers were analyzed for PD-L1 expression using immunohistochemistry. PD-L1 expression, seen in 32.8% (329/1003) of cases, was significantly associated with poor prognostic indicators such as younger patients, high-grade tumors, estrogen-receptor (ER)-negative, progesterone-receptor (PR)-negative, and triple-negative breast cancers (TNBC) as well as high Ki-67 index. We also found a significant association between PD-L1 expression and deficient mismatch repair protein expression. No association was found between PD-L1 expression and clinical outcome. However, on further subgroup analysis, PD-L1 expression was found to be an independent marker for favorable overall survival and recurrence-free survival in TNBC. In conclusion, we demonstrated strong association between PD-L1 and mismatch repair deficiency in Middle Eastern BC patients and that PD-L1 overexpression in tumor cells was an independent prognostic marker in TNBCs from Middle Eastern ethnicity. Overall, these findings might help in the development of more appropriate treatment strategies for BC in Middle Eastern population.

Quantification of Immune Variables from Liquid Biopsy in Breast Cancer Patients Links Vδ2+ γδ T Cell Alterations with Lymph Node Invasion

The rationale for therapeutic targeting of Vδ2+ γδ T cells in breast cancer is strongly supported by in vitro and murine preclinical investigations, characterizing them as potent breast tumor cell killers and source of Th1-related cytokines, backing cytotoxic αβ T cells. Nonetheless, insights regarding Vδ2+ γδ T cell phenotypic alterations in human breast cancers are still lacking. This paucity of information is partly due to the challenging scarcity of these cells in surgical specimens. αβ T cell phenotypic alterations occurring in the tumor bed are detectable in the periphery and correlate with adverse clinical outcomes. Thus, we sought to determine through an exploratory study whether Vδ2+ γδ T cells phenotypic changes can be detected within breast cancer patients' peripheral blood, along with association with tumor progression. By using mass cytometry, we quantified 130 immune variables from untreated breast cancer patients' peripheral blood. Supervised analyses and dimensionality reduction algorithms evidenced circulating Vδ2+ γδ T cell phenotypic alterations already established at diagnosis. Foremost, terminally differentiated Vδ2+ γδ T cells displaying phenotypes of exhausted senescent T cells associated with lymph node involvement. Thereby, our results support Vδ2+ γδ T cells implication in breast cancer pathogenesis and progression, besides shedding light on liquid biopsies to monitor surrogate markers of tumor-infiltrating Vδ2+ γδ T cell antitumor activity.

Clinical significance and immunogenomic landscape analyses of the immune cell signature based prognostic model for patients with breast cancer

Breast cancer is one of the most common types of cancers and the leading cause of death from malignancy among women worldwide. Tumor-infiltrating lymphocytes are a source of important prognostic biomarkers for breast cancer patients. In this study, based on the tumor-infiltrating lymphocytes in the tumor immune microenvironment, a risk score prognostic model was developed in the training cohort for risk stratification and prognosis prediction in breast cancer patients. The prognostic value of this risk score prognostic model was also verified in the two testing cohorts and the TCGA pan cancer cohort. Nomograms were also established in the training and testing cohorts to validate the clinical use of this model. Relationships between the risk score, intrinsic molecular subtypes, immune checkpoints, tumor-infiltrating immune cell abundances and the response to chemotherapy and immunotherapy were also evaluated. Based on these results, we can conclude that this risk score model could serve as a robust prognostic biomarker, provide therapeutic benefits for the development of novel chemotherapy and immunotherapy, and may be helpful for clinical decision making in breast cancer patients.

Tipping the immunostimulatory and inhibitory DAMP balance to harness immunogenic cell death

Induction of tumor cell death is the therapeutic goal for most anticancer drugs. Yet, a mode of drug-induced cell death, known as immunogenic cell death (ICD), can propagate antitumoral immunity to augment therapeutic efficacy. Currently, the molecular hallmark of ICD features the release of damage-associated molecular patterns (DAMPs) by dying cancer cells. Here, we show that gemcitabine, a standard chemotherapy for various solid tumors, triggers hallmark immunostimualtory DAMP release (e.g., calreticulin, HSP70, and HMGB1); however, is unable to induce ICD. Mechanistic studies reveal gemcitabine concurrently triggers prostaglandin E2 release as an inhibitory DAMP to counterpoise the adjuvanticity of immunostimulatory DAMPs. Pharmacological blockade of prostaglandin E2 biosythesis favors CD103+ dendritic cell activation that primes a Tc1-polarized CD8+ T cell response to bolster tumor rejection. Herein, we postulate that an intricate balance between immunostimulatory and inhibitory DAMPs could determine the outcome of drug-induced ICD and pose COX-2/prostaglandin E2 blockade as a strategy to harness ICD.

