Abstract GS5-05: Resistance to neoadjuvant chemotherapy in triple negative breast cancer mediated by a reversible drug-tolerant state

Identification of prognostically significant DNA methylation signatures in patients with various breast cancer types

Breast cancer (BC) is the most frequently diagnosed cancer and one of the major causes of female mortality. The development of prognostic models based on multiomics data is the main goal of precision oncology. Aberrant DNA methylation in BC is a diagnostic marker of carcinogenesis. Despite the existing factors of BC prognosis, introduction of methylation markers would make it possible to obtain more accurate prognostic scores. The study was aimed to assess DNA methylation signatures in various BC subtypes for clinical endpoints and patients' clinicopathological characteristics. The data on methylation of CpG dinucleotides (probes) and clinical characteristics of BC samples were obtained from The Cancer Genome Atlas Breast Cancer database. CpG dinucleotides associated with the selected endpoints were chosen by univariate Cox regression method. The LASSO method was used to search for stable probes, while further signature construction and testing of the clinical characteristics independence were performed using multivariate Cox regression. The dignostic and prognostic potential of the signatures was assessed using ROC analysis and Kaplan–Meier curves. It has been shown that the signatures of selected probes have a significant diagnostic (AUC 0.76–1) and prognostic (p < 0.05) potential. This approach has made it possible to identify 47 genes associated with good and poor prognosis, among these five genes have been described earlier. If the genome-wide DNA analysis results are available, the research approach applied can be used to study molecular pathogenesis of BC and other disorders.

Tumor-Infiltrating Cytotoxic T Cells and Tumor-Associated Macrophages Correlate With the Outcomes of Neoadjuvant Chemoradiotherapy for Locally Advanced Rectal Cancer

BACKGROUND

Tumor-infiltrating immune cells (TIICs) play a key role in immunoregulatory networks and are related to tumor development. Emerging evidence shows that these cells are associated with sensitivity to chemotherapy and radiotherapy. However, the predictive role of TIICs in the outcomes of neoadjuvant chemoradiotherapy (nCRT) for locally advanced rectal cancer (LARC) is unclear.

METHODS

Imaging mass cytometry (IMC) was performed to comprehensively assess the immune status before nCRT in 6 patients with LARC (3 achieved pathological complete response (pCR), 3 did not) with matched clinicopathological parameters. Immunohistochemistry (IHC) for CD8, CD163 and Foxp3 on biopsy samples from 70 patients prior to nCRT and logistic regression analysis were combined to further evaluate its predictive value for treatment responses in an independent validation group.

RESULTS

A trend of increased CD8+ cytotoxic T lymphocytes (CTLs) and decreased CD163+ tumor-associated macrophages (TAMs) and Foxp3+ regulatory T cells (Tregs) in the pCR group was revealed by IMC. In the validation group, CTLs and TAMs were strong predictors of the clinical response to nCRT. High levels of CTLs were positively associated with the pCR ratio (OR=1.042; 95% CI: 1.015~1.070, p=0.002), whereas TAMs were correlated with a poor response (OR=0.969; 95% CI: 0.941~0.998, p=0.036). A high density of TAMs was also associated with an advanced cN stage.

CONCLUSION

CTLs in the tumor microenvironment (TME) may improve the response to nCRT, whereas TAMs have the opposite effect. These results suggest that these cells might be potential markers for the clinical outcomes of nCRT and aid in the clinical decision-making of LARC for improved clinical outcomes.

Laboratory Models for Investigating Breast Cancer Therapy Resistance and Metastasis

While numerous therapies are highly efficacious in early-stage breast cancers and in particular subsets of breast cancers, therapeutic resistance and metastasis unfortunately arise in many patients. In many cases, tumors that are resistant to standard of care therapies, as well as tumors that have metastasized, are treatable but incurable with existing clinical strategies. Both therapy resistance and metastasis are multi-step processes during which tumor cells must overcome diverse environmental and selective hurdles. Mechanisms by which tumor cells achieve this are numerous and include acquisition of invasive and migratory capabilities, cell-intrinsic genetic and/or epigenetic adaptations, clonal selection, immune evasion, interactions with stromal cells, entering a state of dormancy or senescence, and maintaining self-renewal capacity. To overcome therapy resistance and metastasis in breast cancer, the ability to effectively model each of these mechanisms in the laboratory is essential. Herein we review historic and the current state-of-the-art laboratory model systems and experimental approaches used to investigate breast cancer metastasis and resistance to standard of care therapeutics. While each model system has inherent limitations, they have provided invaluable insights, many of which have translated into regimens undergoing clinical evaluation. We will discuss the limitations and advantages of a variety of model systems that have been used to investigate breast cancer metastasis and therapy resistance and outline potential strategies to improve experimental modeling to further our knowledge of these processes, which will be crucial for the continued development of effective breast cancer treatments.

Oncolytic Herpes Simplex Virus Encoding IL12 Controls Triple-Negative Breast Cancer Growth and Metastasis

Triple-negative breast cancer (TNBC) is a difficult-to-treat disease with high rates of local recurrence, distant metastasis, and poor overall survival with existing therapies. Thus, there is an unmet medical need to develop new treatment regimen(s) for TNBC patients. An oncolytic herpes simplex virus encoding a master anti-tumor cytokine, interleukin 12, (designated G47Δ-mIL12) selectively kills cancer cells while inducing anti-tumor immunity. G47Δ-mIL12 efficiently infected and killed murine (4T1 and EMT6) and human (HCC1806 and MDA-MB-468) mammary tumor cells in vitro. In vivo in the 4T1 syngeneic TNBC model, it significantly reduced primary tumor burden and metastasis, both at early and late stages of tumor development. The virus-induced local and abscopal effects were confirmed by significantly increased infiltration of CD45⁺ leukocytes and CD8⁺ T cells, and reduction of granulocytic and monocytic MDSCs in tumors, both treated and untreated contralateral, and in the spleen. Significant trafficking of dendritic cells (DCs) were only observed in spleens of virus-treatment group, indicating that DCs are primed and activated in the tumor-microenvironment following virotherapy, and trafficked to lymphoid organs for activation of immune cells, such as CD8⁺ T cells. DC priming/activation could be associated with virally enhanced expression of several antigen processing/presentation genes in the tumor microenvironment, as confirmed by NanoString gene expression analysis. Besides DC activation/priming, G47Δ-mIL12 treatment led to up-regulation of CD8⁺ T cell activation markers in the tumor microenvironment and inhibition of tumor angiogenesis. The anti-tumor effects of G47Δ-mIL12 treatment were CD8-dependent. These studies illustrate the ability of G47Δ-mIL12 to immunotherapeutically treat TNBC.