Clinical evaluation of BCL-2/XL levels pre- and post- HER2-targeted therapy

Characterization of BCL-X L , MCL-1, and BAX Protein Expression in Response to Neoadjuvant Chemotherapy in Breast Cancer

The use of chemotherapy has improved the overall treatment of breast cancer, which is frequently administered in the form of neoadjuvant chemotherapy (NAC). Apoptosis is an established cell stress response to NAC in preclinical models; however, there is limited understanding of its role in clinical cancer, specifically, its contribution to favorable pathologic responses in breast cancer therapy. Here, we aimed to characterize the change in protein expression of 3 apoptosis-associated biomarkers, namely, BCL-X L , MCL-1, and BAX in breast cancer in response to NAC. For this, we utilized a set of 68 matched invasive breast cancer FFPE samples that were collected before (pre) and after (post) the exposure to NAC therapy that were characterized by incomplete pathologic response. Immunohistochemistry (IHC) analysis suggested that most of the samples show a decrease in the protein expression of all 3 markers following exposure to NAC as 90%, 69%, and 76% of the matched samples exhibited a decrease in expression for BCL-X L , MCL-1, and BAX, respectively. The median H-score of BCL-X L post-NAC was 150/300 compared with 225/300 pre-NAC ( P value <0.0001). The median H-score of MCL-1 declined from 200 pre-NAC to 160 post-NAC ( P value <0.0001). The median H-score of BAX protein expression decreased from 260 pre-NAC to 190 post-NAC ( P value <0.0001). There was no statistically significant association between the expression of these markers and stage, grade, and hormone receptor profiling (luminal status). Collectively, our data indicate that the expression of apoptosis regulatory proteins changes following exposure to NAC in breast cancer tissue, developing a partial pathologic response.

Txnrd1 as a prognosticator for recurrence, metastasis and response to neoadjuvant chemotherapy and radiotherapy in breast cancer patients

Thioredoxin reductase 1 (Txnrd1) is known to have prognostic significance in a subset of breast cancer patients. Despite the pivotal role of Txnrd1 in regulating several cellular and physiological processes in cancer progression and metastasis, its clinical significance is largely unrecognized. Here, we undertook a retrospective comprehensive meta-analysis of 13,322 breast cancer patients from 43 independent cohorts to assess prognostic and predictive roles of Txnrd1. We observed that Txnrd1 has a positive correlation with tumor grade and size and it is over-expressed in higher-grade and larger tumors. Further, hormone receptor-negative and HER2-positive tumors exhibit elevated Txnrd1 gene expression. Patients with elevated Txnrd1 expression exhibit significant hazards for shorter disease-specific and overall survival. While Txnrd1 has a positive correlation with tumor recurrence and metastasis, it has a negative correlation with time to recurrence and metastasis. Txnrd1High patients exhibit 2.5 years early recurrence and 1.3 years early metastasis as compared to Txnrd1Low cohort. Interestingly, patients with high Txnrd1 gene expression exhibit a pathologic complete response (pCR) to neoadjuvant chemotherapy, but they experience early recurrence after radiotherapy. Txnrd1High MDA-MB-231 cells exhibit significant ROS generation and reduced viability after doxorubicin treatment compared to Txnrd1Low MCF7 cells. Corroborating with findings from meta-analysis, Txnrd1 depletion leads to decreased survival, enhanced sensitivity to radiation induced killing, poor scratch-wound healing, and reduced invasion potential in MDA-MB-231 cells. Thus, Txnrd1 appears to be a potential predictor of recurrence, metastasis and therapy response in breast cancer patients.

Transferrin receptor in primary and metastatic breast cancer: Evaluation of expression and experimental modulation to improve molecular targeting

BACKGROUND

Conjugation of transferrin (Tf) to imaging or nanotherapeutic agents is a promising strategy to target breast cancer. Since the efficacy of these biomaterials often depends on the overexpression of the targeted receptor, we set out to survey expression of transferrin receptor (TfR) in primary and metastatic breast cancer samples, including metastases and relapse, and investigate its modulation in experimental models.

METHODS

Gene expression was investigated by datamining in twelve publicly-available datasets. Dedicated Tissue microarrays (TMAs) were generated to evaluate matched primary and bone metastases as well as and pre and post chemotherapy tumors from the same patient. TMA were stained with the FDA-approved MRQ-48 antibody against TfR and graded by staining intensity (H-score). Patient-derived xenografts (PDX) and isogenic metastatic mouse models were used to study in vivo TfR expression and uptake of transferrin.

RESULTS

TFRC gene and protein expression were high in breast cancer of all subtypes and stages, and in 60-85% of bone metastases. TfR was detectable after neoadjuvant chemotherapy, albeit with some variability. Fluorophore-conjugated transferrin iron chelator deferoxamine (DFO) enhanced TfR uptake in human breast cancer cells in vitro and proved transferrin localization at metastatic sites and correlation of tumor burden relative to untreated tumor mice.