PD-1 protein and gene expression as prognostic factors in early breast cancer

BACKGROUND

There is a paucity of data on the prognostic value of programmed cell death protein 1 (PD-1) protein and gene expression in early breast cancer (BC) and the present study's aim was to comprehensively investigate it.

METHODS

The study consisted of three parts: a correlative analysis of PD-1 protein and gene expression from an original patient cohort of 564 patients with early BC; a systematic review and trial-level meta-analysis on the association between PD-1 protein expression and disease-free survival/overall survival (OS) in early BC; and a pooled gene expression analysis from publicly available transcriptomic datasets regarding PDCD1 expression.

RESULTS

In the study cohort, PD-1 protein, but not gene expression, was associated with improved OS (HRadj=0.73, 95% CI 0.55 to 0.97, p=0.027 and HRadj=0.88, 95% CI 0.68 to 1.13, p=0.312, respectively). In the trial-level meta-analysis, PD-1 protein expression was not found to be statistically significantly associated with outcomes in the overall population. Finally, in the pooled gene expression analysis, higher PDCD1 expression was associated with better OS in multivariable analysis in the entire population (HRadj=0.89, 95% CI 0.80 to 0.99, p=0.025) and in basal-like tumours.

CONCLUSIONS

PD-1 protein and gene expression seem to be promising prognostic factors in early BC. Standardisation of detection and assessment methods is of utmost importance.

Programmed death-ligand 1 gene expression is a prognostic marker in early breast cancer and provides additional prognostic value to 21-gene and 70-gene signatures in estrogen receptor-positive disease

Gene and protein expression of programmed death‐ligand 1 (PD‐L1) are prognostic in early breast cancer (BC), but their prognostic information is inconsistent at least in some biological subgroups. The validated prognostic gene signatures (GS) in BC are mainly based on proliferation and estrogen receptor (ER)‐related genes. Here, we aimed to explore the prognostic capacity of PD‐L1 expression at the protein vs mRNA levels and to investigate the prognostic information that PD‐L1 can potentially add to routinely used GS. Gene expression data were derived from two early BC cohorts (cohort 1: 562 patients; cohort 2: 1081 patients). Tissue microarrays from cohort 1 were immunohistochemically (IHC) stained for PD‐L1 using the SP263 clone. GS scores (21‐gene, 70‐gene) were calculated, and likelihood‐ratio (LR) tests and concordance indices were used to evaluate the additional prognostic information for each signature. The immune cell composition was also evaluated using the CIBERSORT in silico tool. PD‐L1 gene and protein expressions were independently associated with better prognosis. In ER+/HER2− patients, PD‐L1 gene expression provided significant additional prognostic information beyond that of both 21‐GS [LR‐Δχ² = 15.289 and LR‐Δχ² = 8.812, P < 0.01 for distant metastasis‐free interval (DMFI) in cohorts 1 and 2, respectively] and 70‐GS score alone (LR‐Δχ² = 18.198 and LR‐Δχ² = 8.467, P < 0.01 for DMFI in cohorts 1 and 2, respectively). PD‐L1 expression was correlated with IHC‐determined CD3+ cells (r = 0.41, P < 0.001) and with CD8+ (r = 0.62, P < 0.001) and CD4+ memory activated (r = 0.66, P < 0.001) but not with memory resting (r = −0.063, P = 0.14) or regulatory (r = −0.12, P < 0.01) T cells in silico. PD‐L1 gene expression represents a promising favorable prognostic marker and can provide additional prognostic value to 21‐ and 70‐gene scores in ER+/HER2− BC.

