Identification Of Predictive Biomarkers Research Articles

DARPP-32 and t-DARPP in the development of resistance to anti-HER2 agents. Pre-clinical evidence from the STEP study

The therapeutic scenario of Human Epidermal Growth Factor Receptor 2 positive advanced breast cancer (ABC) has been recently enriched by a number of innovative agents, which are reshaping treatment sequence. While randomized trials have documented an advantage in terms of efficacy, for the newly available agents we lack effectiveness and tolerability evidence from the real-world setting. Similarly, the identification of predictive biomarkers might improve clinical decision. We herein describe the outline of a prospective/retrospective study which aims to explore the optimal sequence of treatment in HER2+, pertuzumab pre-treated ABC patients treated in II line with anti-HER2 agents in clinical practice. As part of the pre-clinical tasks envisioned by the STEP study, in vitro cell models of resistance were exploited to investigate molecular features associated with reduced efficacy of HER2 targeting agents at the transcript level. The aggressive behavior of resistant cell populations was measured by growth assessment in mouse models. This approach led to the identification of DARPP-32 and t-DARPP proteins as possible predictive biomarkers of efficacy of anti-HER2 agents. Biomarkers validation and the clinical goals will be reached through patients’ inclusion into two independent cohorts, i.e., the prospective and retrospective cohorts, whose setup is currently ongoing.

Exploring the Interplay Between Vitamin B12-related Biomarkers, DNA Methylation, and Gene-Nutrition Interaction in Esophageal Precancerous Lesions

Vitamin B12 depletion has been suggested to be associated with esophageal precancerous lesions (EPL). However, the potential mechanisms remain unclear. This study aims to evaluate the role of vitamin B12 and its regulated epigenetic modification in EPL and provide preliminary information on the identification of potential molecular biomarkers for the early prediction of EPL. We collected information and samples from the Early Diagnosis and Early Treatment Project of Esophageal Cancer database from 200 EPL cases and 200 matched controls. Vitamin B12, one-carbon metabolism biomarkers, genetic polymorphism of TCN2 C776G, and DNA methylation were compared. Preliminarily identified candidate promoters of differentially methylated CpG positions were further verified by targeted bisulfite sequencing. EPL cases had significantly lower serum levels of vitamin B12 and transcobalamin II, and higher serum levels of homocysteine and 5-methyltetrahydrofolate than controls. The TCN2 C776G polymorphism was found to be associated with susceptibility to EPL and may interact with vitamin B12 nutritional status to influence the risk of EPL in male subjects. In addition, global hypomethylation related to vitamin B12 depletion was observed in EPL cases, along with region-specific hypermethylation of UGT2B15 and FGFR2 promoters. This study suggests that vitamin B12 depletion may be associated with aberrant DNA methylation and increased risk of EPL through the one-carbon metabolism pathway, presents that the TCN2 C776G polymorphism may interact with vitamin B12 nutritional status to affect EPL risk in males, and also identifies specific locations in the UGT2B15 and FGFR2 promoters with potential as promising molecular biomarkers.

Biomarkers for immunotherapy of hepatocellular carcinoma.

Immune-checkpoint inhibitors (ICIs) are now widely used for the treatment of patients with advanced-stage hepatocellular carcinoma (HCC). Two different ICI-containing regimens, atezolizumab plus bevacizumab and tremelimumab plus durvalumab, are now approved standard-of-care first-line therapies in this setting. However, and despite substantial improvements in survival outcomes relative to sorafenib, most patients with advanced-stage HCC do not derive durable benefit from these regimens. Advances in genome sequencing including the use of single-cell RNA sequencing (both of tumour material and blood samples), as well as immune cell identification strategies and other techniques such as radiomics and analysis of the microbiota, have created considerable potential for the identification of novel predictive biomarkers enabling the accurate selection of patients who are most likely to derive benefit from ICIs. In this Review, we summarize data on the immunology of HCC and the outcomes in patients receiving ICIs for the treatment of this disease. We then provide an overview of current biomarker use and developments in the past 5 years, including gene signatures, circulating tumour cells, high-dimensional flow cytometry, single-cell RNA sequencing as well as approaches involving the microbiome, radiomics and clinical markers. Novel concepts for further biomarker development in HCC are then discussed including biomarker-driven trials, spatial transcriptomics and integrated 'big data' analysis approaches. These concepts all have the potential to better identify patients who are most likely to benefit from ICIs and to promote the development of new treatment approaches.

