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Antibody–drug conjugates (ADCs) are a promising cancer treatment modality that enables the selective delivery of highly cytotoxic payloads to tumours. However, realizing the full potential of this platform necessitates innovative molecular designs to tackle several clinical challenges such as drug resistance, tumour heterogeneity and treatment-related adverse effects. Several emerging ADC formats exist, including bispecific ADCs, conditionally active ADCs (also known as probody–drug conjugates), immune-stimulating ADCs, protein-degrader ADCs and dual-drug ADCs, and each offers unique capabilities for tackling these various challenges. For example, probody–drug conjugates can enhance tumour specificity, whereas bispecific ADCs and dual-drug ADCs can address resistance and heterogeneity with enhanced activity. The incorporation of immune-stimulating and protein-degrader ADCs, which have distinct mechanisms of action, into existing treatment strategies could enable multimodal cancer treatment. Despite the promising outlook, the importance of patient stratification and biomarker identification cannot be overstated for these emerging ADCs, as these factors are crucial to identify patients who are most likely to derive benefit. As we continue to deepen our understanding of tumour biology and refine ADC design, we will edge closer to developing truly effective and safe ADCs for patients with treatment-refractory cancers. In this Review, we highlight advances in each ADC component (the monoclonal antibody, payload, linker and conjugation chemistry) and provide more-detailed discussions on selected examples of emerging novel ADCs of each format, enabled by engineering of one or more of these components.Antibody–drug conjugates (ADCs) are effective cancer drugs that have been approved for more than 20 specific indications. Nonetheless, acquired resistance and adverse events both limit the effectiveness of these agents. In this Review, the authors describe the development of novel ADC designs, including bispecific ADCs, probody–drug conjugates, immune-stimulating ADCs, protein-degrader ADCs and dual-drug ADCs. all of which have the potential to address these challenges and provide more effective ADCs.

Dysregulated RNA splicing is a molecular feature that characterizes almost all tumour types. Cancer-associated splicing alterations arise from both recurrent mutations and altered expression of trans-acting factors governing splicing catalysis and regulation. Cancer-associated splicing dysregulation can promote tumorigenesis via diverse mechanisms, contributing to increased cell proliferation, decreased apoptosis, enhanced migration and metastatic potential, resistance to chemotherapy and evasion of immune surveillance. Recent studies have identified specific cancer-associated isoforms that play critical roles in cancer cell transformation and growth and demonstrated the therapeutic benefits of correcting or otherwise antagonizing such cancer-associated mRNA isoforms. Clinical-grade small molecules that modulate or inhibit RNA splicing have similarly been developed as promising anticancer therapeutics. Here, we review splicing alterations characteristic of cancer cell transcriptomes, dysregulated splicing’s contributions to tumour initiation and progression, and existing and emerging approaches for targeting splicing for cancer therapy. Finally, we discuss the outstanding questions and challenges that must be addressed to translate these findings into the clinic.This Review discusses the diverse ways in which cancer-associated RNA splicing dysregulation promotes tumour initiation and progression, existing and emerging approaches for targeting splicing for cancer therapy and outstanding questions and challenges in the field.

Cyclin-dependent kinase 4 (CDK4) and CDK6 are critical mediators of cellular transition into S phase and are important for the initiation, growth and survival of many cancer types. Pharmacological inhibitors of CDK4/6 have rapidly become a new standard of care for patients with advanced hormone receptor-positive breast cancer. As expected, CDK4/6 inhibitors arrest sensitive tumour cells in the G1 phase of the cell cycle. However, the effects of CDK4/6 inhibition are far more wide-reaching. New insights into their mechanisms of action have triggered identification of new therapeutic opportunities, including the development of novel combination regimens, expanded application to a broader range of cancers and use as supportive care to ameliorate the toxic effects of other therapies. Exploring these new opportunities in the clinic is an urgent priority, which in many cases has not been adequately addressed. Here, we provide a framework for conceptualizing the activity of CDK4/6 inhibitors in cancer and explain how this framework might shape the future clinical development of these agents. We also discuss the biological underpinnings of CDK4/6 inhibitor resistance, an increasingly common challenge in clinical oncology.Dysregulation of cyclin-dependent kinase 4 (CDK4) and CDK6, regulators of the cell cycle, favours the growth and survival of several cancer types. Owing to this, CDK4 and CDK6 inhibitors were developed and are currently approved for the treatment of advanced hormone receptor-positive breast cancer. This Review describes how we are only now beginning to fully understand their mechanisms of action and provides a new framework for conceptualizing their activity, which might enable expansion of the clinical opportunities of these agents.