Trial watch: chemotherapy-induced immunogenic cell death in immuno-oncology

The term ‘immunogenic cell death’ (ICD) denotes an immunologically unique type of regulated cell death that enables, rather than suppresses, T cell-driven immune responses that are specific for antigens derived from the dying cells. The ability of ICD to elicit adaptive immunity heavily relies on the immunogenicity of dying cells, implying that such cells must encode and present antigens not covered by central tolerance (antigenicity), and deliver immunostimulatory molecules such as damage-associated molecular patterns and cytokines (adjuvanticity). Moreover, the host immune system must be equipped to detect the antigenicity and adjuvanticity of dying cells. As cancer (but not normal) cells express several antigens not covered by central tolerance, they can be driven into ICD by some therapeutic agents, including (but not limited to) chemotherapeutics of the anthracycline family, oxaliplatin and bortezomib, as well as radiation therapy. In this Trial Watch, we describe current trends in the preclinical and clinical development of ICD-eliciting chemotherapy as partner for immunotherapy, with a focus on trials assessing efficacy in the context of immunomonitoring.

Exploration of the immune-related signature and immune infiltration analysis for breast ductal and lobular carcinoma

Background

In this study, we aimed to explore the tumour associated immune signature of breast cancer (BC) and conduct integrative analyses with immune infiltrates in BC.

Methods

We downloaded the transcriptome profiling and clinical data of BC from The Cancer Genome Atlas (TCGA) database. The list of immune-related signatures was from the Innate database. The limma package was utilized to conduct the normalization, and we screened the differential immune signatures in BC. A univariate Cox regression model and the LASSO method were used to find the hub prognostic immune genes. The TAIG risk model was calculated based on the multivariate Cox regression results, and a receiver operating characteristic (ROC) curve was generated to assess the predictive power of TAIG. Moreover, we also conducted a correlation analysis between TAIG and the clinical characteristics. Additionally, we utilized the METABRIC cohort as the validation data set. The TIMER database is a comprehensive resource for performing systematic analyses of immune infiltrates across various malignancies. We evaluated the associations of immune signatures with several immune cells based on TIMER. Furthermore, we used the CIBERSORT algorithm to determine the fractions of immune cells in each sample and compared the differential distributions of immune infiltrates between two TAIG groups using the Wilcoxon rank-sum test.

Results

A total of 1,178 samples were obtained from the TCGA-BRCA database, but only 1,045 breast tumour samples were matched with complete transcriptome expression data. Meanwhile, we collected a total of 1,094 BC patients from the METABRIC cohort. We found a list of 1,399 differential immune signatures associated with survival, and functional analysis revealed that these genes participated in cytokine-cytokine receptor interactions, Th1 and Th2 cell differentiation and the JAK-STAT signalling pathway. The TAIG risk model was established from the multivariate Cox analysis, and we observed that high TAIG levels correlated with poor survival outcomes based on Kaplan-Meier analysis. The Kruskal-Wallis test suggested that high TAIG levels correlated with high AJCC-TNM stages and advanced pathological stages (P<0.01). We validated the well robustness of TAIG in METABRIC cohort and 5-year AUC reached up to 0.829. Moreover, we further uncovered the associations of hub immune signatures with immune cells and calculated the immune cell fractions in specific tumour samples based on gene signature expression. Last, we used the Wilcoxon rank-sum test to compare the differential immune density in the two groups and found that several immune cells had a significantly lower infiltrating density in the high TAIG groups, including CD8⁺ T cells (P=0.031), memory resting CD4⁺ T cells (P=0.026), M0 macrophages (P=0.023), and M2 macrophages (P=0.048).

Conclusions

In summary, we explored the immune signature of BC and constructed a TAIG risk model to predict prognosis. Moreover, we integrated the identified immune signature with tumour-infiltrating immune cells and found adverse associations between the TAIG levels and immune cell infiltrating density.

Prognostic Implications of PD-L1 Expression in Breast Cancer: Systematic Review and Meta-analysis of Immunohistochemistry and Pooled Analysis of Transcriptomic Data

PURPOSE

Conflicting data have been reported on the prognostic value of PD-L1 protein and gene expression in breast cancer.Experimental Design: Medline, Embase, Cochrane Library, and Web of Science Core Collection were searched, and data were extracted independently by two researchers. Outcomes included pooled PD-L1 protein positivity in tumor cells, immune cells, or both, per subtype and per antibody used, and its prognostic value for disease-free and overall survival. A pooled gene expression analysis of 39 publicly available transcriptomic datasets was also performed.