CONCLUSIONS

TfR is expressed in breast cancer, primary, metastatic, and after neoadjuvant chemotherapy. Variability in expression of TfR suggests that evaluation of the expression of TfR in individual patients could identify the best candidates for targeting. Further, systemic iron chelation with DFO may upregulate receptor expression and improve uptake of therapeutics or tracers that use transferrin as a homing ligand.

Single domain antibodies specific for HER2 dimerization domain effectively disrupts HER2 dimerization

Dimer-dependent phosphorylation of HER2 receptor is a key event for the signal transduction of HER family of receptors which correlates with tumor invasion and metastasis. New generation of therapies based on dimerization domain inhibition using monoclonal or fragment antibodies was introduced. A potent method for manufacturing antibodies and antibody fragments is the phage display antibody library method. A recombinant phage was generated using the phage display method from synthetic dAb library. Subtractive biopanning was performed on sepharose 4b resin. Evaluation of success of subtractive biopanning was confirmed by the PCR fingerprinting after the fourth round of biopanning. The fourth round of biopanning results in the isolation of several dimerization domain reactive clones based on the polyclonal phage ELISA results. Monoclonal phage cell ELISA was used to select the positive clones with the highest affinity, and they were subsequently employed for functional tests. Cell-ELISA, MTT assay and dimerization inhibition test revealed that the reactivity and specificity of the selected monoclonal phage to dimerization domain of HER2. Further, Annexin V/PI staining and gene expression analysis showed that increased apoptosis rates. Also, in silico binding of the selected clones to conformational structure of HER2 was applied, using protein-protein docking tool of the ICM-Pro software, and showed sdAbs were specifically interacted with dimerization domain of the receptor. In conclusion, we have identified a single domain targeting HER2 dimerization, which represents a promising therapeutic and diagnostic candidate for HER2-positive cancers. Purified sdAb needs to more research to evaluate it both in vivo and in vitro via functional tests to determine if it can be applied for treatment and diagnostics.

Multi-omics analyses unravel DNA damage repair-related clusters in breast cancer with experimental validation

Background

As one of the most common malignancies worldwide, breast cancer (BC) exhibits high heterogeneity of molecular phenotypes. The evolving view regarding DNA damage repair (DDR) is that it is context-specific and heterogeneous, but its role in BC remains unclear.

Methods

Multi-dimensional data of transcriptomics, genomics, and single-cell transcriptome profiling were obtained to characterize the DDR-related features of BC. We collected 276 DDR-related genes based on the Molecular Signature Database (MSigDB) database and previous studies. We acquired public datasets included the SCAN-B dataset (GEO: GSE96058), METABRIC database, and TCGA-BRCA database. Corresponding repositories such as transcriptomics, genomics, and clinical information were also downloaded. We selected scRNA-seq data from GEO: GSE176078, GSE114727, GSE161529, and GSE158724. Bulk RNA-seq data from GEO: GSE176078, GSE18728, GSE5462, GSE20181, and GSE130788 were extracted for independent analyses.

Results

The DDR classification was constructed in the SCAN-B dataset (GEO: GSE96058) and METABRIC database, Among BC patients, there were two clusters with distinct clinical and molecular characteristics: the DDR-suppressed cluster and the DDR-active cluster. A superior survival rate is found for tumors in the DDR-suppressed cluster, while those with the DDR-activated cluster tend to have inferior prognoses and clinically aggressive behavior. The DDR classification was validated in the TCGA-BRCA cohort and shown similar results. We also found that two clusters have different pathway activities at the genomic level. Based on the intersection of the different expressed genes among these cohorts, we found that PRAME might play a vital role in DDR. The DDR classification was then enabled by establishing a DDR score, which was verified through multilayer cohort analysis. Furthermore, our results revealed that malignant cells contributed more to the DDR score at the single-cell level than nonmalignant cells. Particularly, immune cells with immunosuppressive properties (such as FOXP3+ CD4+ T cells) displayed higher DDR scores among those with distinguishable characteristics.

Conclusion

Collectively, this study performs general analyses of DDR heterogeneity in BC and provides insight into the understanding of individualized molecular and clinicopathological mechanisms underlying unique DDR profiles.

