Predictive factors for relapse in triple-negative breast cancer patients without pathological complete response after neoadjuvant chemotherapy

Impact of obesity on pathological complete remission in early stage breast cancer patients after neoadjuvant chemotherapy: a retrospective study from a German University breast center

PURPOSE

Breast cancer is a primary cause of cancer-related death among women worldwide. Neoadjuvant chemotherapy (NACT) is a cornerstone treatment for locally advanced, non-metastatic breast cancer. Achieving pathological complete response (pCR) is often used as a surrogate marker for long-term outcomes. This study examines the impact of obesity, defined by a body mass index (BMI) over 30 kg/m2, on achieving pCR in patients with early stage breast cancer (eBC) undergoing NACT.

METHODS

A retrospective analysis was conducted on patients with eBC treated with NACT at the University of Tübingen. The primary objective was to assess the impact of obesity on achieving pCR. Logistic regression analysis was used to determine the association between pre-treatment BMI and pCR, adjusting for covariates such as age, tumor stage, grading, and chemotherapy intensity.

RESULTS

The study included 325 patients, with 24% classified as obese. While the univariate logistic regression analysis showed no significant impact of obesity on the odds ratio of achieving pCR, the multivariate analysis, accounting for covariates, demonstrated that obese patients had a significantly higher likelihood of achieving pCR.

CONCLUSION

In this retrospective study, obesity significantly affected the likelihood of achieving pCR in patients with eBC cancer undergoing NACT after adjusting for covariates. While obesity is a known risk factor for breast cancer development and progression, its impact on the efficacy of NACT in terms of achieving pCR was positive in our study. These findings contribute to the ongoing debate in the literature, though the retrospective design and potential uncontrolled factors should be considered.

An Investigation into the In Vitro Targeted Killing of CD44-Expressing Triple-Negative Breast Cancer Cells Using Recombinant Photoimmunotherapeutics Compared to Auristatin-F-Based Antibody-Drug Conjugates

Triple-negative breast cancer (TNBC) is the deadliest form of breast cancer with limited treatment options. The persistence of highly tumorigenic CD44-expressing subpopulation referred to as cancer stem cells (CSCs), endowed with the self-renewal capacity, has been associated with therapeutic resistance, hence clinical relapses. To mitigate these undesired events, targeted immunotherapies using antibody-photoconjugate (APC) or antibody-drug conjugate (ADC), were developed to specifically release cytotoxic payloads within targeted cells overexpressing cognate antigen receptors. Therefore, an αCD44(scFv)-SNAP-tag antibody fusion protein was engineered through genetic fusion of a single-chain antibody fragment (scFv) to a SNAPf-tag fusion protein, capable of self-conjugating with benzylguanine-modified light-sensitive near-infrared (NIR) phthalocyanine dye IRDye700DX (BG-IR700) or the small molecule toxin auristatin-F (BG-AURIF). Binding of the αCD44(scFv)-SNAPf-IR700 photoimmunoconjugate to antigen-positive cells was demonstrated by confocal microscopy and flow cytometry. By switching to NIR irradiation, CD44-expressing TNBC was selectively killed through induced phototoxic activities. Likewise, the αCD44(scFv)-SNAPf-AURIF immunoconjugate was able to selectively accumulate within targeted cells and significantly reduced cell viability through antimitotic activities at nano- to micromolar drug concentrations. This study provides an in vitro proof-of-concept for a future strategy to selectively destroy light-accessible superficial CD44-expressing TNBC tumors and their metastatic lesions which are inaccessible to therapeutic light.

Key target genes related to anti-breast cancer activity of ATRA: A network pharmacology, molecular docking and experimental investigation

