Recent Advances with Precision Medicine Treatment for Breast Cancer including Triple-Negative Sub-Type

Harnessing the synergistic potential of NK1R antagonists and selective COX-2 inhibitors for simultaneous targeting of TNBC cells and cancer stem cells

Triple-negative breast cancer (TNBC) lacks the expression of oestrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2), rendering it unresponsive to endocrine therapy and HER2 targeted treatments. Though certain chemotherapeutics targeting the cell cycle have shown efficacy to a certain extent, the presence of chemotherapy-resistant cancer stem cells (CSCs) presents a significant challenge in tackling TNBC. Multiple lines of evidence suggest the upregulation of neuropeptide Substance P (SP), its NK-1 receptor (NK1R) and the Cyclooxygenase-2 (COX-2) enzyme in TNBC patients. Upregulation of the SP/NK1R system and COX-2 influences major signalling pathways involved in cell proliferation, growth, survival, angiogenesis, inflammation, metastasis and stem cell activity. The simultaneous activation and crosstalk between the pathways activated by SP/NK1R and COX-2 consequently increase the levels of key regulators of self-renewal pathways in CSCs, promoting stemness. The combination therapy with NK1R antagonists and COX-2 inhibitors can simultaneously target TNBC cells and CSCs, thereby enhancing treatment efficacy and reducing the risk of recurrence and relapse. This review discusses the rationale for combining NK1R antagonists and COX-2 inhibitors for the better management of TNBC and a novel strategy to deliver drug cargo precisely to the tumour site to address the challenges associated with off-target binding.

Injectable and NIR-responsive CDN-POM hydrogels for combined non-inflammatory photo-immunotherapy

Similar to clinically applied thermal ablation techniques, the cellular necrosis that occurs during photothermal tumor therapy (PTT) can induce inflammatory response, severely compromising the therapeutic efficacy and clinical translation of the PTT. Inspired by the remarkable ROS-scavenging activity and high photothermal efficiency of molybdenum-based polyoxometalate (POM) and the immunostimulatory effect of cyclic dinucleotides (CDNs), a NIR-responsive and injectable DNA-mediated hybrid hydrogel (CDN-POM) has been developed. The hydrogels have superior photothermal efficiency (43.41%) to POM, impressive anti-inflammatory capability and prolonged intratumoral CDN-releasing behavior, thus enabling synergistic anti-tumor therapeutic outcomes. Meanwhile, local treatment induced by CDN-POM hydrogels displays minimal side effects on normal tissue. Taking advantage of the high phototherapeutic effect, ROS-scavenging activity and sustained CDN release of CDN-POM hydrogels, a novel combined approach that integrates photothermal therapy and immunotherapy of breast tumor is successfully pioneered.

Investigating the effects of artificial intelligence on the personalization of breast cancer management: a systematic study

BACKGROUND

Providing appropriate specialized treatment to the right patient at the right time is considered necessary in cancer management. Targeted therapy tailored to the genetic changes of each breast cancer patient is a desirable feature of precision oncology, which can not only reduce disease progression but also potentially increase patient survival. The use of artificial intelligence alongside precision oncology can help physicians by identifying and selecting more effective treatment factors for patients.

METHOD

A systematic review was conducted using the PubMed, Embase, Scopus, and Web of Science databases in September 2023. We performed the search strategy with keywords, namely: Breast Cancer, Artificial intelligence, and precision Oncology along with their synonyms in the article titles. Descriptive, qualitative, review, and non-English studies were excluded. The quality assessment of the articles and evaluation of bias were determined based on the SJR journal and JBI indices, as well as the PRISMA2020 guideline.

RESULTS

Forty-six studies were selected that focused on personalized breast cancer management using artificial intelligence models. Seventeen studies using various deep learning methods achieved a satisfactory outcome in predicting treatment response and prognosis, contributing to personalized breast cancer management. Two studies utilizing neural networks and clustering provided acceptable indicators for predicting patient survival and categorizing breast tumors. One study employed transfer learning to predict treatment response. Twenty-six studies utilizing machine-learning methods demonstrated that these techniques can improve breast cancer classification, screening, diagnosis, and prognosis. The most frequent modeling techniques used were NB, SVM, RF, XGBoost, and Reinforcement Learning. The average area under the curve (AUC) for the models was 0.91. Moreover, the average values for accuracy, sensitivity, specificity, and precision were reported to be in the range of 90-96% for the models.