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.This Review discusses mechanisms by which tumour ecosystems adapt to therapeutic stresses and how these could be exploited, as well as challenges associated with tumour heterogeneity. It provides an integrative framework to identify and target vulnerabilities that arise from adaptive responses to overcome cancer therapy resistance.

The mechanisms of action of and resistance to trastuzumab deruxtecan (T-DXd), an anti-HER2–drug conjugate for breast cancer treatment, remain unclear. The phase 2 DAISY trial evaluated the efficacy of T-DXd in patients with HER2-overexpressing ( n  = 72, cohort 1), HER2-low ( n  = 74, cohort 2) and HER2 non-expressing ( n  = 40, cohort 3) metastatic breast cancer. In the full analysis set population ( n  = 177), the confirmed objective response rate (primary endpoint) was 70.6% (95% confidence interval (CI) 58.3–81) in cohort 1, 37.5% (95% CI 26.4–49.7) in cohort 2 and 29.7% (95% CI 15.9–47) in cohort 3. The primary endpoint was met in cohorts 1 and 2. Secondary endpoints included safety. No new safety signals were observed. During treatment, HER2-expressing tumors ( n  = 4) presented strong T-DXd staining. Conversely, HER2 immunohistochemistry 0 samples ( n  = 3) presented no or very few T-DXd staining (Pearson correlation coefficient r  = 0.75, P  = 0.053). Among patients with HER2 immunohistochemistry 0 metastatic breast cancer, 5 of 14 (35.7%, 95% CI 12.8–64.9) with ERBB2 expression below the median presented a confirmed objective response as compared to 3 of 10 (30%, 95% CI 6.7–65.2) with ERBB2 expression above the median. Although HER2 expression is a determinant of T-DXd efficacy, our study suggests that additional mechanisms may also be involved. (ClinicalTrials.gov identifier NCT04132960 .) Trastuzumab deruxtecan, an anti-HER2–drug conjugate, exhibits the highest objective response rate in patients with HER2-overexpressing metastatic breast cancer, but clinical activity is also observed in patients with HER2-low or non-expressing tumors, potentially pointing to additional determinants of drug efficacy.

Systemic chemotherapy remains the backbone of many cancer treatments. Due to its untargeted nature and the severe side effects it can cause, numerous nanomedicine approaches have been developed to overcome these issues. However, targeted delivery of therapeutics remains challenging. Engineering microrobots is increasingly receiving attention in this regard. Their functionalities, particularly their motility, allow microrobots to penetrate tissues and reach cancers more efficiently. Here, we highlight how different microrobots, ranging from tailor-made motile bacteria and tiny bubble-propelled microengines to hybrid spermbots, can be engineered to integrate sophisticated features optimised for precision-targeting of a wide range of cancers. Towards this, we highlight the importance of integrating clinicians, the public and cancer patients early on in the development of these novel technologies. Microbot delivery devices are the latest development in attempts to overcome the systemic toxicity associated with classical chemotherapy. Here, the authors review the recent progress in the field with a focus on the clinical translation and potential of the research and give a future perspective on this topic.

