Computational selection of antibody-drug conjugate targets for breast cancer

Unraveling Biomarker Signatures in Triple-Negative Breast Cancer: A Systematic Review for Targeted Approaches

Triple-negative breast cancer (TNBC) is one of the most aggressive subtypes of breast cancer, marked by poor outcomes and dismal prognosis. Due to the absence of targetable receptors, chemotherapy still represents the main therapeutic option. Therefore, current research is now focusing on understanding the specific molecular pathways implicated in TNBC, in order to identify novel biomarker signatures and develop targeted therapies able to improve its clinical management. With the aim of identifying novel molecular features characterizing TNBC, elucidating the mechanisms by which these molecular biomarkers are implicated in the tumor development and progression, and assessing the impact on cancerous cells following their inhibition or modulation, we conducted a literature search from the earliest works to December 2023 on PubMed, Scopus, and Web Of Science. A total of 146 studies were selected. The results obtained demonstrated that TNBC is characterized by a heterogeneous molecular profile. Several biomarkers have proven not only to be characteristic of TNBC but also to serve as potential effective therapeutic targets, holding the promise of a new era of personalized treatments able to improve its prognosis. The pre-clinical findings that have emerged from our systematic review set the stage for further investigation in forthcoming clinical trials.

Antibody-drug conjugates come of age in oncology

Antibody-drug conjugates (ADCs) combine the specificity of monoclonal antibodies with the potency of highly cytotoxic agents, potentially reducing the severity of side effects by preferentially targeting their payload to the tumour site. ADCs are being increasingly used in combination with other agents, including as first-line cancer therapies. As the technology to produce these complex therapeutics has matured, many more ADCs have been approved or are in late-phase clinical trials. The diversification of antigenic targets as well as bioactive payloads is rapidly broadening the scope of tumour indications for ADCs. Moreover, novel vector protein formats as well as warheads targeting the tumour microenvironment are expected to improve the intratumour distribution or activation of ADCs, and consequently their anticancer activity for difficult-to-treat tumour types. However, toxicity remains a key issue in the development of these agents, and better understanding and management of ADC-related toxicities will be essential for further optimization. This Review provides a broad overview of the recent advances and challenges in ADC development for cancer treatment.

Antibody-drug conjugates: Smart chemotherapy delivery across tumor histologies

As distinct cancer biomarkers have been discovered in recent years, a need to reclassify tumors by more than their histology has been proposed, and therapies are now tailored to treat cancers based on specific molecular aberrations and immunologic markers. In fact, multiple histology-agnostic therapies are currently adopted in clinical practice for treating patients regardless of their tumor site of origin. In parallel with this new model for drug development, in the past few years, several novel antibody-drug conjugates (ADCs) have been approved to treat solid tumors, benefiting from engineering improvements in the conjugation process and the introduction of novel linkers and payloads. With the recognition that numerous surface targets are expressed across various cancer histologies, alongside the remarkable activity of modern ADCs, this drug class has been increasingly evaluated as suitable for a histology-agnostic expansion of indication. For illustration, the anti-HER2 ADC trastuzumab deruxtecan has demonstrated compelling activity in HER2-overexpressing breast, gastric, colorectal, and lung cancer. Examples of additional novel and potentially histology-agnostic ADC targets include trophoblast cell-surface antigen 2 (Trop-2) and nectin-4, among others. In the current review article, the authors summarize the current approvals of ADCs by the US Food and Drug Administration focusing on solid tumors and discuss the challenges and opportunities posed by the multihistological expansion of ADCs.

Developing Novel Anticancer Drugs for Targeted Populations: An Update

BACKGROUND

Due to higher failure rates, lengthy time and high cost of the traditional de novo drug discovery and development process, the rate of opportunity to get new, safe and efficacious drugs for the targeted population, including pediatric patients with cancer, becomes sluggish.

OBJECTIVES

This paper discusses the development of novel anticancer drugs focusing on the identification and selection of targeted anticancer drug development for the targeted population.

METHODS

Information presented in this review was obtained from different databases, including PUBMED, SCOPUS, Web of Science, and EMBASE. Various keywords were used as search terms.

RESULTS

The pharmaceutical companies currently are executing drug repurposing as an alternative means to accelerate the drug development process that reduces the risk of failure, time and cost, which take 3-12 years with almost 25% overall probability of success as compared to de novo drug discovery and development process (10- 17 years) which has less than 10% probability of success. An alternative strategy to the traditional de novo drug discovery and development process, called drug repurposing, is also presented.

CONCLUSION

Therefore, to continue with the progress of developing novel anticancer drugs for the targeted population, identification and selection of target to specific disease type is important. Considering the aspects of the age of the patient and the disease stages such as each cancer types are different when we study the disease at a molecular level. Drug repurposing technique becomes an influential alternative strategy to discover and develop novel anticancer drug candidates.