CONCLUSION

Artificial intelligence has proven to be effective in assisting physicians and researchers in managing breast cancer treatment by uncovering hidden patterns in complex omics and genetic data. Intelligent processing of omics data through protein and gene pattern classification and the utilization of deep neural patterns has the potential to significantly transform the field of complex disease management.

Medicinal Mushrooms in Metastatic Breast Cancer: What Is Their Therapeutic Potential as Adjuvant in Clinical Settings?

Breast cancer (BC) is the most commonly diagnosed tumor, remaining one of the leading causes of morbidity and mortality in females worldwide, with the highest rates in Western countries. Among metastatic BC (MBC), triple-negative breast cancer (TNBC) is characterized by the lack of expression of specific receptors, and differs from other subgroups of BC for its increased growth and fast spreading, with reduced treatment possibilities and a worse outcome. Actually, MBC patients are extremely prone to metastasis and consequent relapses, which affect distant target organs (e.g., brain, lung, bone and liver). Hence, the comprehension of biological mechanisms underlying the BC metastatization process is a key requirement to conceive/set up innovative medicinal strategies, with the goal to achieve long-lasting therapeutic efficacy, reducing adverse effects, and also ameliorating Quality of Life (QoL). Bioactive metabolites isolated from medicinal mushrooms (MMs) used as a supportive treatment, combined with conventional oncology, have recently gained wide interest. In fact, mounting evidence has revealed their peculiar promising immunomodulatory, anti-inflammatory and anticancer activities, even though these effects have to be further clarified. Among the group of most promising MMs are Lentinula edodes, Grifola frondosa, Ganoderma lucidum, Ophiocordyceps sinensis and Agaricus blazei, which are already employed in conventional cancer protocols in Asia and China. Recently, a growing number of studies have focused on the pharmacology and feasibility of MM-derived bioactive compounds as a novel valuable approach to propose an effective adjuvant therapy for MBC patients' management. In this review, we summarized the current state of knowledge on the abovementioned MM-derived bioactive compounds and their therapeutic potential in clinical settings.

A Review of Pseudomyxoma Peritonei: Insights Into Diagnosis, Management, and Prognosis

Pseudomyxoma peritonei (PMP) is a rare and complex clinical syndrome characterized by the accumulation of mucinous ascites within the peritoneal cavity, typically associated with mucinous tumours of appendiceal origin. Despite its rarity, PMP poses significant challenges in diagnosis and management due to its indolent yet locally aggressive nature. This comprehensive review provides insights into the diagnosis, management, and prognosis of PMP, synthesizing current evidence and emerging trends in the field. Challenges and opportunities in PMP management are discussed, along with recommendations for clinical practice emphasizing the importance of a multidisciplinary approach and specialized care. Despite ongoing challenges, advances in surgical techniques, perioperative chemotherapy, and emerging therapies offer hope for improved outcomes and quality of life for PMP patients.

Seizing the moment: The time for harnessing electronic patient-reported outcome measures for enhanced and sustainable metastatic breast cancer care is now

The sustainability of healthcare systems is under pressure. Unlike care for many other chronic diseases, cancer care has yet to empower patients in effectively self-managing both the medical and emotional consequences of their condition, including adapting to changes in lifestyle and work, which is essential to achieve optimal health and recovery. Although proposed as a potential solution for sustainable healthcare and support for optimal health and recovery already decades ago, practical implementation of digital care lags behind. We believe electronic patient reported outcome measures (ePROMs) could play an important role in creating sustainable healthcare, both to guide complex treatment pathways and to empower survivors to self-manage consequences of diagnosis and treatment. That is, ePROMs can be used for screening and monitoring of symptoms, but also for treatment decision-making and to facilitate communication about quality of life. We therefore see opportunities for improvements in quality of care, quality of life, and survival of cancer patients, as well as research opportunities, as ePROMs collection can lead to better understanding of care needs. The '10 Actions for Change report' of the Advanced Breast Cancer Global Alliance stresses a critical need for improvement of care for metastatic breast cancer (MBC) patients. We therefore in this paper focus on MBC care and research.

