Applicability of Anticancer Drugs for the Triple-Negative Breast Cancer Based on Homologous Recombination Repair Deficiency

Poly (adenosine diphosphate-ribose) polymerase inhibitors in the treatment of triple-negative breast cancer with homologous repair deficiency

Breast cancer (BC) is a highly heterogeneous disease, and the presence of germline breast cancer gene mutation (gBRCAm) is associated with a poor prognosis. Triple-negative breast cancer (TNBC) is a BC subtype, characterized by the absence of hormone and growth factor receptor expression, making therapeutic decisions difficult. Defects in the DNA damage response pathway due to mutation in breast cancer genes (BRCA 1/2) lead to homologous recombination deficiency (HRD). However, in HRD conditions, poly (adenosine diphosphate-ribose) polymerase (PARP) proteins repair DNA damage and lead to tumor cell survival. Biological understanding of HRD leads to the development of PARP inhibitors (PARPi), which trap PARP proteins and cause genomic instability and tumor cell lysis. HRD assessment can be an important biomarker in identifying gBRCAm patients with BC who could benefit from PARPi therapy. HRD can be identified by homologous recombination repair (HRR) gene-based assays, genomic-scarring assays and mutational signatures, transcription and protein expression profiles, and functional assays. However, gold standard methodologies that are robust and reliable to assess HRD are not available currently. Hence, there is a pressing need to develop accurate biomarkers identifying HRD tumors to guide targeted therapies such as PARPi in patients with BC. HRD assessment has shown fruitful outcomes in chemotherapy studies and preliminary evidence on PARPi intervention as monotherapy and combination therapy in HRD-stratified patients. Furthermore, ongoing trials are exploring the potential of PARPi in BC and clinically complex TNBC settings, where HRD testing is used as an adjunct to stratify patients based on BRCA mutations.

In-silico approaches to assessing multiple high-level drug-drug and drug-disease adverse drug effects

INTRODUCTION

Pharmacovigilance plays a pivotal role in monitoring adverse events (AEs) related to chemical substances in human/animal populations. With increasing spontaneous-reporting systems, researchers turned to in-silico approaches to efficiently analyze drug safety profiles. Here, we review in-silico methods employed for assessing multiple drug-drug/drug-disease AEs covered by comparative analyses and visualization strategies.

AREAS COVERED

Disproportionality, involving multi-stage statistical methodologies and data processing, identifies safety signals among drug-AE pairs. By stratifying data based on disease indications/demographics, researchers address confounders and assess drug safety. Comparative analyses, including clustering techniques and visualization techniques, assess drug similarities, patterns, and trends, calculate correlations, and identify distinct toxicities. Furthermore, we conducted a thorough Scopus search on 'pharmacovigilance,' yielding 5,836 publications spanning 2003 to 2023.

EXPERT OPINION

Pharmacovigilance relies on diverse data sources, presenting challenges in the integration of in-silico approaches and requiring compliance with regulations and AI adoption. Systematic use of statistical analyses enables identifications of potential risks with drugs. Frequentist and Bayesian methods are used in disproportionalities, each with its strengths and weaknesses. Integration of pharmacogenomics with pharmacovigilance enables personalized medicine, with AI further enhancing patient engagement. This multidisciplinary approach holds promise, improving drug efficacy and safety, and should be a core mission of One-Health studies.

Microsatellite instability states serve as predictive biomarkers for tumors chemotherapy sensitivity

There is an urgent need for markers to predict the efficacy of different chemotherapy drugs. Herein, we examined whether microsatellite instability (MSI) status can predict tumor multidrug sensitivity and explored the underlying mechanisms. We downloaded data from several public databases. Drug sensitivity was compared between the high microsatellite instability (MSI-H) and microsatellite-stable/low microsatellite instability (MSS/MSI-L) groups. In addition, we performed pathway enrichment analysis and cellular chemosensitivity assays to explore the mechanisms by which MSI status may affect drug sensitivity and assessed the differences between drug-treated and control cell lines. We found that multiple MSI-H tumors were more sensitive to a variety of chemotherapy drugs than MSS/MSI-L tumors, and especially for CRC, chemosensitivity is enhanced through the downregulation of DDR pathways such as NHEJ. Additional DNA damage caused by chemotherapeutic drugs results in further downregulation of DDR pathways and enhances drug sensitivity, forming a cycle of increasing drug sensitivity.