Recent progress in targeting KRAS G12C has provided both insight and inspiration for targeting alternative KRAS mutants. In this study, we evaluated the mechanism of action and anti-tumor efficacy of MRTX1133, a potent, selective and non-covalent KRAS G12D inhibitor. MRTX1133 demonstrated a high-affinity interaction with GDP-loaded KRAS G12D with K D and IC 50 values of ~0.2 pM and <2 nM, respectively, and ~700-fold selectivity for binding to KRAS G12D as compared to KRAS WT . MRTX1133 also demonstrated potent inhibition of activated KRAS G12D based on biochemical and co-crystal structural analyses. MRTX1133 inhibited ERK1/2 phosphorylation and cell viability in KRAS G12D -mutant cell lines, with median IC 50 values of ~5 nM, and demonstrated >1,000-fold selectivity compared to KRAS WT cell lines. MRTX1133 exhibited dose-dependent inhibition of KRAS-mediated signal transduction and marked tumor regression (≥30%) in a subset of KRAS G12D -mutant cell-line-derived and patient-derived xenograft models, including eight of 11 (73%) pancreatic ductal adenocarcinoma (PDAC) models. Pharmacological and CRISPR-based screens demonstrated that co-targeting KRAS G12D with putative feedback or bypass pathways, including EGFR or PI3Kα, led to enhanced anti-tumor activity. Together, these data indicate the feasibility of selectively targeting KRAS mutants with non-covalent, high-affinity small molecules and illustrate the therapeutic susceptibility and broad dependence of KRAS G12D mutation-positive tumors on mutant KRAS for tumor cell growth and survival. A potent and selective inhibitor of KRAS G12D , the most common mutant form of the KRAS oncoprotein, has anti-tumor efficacy in multiple pre-clinical cancer models, opening the possibility to therapeutically target this highly prevalent oncogenic driver.

The human proteome contains approximately 20,000 proteins, and it is estimated that more than 600 of them are functionally important for various types of cancers, including nearly 400 non-enzyme proteins that are challenging to target by traditional occupancy-driven pharmacology. Recent advances in the development of small-molecule degraders, including molecular glues and heterobifunctional degraders such as proteolysis-targeting chimeras (PROTACs), have made it possible to target many proteins that were previously considered undruggable. In particular, PROTACs form a ternary complex with a hijacked E3 ubiquitin ligase and a target protein, leading to polyubiquitination and degradation of the target protein. The broad applicability of this approach is facilitated by the flexibility of individual E3 ligases to recognize different substrates. The vast majority of the approximately 600 human E3 ligases have not been explored, thus presenting enormous opportunities to develop degraders that target oncoproteins with tissue, tumour and subcellular selectivity. In this Review, we first discuss the molecular basis of targeted protein degradation. We then offer a comprehensive account of the most promising degraders in development as cancer therapies to date. Lastly, we provide an overview of opportunities and challenges in this exciting field.The development of small-molecule degraders such as proteolysis-targeting chimeras (PROTACs) has made it possible to target oncoproteins previously considered undruggable. This Review discusses recent advances in the field, with a focus on opportunities and challenges for future development.

Clinical workflows in oncology rely on predictive and prognostic molecular biomarkers. However, the growing number of these complex biomarkers tends to increase the cost and time for decision-making in routine daily oncology practice; furthermore, biomarkers often require tumour tissue on top of routine diagnostic material. Nevertheless, routinely available tumour tissue contains an abundance of clinically relevant information that is currently not fully exploited. Advances in deep learning (DL), an artificial intelligence (AI) technology, have enabled the extraction of previously hidden information directly from routine histology images of cancer, providing potentially clinically useful information. Here, we outline emerging concepts of how DL can extract biomarkers directly from histology images and summarise studies of basic and advanced image analysis for cancer histology. Basic image analysis tasks include detection, grading and subtyping of tumour tissue in histology images; they are aimed at automating pathology workflows and consequently do not immediately translate into clinical decisions. Exceeding such basic approaches, DL has also been used for advanced image analysis tasks, which have the potential of directly affecting clinical decision-making processes. These advanced approaches include inference of molecular features, prediction of survival and end-to-end prediction of therapy response. Predictions made by such DL systems could simplify and enrich clinical decision-making, but require rigorous external validation in clinical settings.

Multidrug resistance (MDR) is the dominant challenge in the failure of chemotherapy in cancers. Phosphatidylinositol 3-kinase (PI3K) is a lipid kinase that spreads intracellular signal cascades and regulates a variety of cellular processes. PI3Ks are considered significant causes of chemoresistance in cancer therapy. Protein kinase B (AKT) is also a significant downstream effecter of PI3K signaling, and it modulates several pathways, including inhibition of apoptosis, stimulation of cell growth, and modulation of cellular metabolism. This review highlights the aberrant activation of PI3K/AKT as a key link that modulates MDR. We summarize the regulation of numerous major targets correlated with the PI3K/AKT pathway, which is further related to MDR, including the expression of apoptosis-related protein, ABC transport and glycogen synthase kinase-3 beta (GSK-3β), synergism with nuclear factor kappa beta (NF-κB) and mammalian target of rapamycin (mTOR), and the regulation of glycolysis.