New hopes for the breast cancer treatment: perspectives on the oncolytic virus therapy

Oncolytic virus (OV) therapy has emerged as a promising frontier in cancer treatment, especially for solid tumours. While immunotherapies like immune checkpoint inhibitors and CAR-T cells have demonstrated impressive results, their limitations in inducing complete tumour regression have spurred researchers to explore new approaches targeting tumours resistant to current immunotherapies. OVs, both natural and genetically engineered, selectively replicate within cancer cells, inducing their lysis while sparing normal tissues. Recent advancements in clinical research and genetic engineering have enabled the development of targeted viruses that modify the tumour microenvironment, triggering anti-tumour immune responses and exhibiting synergistic effects with other cancer therapies. Several OVs have been studied for breast cancer treatment, including adenovirus, protoparvovirus, vaccinia virus, reovirus, and herpes simplex virus type I (HSV-1). These viruses have been modified or engineered to enhance their tumour-selective replication, reduce toxicity, and improve oncolytic properties.Newer generations of OVs, such as Oncoviron and Delta-24-RGD adenovirus, exhibit heightened replication selectivity and enhanced anticancer effects, particularly in breast cancer models. Clinical trials have explored the efficacy and safety of various OVs in treating different cancers, including melanoma, nasopharyngeal carcinoma, head and neck cancer, and gynecologic malignancies. Notably, Talimogene laherparepvec (T-VEC) and Oncorine have. been approved for advanced melanoma and nasopharyngeal carcinoma, respectively. However, adverse effects have been reported in some cases, including flu-like symptoms and rare instances of severe complications such as fistula formation. Although no OV has been approved specifically for breast cancer treatment, ongoing preclinical clinical trials focus on four groups of viruses. While mild adverse effects like low-grade fever and nausea have been observed, the effectiveness of OV monotherapy in breast cancer remains insufficient. Combination strategies integrating OVs with chemotherapy, radiotherapy, or immunotherapy, show promise in improving therapeutic outcomes. Oncolytic virus therapy holds substantial potential in breast cancer treatment, demonstrating safety in trials. Multi-approach strategies combining OVs with conventional therapies exhibit more promising therapeutic effects than monotherapy, signalling a hopeful future for OV-based breast cancer treatments.

A non-negative spike-and-slab lasso generalized linear stacking prediction modeling method for high-dimensional omics data

BACKGROUND

High-dimensional omics data are increasingly utilized in clinical and public health research for disease risk prediction. Many previous sparse methods have been proposed that using prior knowledge, e.g., biological group structure information, to guide the model-building process. However, these methods are still based on a single model, offen leading to overconfident inferences and inferior generalization.

RESULTS

We proposed a novel stacking strategy based on a non-negative spike-and-slab Lasso (nsslasso) generalized linear model (GLM) for disease risk prediction in the context of high-dimensional omics data. Briefly, we used prior biological knowledge to segment omics data into a set of sub-data. Each sub-model was trained separately using the features from the group via a proper base learner. Then, the predictions of sub-models were ensembled by a super learner using nsslasso GLM. The proposed method was compared to several competitors, such as the Lasso, grlasso, and gsslasso, using simulated data and two open-access breast cancer data. As a result, the proposed method showed robustly superior prediction performance to the optimal single-model method in high-noise simulated data and real-world data. Furthermore, compared to the traditional stacking method, the proposed nsslasso stacking method can efficiently handle redundant sub-models and identify important sub-models.

CONCLUSIONS

The proposed nsslasso method demonstrated favorable predictive accuracy, stability, and biological interpretability. Additionally, the proposed method can also be used to detect new biomarkers and key group structures.