Identification of transcriptional subtypes in lung adenocarcinoma and squamous cell carcinoma through integrative analysis of microarray and RNA sequencing data

Classification of tumors into subtypes can inform personalized approaches to treatment including the choice of targeted therapies. The two most common lung cancer histological subtypes, lung adenocarcinoma and lung squamous cell carcinoma, have been previously divided into transcriptional subtypes using microarray data, and corresponding signatures were subsequently used to classify RNA-seq data. Cross-platform unsupervised classification facilitates the identification of robust transcriptional subtypes by combining vast amounts of publicly available microarray and RNA-seq data. However, cross-platform classification is challenging because of intrinsic differences in data generated using the two gene expression profiling technologies. In this report, we show that robust gene expression subtypes can be identified in integrated data representing over 3500 normal and tumor lung samples profiled using two widely used platforms, Affymetrix HG-U133 Plus 2.0 Array and Illumina HiSeq RNA sequencing. We tested and analyzed consensus clustering for 384 combinations of data processing methods. The agreement between subtypes identified in single-platform and cross-platform normalized data was then evaluated using a variety of statistics. Results show that unsupervised learning can be achieved with combined microarray and RNA-seq data using selected preprocessing, cross-platform normalization, and unsupervised feature selection methods. Our analysis confirmed three lung adenocarcinoma transcriptional subtypes, but only two consistent subtypes in squamous cell carcinoma, as opposed to four subtypes previously identified. Further analysis showed that tumor subtypes were associated with distinct patterns of genomic alterations in genes coding for therapeutic targets. Importantly, by integrating quantitative proteomics data, we were able to identify tumor subtype biomarkers that effectively classify samples on the basis of both gene and protein expression. This study provides the basis for further integrative data analysis across gene and protein expression profiling platforms.

Data-Driven Discovery of Molecular Targets for Antibody-Drug Conjugates in Cancer Treatment

Antibody-drug conjugate therapy has attracted considerable attention in recent years. Since the selection of appropriate targets is a critical aspect of antibody-drug conjugate research and development, a big data research for discovery of candidate targets per tumor type is outstanding and of high interest. Thus, the purpose of this study was to identify and prioritize candidate antibody-drug conjugate targets with translational potential across common types of cancer by mining the Human Protein Atlas, as a unique big data resource. To perform a multifaceted screening process, XML and TSV files including immunohistochemistry expression data for 45 normal tissues and 20 tumor types were downloaded from the Human Protein Atlas website. For genes without high protein expression across critical normal tissues, a quasi H-score (range, 0-300) was computed per tumor type. All genes with a quasi H - score ≥ 150 were extracted. Of these, genes with cell surface localization were selected and included in a multilevel validation process. Among 19670 genes that encode proteins, 5520 membrane protein-coding genes were included in this study. During a multistep data mining procedure, 332 potential targets were identified based on the level of the protein expression across critical normal tissues and 20 tumor types. After validation, 23 cell surface proteins were identified and prioritized as candidate antibody-drug conjugate targets of which two have interestingly been approved by the FDA for use in solid tumors, one has been approved for lymphoma, and four have currently been entered in clinical trials. In conclusion, we identified and prioritized several candidate targets with translational potential, which may yield new clinically effective and safe antibody-drug conjugates. This large-scale antibody-based proteomic study allows us to go beyond the RNA-seq studies, facilitates bench-to-clinic research of targeted anticancer therapeutics, and offers valuable insights into the development of new antibody-drug conjugates.

LRP8 is overexpressed in estrogen-negative breast cancers and a potential target for these tumors

Triple‐negative breast cancer (TNBC) is the breast cancer subtype with the worst prognosis. New treatments improving the survival of TNBC patients are, therefore, urgently required. We performed a transcriptome microarray analysis to identify new treatment targets for TNBC. We found that low‐density lipoprotein receptor‐related protein 8 (LRP8) was more strongly expressed in estrogen receptor‐negative breast tumors, including TNBCs and those overexpressing HER2, than in luminal breast tumors and normal breast tissues. LRP8 depletion decreased cell proliferation more efficiently in estrogen receptor‐negative breast cancer cell lines: TNBC and HER2 overexpressing cell lines. We next focused on TNBC cells for which targeted therapies are not available. LRP8 depletion induced an arrest of the cell cycle progression in G1 phase and programmed cell death. We also found that LRP8 is required for anchorage‐independent growth in vitro, and that its depletion in vivo slowed tumor growth in a xenograft model. Our findings suggest that new approaches targeting LRP8 may constitute promising treatments for hormone‐negative breast cancers, those overexpressing HER2 and TNBCs.

Strategies and challenges for the next generation of antibody-drug conjugates

Antibody-drug conjugates (ADCs) are one of the fastest growing classes of oncology therapeutics. After half a century of research, the approvals of brentuximab vedotin (in 2011) and trastuzumab emtansine (in 2013) have paved the way for ongoing clinical trials that are evaluating more than 60 further ADC candidates. The limited success of first-generation ADCs (developed in the early 2000s) informed strategies to bring second-generation ADCs to the market, which have higher levels of cytotoxic drug conjugation, lower levels of naked antibodies and more-stable linkers between the drug and the antibody. Furthermore, lessons learned during the past decade are now being used in the development of third-generation ADCs. In this Review, we discuss strategies to select the best target antigens as well as suitable cytotoxic drugs; the design of optimized linkers; the discovery of bioorthogonal conjugation chemistries; and toxicity issues. The selection and engineering of antibodies for site-specific drug conjugation, which will result in higher homogeneity and increased stability, as well as the quest for new conjugation chemistries and mechanisms of action, are priorities in ADC research.