RESULTS

Of the initial 4,184 entries, 38 retrospective studies fulfilled the predefined inclusion criteria. The overall pooled PD-L1 protein positivity rate was 24% (95% CI, 15%-33%) in tumor cells and 33% (95% CI, 14%- 56%) in immune cells. PD-L1 protein expression in tumor cells was prognostic for shorter overall survival (HR, 1.63; 95% CI, 1.07-2.46; P = 0.02); there was significant heterogeneity (I² = 80%, P _{heterogeneity} < 0.001). In addition, higher PD-L1 gene expression predicted better survival in multivariate analysis in the entire population (HR, 0.82; 95% CI, 0.74-0.90; P < 0.001 for OS) and in basal-like tumors (HR, 0.64; 95% CI, 0.52-0.80; P < 0.001 for OS; P _interaction 0.005).

CONCLUSIONS

The largest to our knowledge meta-analysis on the subject informs on PD-L1 protein positivity rates and its prognostic value in breast cancer. Standardization is needed prior to routine implementation. PD-L1 gene expression is a promising prognostic factor, especially in basal-like breast cancer. Discrepant prognostic information might be related to PD-L1 gene expression in the stroma.

Beyond PD-1/PD-L1 Inhibition: What the Future Holds for Breast Cancer Immunotherapy

Cancer immunotherapy has altered the management of human malignancies, improving outcomes in an expanding list of diseases. Breast cancer - presumably due to its perceived low immunogenicity - is a late addition to this list. Furthermore, most of the focus has been on the triple negative subtype because of its higher tumor mutational load and lymphocyte-enriched stroma, although emerging data show promise on the other breast cancer subtypes as well. To this point the clinical use of immunotherapy is limited to the inhibition of two immune checkpoints, Programmed Cell Death Protein 1 (PD-1) and Cytotoxic T-lymphocyte-associated Protein 4 (CTLA-4). Consistent with the complexity of the regulation of the tumor - host interactions and their lack of reliance on a single regulatory pathway, combinatory approaches have shown improved efficacy albeit at the cost of increased toxicity. Beyond those two checkpoints though, a large number of co-stimulatory or co-inhibitory molecules play major roles on tumor evasion from immunosurveillance. These molecules likely represent future targets of immunotherapy provided that the promise shown in early data is translated into improved patient survival in randomized trials. The biological role, prognostic and predictive implications regarding breast cancer and early clinical efforts on exploiting these immune-related therapeutic targets are herein reviewed.

Augmenting the synergies of chemotherapy and immunotherapy through drug delivery

Despite the recent approvals of multiple cancer immunotherapies, low tumor immunogenicity and immunosuppressive tumor microenvironments prevent a large portion of patients from responding to these treatment modalities. Given the immunomodulatory and adjuvant effects of conventional chemotherapy as well as its widespread clinical use, the use of chemotherapy in combination with immunotherapy (so-called chemoimmunotherapy) is an attractive approach to potentiate the effects of immunotherapy in more patient populations. However, due to the limited extent of tumor accumulation, poorly controlled interactions with the immune system, and effects on systemic healthy tissues by chemotherapeutic drugs, the incorporation of anti-cancer agents into biomaterial-based structures, such as nanocarriers, is highly attractive to improve the safety and efficacy of chemoimmunotherapy. Herein, we review the recent progress in drug delivery systems (DDSs) for potentiating the immunomodulatory effects of chemotherapeutics in chemoimmunotherapy, which represent among the most promising next generation strategies for cancer treatment in the immunotherapy era. STATEMENT OF SIGNIFICANCE: Given the benefits of cancer immunotherapy in inducing durable, albeit low rates, of patient response, interest in the immunomodulatory and adjuvant effects of conventional chemotherapy has been re-invigorated. This review article discusses the recent progress towards understanding the synergies between these two treatment types, how they can be used in combination (so-called chemoimmunotherapy), and the potential for drug delivery systems to optimize their effects in translational settings.