Antibody-drug conjugates in cancer therapy: innovations, challenges, and future directions

The emergence of antibody-drug conjugates (ADCs) as a potential therapeutic avenue in cancer treatment has garnered significant attention. By combining the selective specificity of monoclonal antibodies with the cytotoxicity of drug molecules, ADCs aim to increase the therapeutic index, selectively targeting cancer cells while minimizing systemic toxicity. Various ADCs have been licensed for clinical usage, with ongoing research paving the way for additional options. However, the manufacture of ADCs faces several challenges. These include identifying suitable target antigens, enhancing antibodies, linkers, and payloads, and managing resistance mechanisms and side effects. This review focuses on the strategies to overcome these hurdles, such as site-specific conjugation techniques, novel antibody formats, and combination therapy. Our focus lies on current advancements in antibody engineering, linker technology, and cytotoxic payloads while addressing the challenges associated with ADC development. Furthermore, we explore the future potential of personalized medicine, leveraging individual patients' molecular profiles, to propel ADC treatments forward. As our understanding of the molecular mechanisms driving cancer progression continues to expand, we anticipate the development of new ADCs that offer more effective and personalized therapeutic options for cancer patients.

Prognostic significance of HALP score and combination of peripheral blood multiple indicators in patients with early breast cancer

Background

To assess the prognostic significance of preoperative hemoglobin, albumin, lymphocyte, and platelet (HALP) score combined with multiple peripheral blood indicators in patients with early breast cancer (EBC).

Methods

A total of 411 patients with early invasive breast cancer underwent breast-conserving surgery or radical surgery at Changzhou No.2 People's Hospital from January 2015 to December 2020. The cut-off values of HALP, neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR), and prognostic nutritional index (PNI) were calculated using the software X-tile. The primary outcomes were recurrence-free survival (RFS), which was analyzed using the Kaplan Meier (K-M) method, while log-rank was used to test the differences between high and low curves. Cox regression analysis was used to analyze the prognostic significance of HALP. Furthermore, the prognostic predictive value of independent prognostic factors was determined using the receiver operating characteristic (ROC) curve.

Results

Low HALP score (P<0.0001), high PLR (P<0.0001), and low LMR (P = 0.0345) were significantly associated with worse RFS. Body mass index (BMI)<24 (P = 0.0036), no diabetes (P = 0.0205), earlier TNM stage (P = 0.0005), and no lymph node metastasis (P = 0.0022) were positively correlated with longer survival HALP scores (hazard ratio [HR] 95% confidence interval [CI]: 0.08 (0.024-0.265), P<0.0001), BMI (HR 95%CI: 0.254 (0.109-0.589), P = 0.001), TNM stage (HR 95%CI: 0.153 (0.041-0.571), P = 0.005), and diabetes (HR 95%CI: 0.259 (0.085-0.785), P = 0.017) were demonstrated as independent prognostic factors by Cox regression analysis. The ROC curves depicted that the two most valuable factors were TNM stage and HALP, and combined independent factors were more accurate in prognostic prediction than any single factor. This further indicated that the TNM stage combined HALP or BMI were more valuable combinations.

Conclusion

The HALP score was an independent prognostic factor for EBC and was significantly associated with worse RFS. This score may predict the probability of postoperative tumor recurrence or metastasis before surgery.

Triple-negative breast cancer: from none to multiple therapeutic targets in two decades

Triple-negative breast cancers (TNBCs) are more likely to occur in younger patients and have a poor prognosis. They are highly heterogeneous tumors consisting of different molecular subtypes. The only common characteristic among them is the absence of targets for endocrine therapy and human epidermal growth factor receptor 2 (HER2) blockade. In the past two decades, there has been an increased understanding of these tumors from a molecular perspective, leading to their stratification according to new therapeutic strategies. TNBC has ushered breast carcinomas into the era of immunotherapy. The higher frequency of germline BRCA mutations in these tumors enables targeting this repair defect by drugs like PARP inhibitors, resulting in synthetic lethality in neoplastic cells. Additionally, we have the identification of new molecules to which this generation of smart drugs, such as antibody-drug conjugates (ADCs), are directed. In this review, we will discuss the trajectory of this knowledge in a systematic manner, presenting the molecular bases, therapeutic possibilities, and biomarkers.