All-trans retinoic acid (ATRA) has promising activity against breast cancer. However, the exact mechanisms of ATRA's anticancer effects remain complex and not fully understood. In this study, a network pharmacology and molecular docking approach was applied to identify key target genes related to ATRA's anti-breast cancer activity. Gene/disease enrichment analysis for predicted ATRA targets was performed using the Database for Annotation, Visualization and Integrated Discovery (DAVID), the Comparative Toxicogenomics Database (CTD), and the Gene Set Cancer Analysis (GSCA) database. Protein-Protein Interaction Network (PPIN) generation and analysis was conducted via Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and cytoscape, respectively. Cancer-associated genes were evaluated using MyGeneVenn from the CTD. Differential expression analysis was conducted using the Tumor, Normal, and Metastatic (TNM) Plot tool and the Human Protein Atlas (HPA). The Glide docking program was used to predict ligand-protein binding. Treatment response predication and clinical profile assessment were performed using Receiver Operating Characteristic (ROC) Plotter and OncoDB databases, respectively. Cytotoxicity and gene expression were measured using MTT/fluorescent assays and Real-Time PCR, respectively. Molecular functions of ATRA targets (n = 209) included eicosanoid receptor activity and transcription factor activity. Some enriched pathways included inclusion body myositis and nuclear receptors pathways. Network analysis revealed 35 hub genes contributing to 3 modules, with 16 of them were associated with breast cancer. These genes were involved in apoptosis, cell cycle, androgen receptor pathway, and ESR-mediated signaling, among others. CCND1, ESR1, MMP9, MDM2, NCOA3, and RARA were significantly overexpressed in tumor samples. ATRA showed a high affinity towards CCND1/CDK4 and MMP9. CCND1, ESR1, and MDM2 were associated with poor treatment response and were downregulated after treatment of the breast cancer cell line with ATRA. CCND1 and ESR1 exhibited differential expression across breast cancer stages. Therefore, some part of ATRA's anti-breast cancer activity may be exerted through the CCND1/CDK4 complex.

Prognostic predictive value of Ki-67 in stage I-II triple-negative breast cancer

Aim: Our research aimed to determine an optimal cutoff value and investigate the prognostic predictive function of Ki-67. Materials & methods: We retrospectively enrolled 1146 patients diagnosed with stage I-II triple-negative breast cancer. Disease-free and overall survival were analyzed using the Kaplan-Meier method and the Cox regression model. Results: We classified Ki-67 >45% as the high group (n = 716). A Ki-67 level of >45% was associated with poorer disease-free survival (p = 0.039) and overall survival (p = 0.029). Lymph node stage, neoadjuvant chemotherapy, and radiotherapy were independent predictive variables of prognosis. Conclusion: Triple-negative breast cancer may be further subcategorized according to the Ki-67 level. Neoadjuvant chemotherapy and postoperative radiotherapy can improve the prognosis of early triple-negative breast cancer.

Increased blood draws for ultrasensitive ctDNA and CTCs detection in early breast cancer patients

Early breast cancer patients often experience relapse due to residual disease after treatment. Liquid biopsy is a methodology capable of detecting tumor components in blood, but low concentrations at early stages pose challenges. To detect them, next-generation sequencing has promise but entails complex processes. Exploring larger blood volumes could overcome detection limitations. Herein, a total of 282 high-volume plasma and blood-cell samples were collected for dual ctDNA/CTCs detection using a single droplet-digital PCR assay per patient. ctDNA and/or CTCs were detected in 100% of pre-treatment samples. On the other hand, post-treatment positive samples exhibited a minimum variant allele frequency of 0.003% for ctDNA and minimum cell number of 0.069 CTCs/mL of blood, surpassing previous investigations. Accurate prediction of residual disease before surgery was achieved in patients without a complete pathological response. A model utilizing ctDNA dynamics achieved an area under the ROC curve of 0.92 for predicting response. We detected disease recurrence in blood in the three patients who experienced a relapse, anticipating clinical relapse by 34.61, 9.10, and 7.59 months. This methodology provides an easily implemented alternative for ultrasensitive residual disease detection in early breast cancer patients.

Differential Expression of NOTCH-1 and Its Molecular Targets in Response to Metronomic Followed by Conventional Therapy in a Patient with Advanced Triple-Negative Breast Cancer

A group of 27 patients diagnosed with metastatic triple-negative breast cancer (mTNBC) was randomly distributed into two groups and underwent different lines of metronomic treatment (mCHT). The former group (N 14) received first-line mCHT and showed a higher overall survival rate than the second group (N 13), which underwent second-line mCHT. Analysis of one patient still alive from the first group, diagnosed with mTNBC in 2019, showed a complete metabolic response (CMR) after a composite approach implicating first-line mCHT followed by second-line epirubicin and third-line nab-paclitaxel, and was chosen for subsequent molecular characterization. We found altered expression in the cancer stemness-associated gene NOTCH-1 and its corresponding protein. Additionally, we found changes in the expression of oncogenes, such as MYC and AKT, along with their respective proteins. Overall, our data suggest that a first-line treatment with mCHT followed by MTD might be effective by negatively regulating stemness traits usually associated with the emergence of drug resistance.