Protein profiling of fine-needle aspirates reveals subtype-associated immune signatures and involvement of chemokines in breast cancer

There are increasing demands for informative cancer biomarkers, accessible via minimally invasive procedures, both for initial diagnostics and for follow-up of personalized cancer therapy, including immunotherapy. Fine-needle aspiration (FNA) biopsy provides ready access to relevant tissue samples; however, the minute amounts of sample require sensitive multiplex molecular analysis to be of clinical biomarker utility. We have applied proximity extension assays (PEA) to analyze 167 proteins in FNA samples from patients with breast cancer (BC; n = 25) and benign lesions (n = 32). We demonstrate that the FNA BC samples could be divided into two main clusters, characterized by differences in expression levels of the estrogen receptor (ER) and the proliferation marker Ki67. This clustering corresponded to some extent to established BC subtypes. Our analysis also revealed several proteins whose expression levels differed between BC and benign lesions (e.g., CA9, GZMB, IL-6, VEGFA, CXCL11, PDL1, and PCD1), as well as several chemokines correlating with ER and Ki67 status (e.g., CCL4, CCL8, CCL20, CXCL8, CXCL9, and CXCL17). Finally, we also identified three signatures that could predict Ki67 status, ER status, and tumor grade, respectively, based on a small subset of proteins, which was dominated by chemokines. To our knowledge, expression profiles of CCL13 in benign lesions and BC have not previously been described but were shown herein to correlate with proliferation (P = 0.00095), suggesting a role in advanced BC. Given the broad functional range of the proteins analyzed, immune-related proteins were overrepresented among the observed alterations. Our pilot study supports the emerging role of chemokines in BC progression. Due to the minimally traumatic sampling and clinically important molecular information for therapeutic decisions, this methodology is promising for future immunoscoring and monitoring of treatment efficacy in BC.

Alterations of Signaling Pathways Related to the Immune System in Breast Cancer: New Perspectives in Patient Management

In recent years, immune manipulation for cancer treatment, including breast cancer, has been increasingly gaining consent, and many attempts have been made, mainly by either strengthening the immune response (IR) or by inhibiting immune evasion. Therefore, elucidating the related mechanisms is of importance due to the potential to improve the management of cancer patients by immunotherapy. This review article summarized some recent experimental studies, which have discovered novel alterations of signaling pathways related to the immune system in breast cancer. These altered signaling pathways have been grouped according to the general biological mechanism involved: tumor-initiating cells (TICs), cancer stem cells (CSCs), immune evasion, tumor growth and progression, prediction of clinical outcome and prediction of response, or resistance to chemotherapy. These altered pathways related to the immune system open clinical opportunities for the prognosis or treatment of patients. Many of these pathways are related to the origin of breast cancer and immune evasion. We recommended development of new drugs which act on these molecular pathways, and the designing of clinical trials to be carried out mainly in breast cancer patients who required adjuvant treatment.

Dynamic evaluation of the immune infiltrate and immune function genes as predictive markers for neoadjuvant chemotherapy in hormone receptor positive, HER2 negative breast cancer

Gene expression (GE) signatures and Tumor Infiltrating Lymphocytes (TIL) enumeration are predictive for response to neoadjuvant chemotherapy in HR- and in HER2+ breast cancer, but data are conflicting in HR+/HER2- disease. This study aimed to explore their predictive value in this subset, measured both at baseline and after short exposure to chemotherapy. Specifically, the PROMIX phase 2 trial enrolled patients with locally advanced HER2- BC to receive six cycles of epirubicin and docetaxel, plus bevacizumab during cycles 3-6. Patients underwent tumor biopsies at baseline and after cycle 2 for GE profiling and enumeration of TIL, FOXP3+ T-cells and CD163+ macrophages. An immune related gene module and the quantification of the immune infiltrate were analyzed for association with pathologic complete response (pCR), decrease in tumor size and disease-free survival (DFS). Of the 150 patients enrolled in PROMIX, 113 were HR+/HER2-. Baseline GE and immune cell enumeration data were available from 71 patients, while data after 2 cycles of chemotherapy were available from 41. At baseline, only GE was statistically significantly associated with higher pCR rates (OR 2.29, 95% CI 1.05 - 5.38, p = 0.037) and decrease in tumor size (r = 0.25, p = 0.047). In contrast, longitudinal data indicate that both GE (r = 0.54, p<0.001) and TIL abundance (p = 0.009) are stronger predictors for the reduction of tumor size, while low FOXP3+ was statistically significantly associated with an improved DFS (p = 0.027). In conclusion, GE analysis, TIL and FOXP3+ enumeration after short-term exposure to chemotherapy carry important predictive information in HR+/HER2- breast cancer at the neoadjuvant setting.