Adverse Crosstalk between Extracellular Matrix Remodeling and Ferroptosis in Basal Breast Cancer

(1) Background: Breast cancer is a frequent heterogeneous disorder diagnosed in women and causes a high number of mortality among this population due to rapid metastasis and disease recurrence. Ferroptosis can inhibit breast cancer cell growth, improve the sensitivity of chemotherapy and radiotherapy, and inhibit distant metastases, potentially impacting the tumor microenvironment. (2) Methods: Through data mining, the ferroptosis/extracellular matrix remodeling literature text-mining results were integrated into the breast cancer transcriptome cohort, taking into account patients with distant relapse-free survival (DRFS) under adjuvant therapy (anthracyclin + taxanes) with validation in an independent METABRIC cohort, along with the MDA-MB-231 and HCC338 transcriptome functional experiments with ferroptosis activations (GSE173905). (3) Results: Ferroptosis/extracellular matrix remodeling text-mining identified 910 associated genes. Univariate Cox analyses focused on breast cancer (GSE25066) selected 252 individual significant genes, of which 170 were found to have an adverse expression. Functional enrichment of these 170 adverse genes predicted basal breast cancer signatures. Through text-mining, some ferroptosis-significant adverse-selected genes shared citations in the domain of ECM remodeling, such as TNF, IL6, SET, CDKN2A, EGFR, HMGB1, KRAS, MET, LCN2, HIF1A, and TLR4. A molecular score based on the expression of the eleven genes was found predictive of the worst prognosis breast cancer at the univariate level: basal subtype, short DRFS, high-grade values 3 and 4, and estrogen and progesterone receptor negative and nodal stages 2 and 3. This eleven-gene signature was validated as regulated by ferroptosis inductors (erastin and RSL3) in the triple-negative breast cancer cellular model MDA-MB-231. (4) Conclusions: The crosstalk between ECM remodeling-ferroptosis functionalities allowed for defining a molecular score, which has been characterized as an independent adverse parameter in the prognosis of breast cancer patients. The gene signature of this molecular score has been validated to be regulated by erastin/RSL3 ferroptosis activators. This molecular score could be promising to evaluate the ECM-related impact of ferroptosis target therapies in breast cancer.

Disintegrin-like Protein Strategy to Inhibit Aggressive Triple-Negative Breast Cancer

Venoms are a rich source of bioactive compounds, and among them is leberagin-C (Leb-C), a disintegrin-like protein derived from the venom of Macrovipera lebetina transmediterrannea snakes. Leb-C has shown promising inhibitory effects on platelet aggregation. Previous studies have demonstrated that this SECD protein specifically targets α5β1, αvβ3, and αvβ6 integrins through a mimic mechanism of RGD disintegrins. In our current study, we focused on exploring the potential effects of Leb-C on metastatic breast cancer. Our findings revealed that Leb-C disrupted the adhesion, migration, and invasion capabilities of MDA-MB-231 breast cancer cells and its highly metastatic D3H2LN sub-population. Additionally, we observed significant suppression of adhesion, migration, and invasion of human umbilical vein endothelial cells (HUVECs). Furthermore, Leb-C demonstrated a strong inhibitory effect on fibroblast-growth-factor-2-induced proliferation of HUVEC. We conducted in vivo experiments using nude mice and found that treatment with 2 µM of Leb-C resulted in a remarkable 73% reduction in D3H2LN xenograft tumor size. Additionally, quantification of intratumor microvessels revealed a 50% reduction in tumor angiogenesis in xenograft after 21 days of twice-weekly treatment with 2 µM of Leb-C. Collectively, these findings suggest the potential utility of this disintegrin-like protein for inhibiting aggressive and resistant metastatic breast cancer.