High-throughput screen in vitro identifies dasatinib as a candidate for combinatorial treatment with HER2-targeting drugs in breast cancer

Human epidermal growth factor receptor 2-positive (HER2+) breast cancer is an aggressive subtype of this disease. Targeted treatment has improved outcome, but there is still a need for new therapeutic strategies as some patients respond poorly to treatment. Our aim was to identify compounds that substantially affect viability in HER2+ breast cancer cells in response to combinatorial treatment. We performed a high-throughput drug screen of 278 compounds in combination with trastuzumab and lapatinib using two HER2+ breast cancer cell lines (KPL4 and SUM190PT). The most promising drugs were validated in vitro and in vivo, and downstream molecular changes of the treatments were analyzed. The screen revealed multiple drugs that could be used in combination with lapatinib and/or trastuzumab. The Src-inhibitor dasatinib showed the largest combinatorial effect together with lapatinib in the KPL4 cell line compared to treatment with dasatinib alone (p < 0.01). In vivo, only lapatinib significantly reduced tumor growth (p < 0.05), whereas dasatinib alone, or in combination with lapatinib, did not show significant effects. Protein analyses of the treated xenografts showed significant alterations in protein levels compared to untreated controls, suggesting that all drugs reached the tumor and exerted a measurable effect. In silico analyses suggested activation of apoptosis and reduced activity of survival pathways by all treatments, but the opposite pattern was observed for the combinatorial treatment compared to lapatinib alone.

CD16+ fibroblasts foster a trastuzumab-refractory microenvironment that is reversed by VAV2 inhibition

The leukocyte Fcγ receptor (FcγR)-mediated response is important for the efficacy of therapeutic antibodies; however, little is known about the role of FcγRs in other cell types. Here we identify a subset of fibroblasts in human breast cancer that express CD16 (FcγRIII). An abundance of these cells in HER2⁺ breast cancer patients is associated with poor prognosis and response to trastuzumab. Functionally, upon trastuzumab stimulation, CD16⁺ fibroblasts reduce drug delivery by enhancing extracellular matrix stiffness. Interaction between trastuzumab and CD16 activates the intracellular SYK-VAV2-RhoA-ROCK-MLC2-MRTF-A pathway, leading to elevated contractile force and matrix production. Targeting of a Rho family guanine nucleotide exchange factor, VAV2, which is indispensable for the function of CD16 in fibroblasts rather than leukocytes, reverses desmoplasia provoked by CD16⁺ fibroblasts. Collectively, our study reveals a role for the fibroblast FcγR in drug resistance, and suggests that VAV2 is an attractive target to augment the effects of antibody treatments.

Therapy resistance: opportunities created by adaptive responses to targeted therapies in cancer

Normal cells explore multiple states to survive stresses encountered during development and self-renewal as well as environmental stresses such as starvation, DNA damage, toxins or infection. Cancer cells co-opt normal stress mitigation pathways to survive stresses that accompany tumour initiation, progression, metastasis and immune evasion. Cancer therapies accentuate cancer cell stresses and invoke rapid non-genomic stress mitigation processes that maintain cell viability and thus represent key targetable resistance mechanisms. In this Review, we describe mechanisms by which tumour ecosystems, including cancer cells, immune cells and stroma, adapt to therapeutic stresses and describe three different approaches to exploit stress mitigation processes: (1) interdict stress mitigation to induce cell death; (2) increase stress to induce cellular catastrophe; and (3) exploit emergent vulnerabilities in cancer cells and cells of the tumour microenvironment. We review challenges associated with tumour heterogeneity, prioritizing actionable adaptive responses for optimal therapeutic outcomes, and development of an integrative framework to identify and target vulnerabilities that arise from adaptive responses and engagement of stress mitigation pathways. Finally, we discuss the need to monitor adaptive responses across multiple scales and translation of combination therapies designed to take advantage of adaptive responses and stress mitigation pathways to the clinic.

Clinical and Genetic Predictive Models for the Prediction of Pathological Complete Response to Optimize the Effectiveness for Trastuzumab Based Chemotherapy

Background

Trastuzumab shows excellent benefits for HER2+ breast cancer patients, although 20% treated remain unresponsive. We conducted a retrospective cohort study to optimize neoadjuvant chemotherapy and trastuzumab treatment in HER2+ breast cancer patients.

Methods

Six hundred patients were analyzed to identify clinical characteristics of those not achieving a pathological complete response (pCR) to develop a clinical predictive model. Available RNA sequence data was also reviewed to develop a genetic model for pCR.

Results

The pCR rate was 39.8% and pCR was associated with superior disease free survival and overall survival. ER negativity and PR negativity, higher HER2 IHC scores, higher Ki-67, and trastuzumab use were associated with improved pCR. Weekly paclitaxel and carboplatin had the highest pCR rate (46.70%) and the anthracycline+taxanes regimen had the lowest rate (11.11%). Four published GEO datasets were analyzed and a 10-gene model and immune signature for pCR were developed. Non-pCR patients were ER⁺PR⁺ and had a lower immune signature and gene model score. Hormone receptor status and immune signatures were independent predictive factors of pCR.

Conclusion

Hormone receptor status and a 10-gene model could predict pCR independently and may be applied for patient selection and drug effectiveness optimization.