Identification of novel first-trimester serum biomarkers for early prediction of preeclampsia

BackgroundPreeclampsia (PE) is a leading cause of maternal and perinatal mortality and morbidity worldwide, but effective early prediction remains a challenge due to the lack of reliable biomarkers.MethodsBased on the extensive human biobank of our large-scale assisted reproductive cohort platform, the first-trimester serum levels of 48 cytokines, total immunoglobulins (Igs), anti-phosphatidylserine (aPS) antibodies, and several previously reported PE biomarkers [including placental growth factor (PlGF), soluble fms-like tyrosine kinase-1 (sFlt-1), and activin A] were measured in 34 women diagnosed with PE and 34 matched normotensive controls.ResultsThe PE group has significantly higher first-trimester serum levels of interleukin (IL)-2Rα, IL-9, tumor necrosis factor-β (TNF-β), RANTES, hepatocyte growth factor (HGF), total IgM, and total IgG, and aPS IgG optical density (OD) value, as well as lower first-trimester serum levels of PlGF and total IgA and aPS-IgG immune complexes (IC) OD value than the control group. Combining top five first-trimester serum biomarkers (total IgM, total IgG, PlGF, aPS IgG, and total IgA) achieved superior predictive value [area under the curve (AUC) and 95% confidence interval (CI) 0.983 (0.952–1.000), with a sensitivity of 100% and a specificity of 94.1%] for PE development compared to PlGF and PlGF/sFlt-1 independently [AUC and 95% CI 0.825 (0.726–0.924) and 0.670 (0.539–0.800), respectively].ConclusionWe identified novel first-trimester serum biomarkers and developed an effective first-trimester prediction model using immune-related factors and PlGF for PE, which could facilitate the development of early diagnostic strategies and provide immunological insight into the further mechanistic exploration of PE.

CANLI DONÖR KARACİĞER NAKLİNİN ÖNGÖRÜSEL BİYOBELİRTEÇLERİ

Objective: Liver transplantation using a living donor (LDLT) is currently the most popular method used in the worldwide. Appropriate biomarkers that predict graft status should be used to detect early post-transplant complications that may lead to a rejection reaction. Material and Method: The study involved a total of 44 liver recipients and 44 liver donors, from whom preoperative blood samples were taken and immunoassay and spectrophotometric studies were carried out. The levels of serum neopterin, interferon-gamma (IFN- y), indoleamine-2,3 dioxygenase (IDO), and -glutathione S transferase (a-GST) were assessed using an enzyme-linked immunosorbent test. The activity of glutathione reductase (GR) and glucose-6-phosphate dehydrogenase (G6PD) in erythrocytes was measured using spectrophotometry. Result and Discussion: “Neopterin, IDO, and G6PD levels were significantly higher in the recipient group than in the donor group. The differences in gender and blood groups were statistically insignificant. The rejection reaction developed in 25% of patients and none survived. These findings may facilitate the identification of novel predictive biomarkers for the diagnosis of acute rejection reactions after LDLT. The clinical use of novel non-invasive biomarkers may provide time and cost advantages.

Statistical models of complex brain networks: a maximum entropy approach.

The brain is a highly complex system. Most of such complexity stems from the intermingled connections between its parts, which give rise to rich dynamics and to the emergence of high-level cognitive functions. Disentangling the underlying network structure is crucial to understand the brain functioning under both healthy and pathological conditions. Yet, analyzing brain networks is challenging, in part because their structure represents only one possible realization of a generative stochastic process which is in general unknown. Having a formal way to cope with such intrinsic variability is therefore central for the characterization of brain network properties. Addressing this issue entails the development of appropriate tools mostly adapted from network science and statistics. Here, we focus on a particular class of maximum entropy models for networks, i.e. exponential random graph models, as a parsimonious approach to identify the local connection mechanisms behind observed global network structure. Efforts are reviewed on the quest for basic organizational properties of human brain networks, as well as on the identification of predictive biomarkers of neurological diseases such as stroke. We conclude with a discussion on how emerging results and tools from statistical graph modeling, associated with forthcoming improvements in experimental data acquisition, could lead to a finer probabilistic description of complex systems in network neuroscience.

Lacking Immunotherapy Biomarkers for Biliary Tract Cancer: A Comprehensive Systematic Literature Review and Meta-Analysis.

Immunotherapy has recently been incorporated into the spectrum of biliary tract cancer (BTC) treatment. The identification of predictive response biomarkers is essential in order to identify those patients who may benefit most from this novel treatment option. Here, we propose a systematic literature review and a meta-analysis of PD-1, PD-L1, and other immune-related biomarker expression levels in patients with BTC. Prisma guidelines were followed for this systematic review and meta-analysis. Eligible studies were searched on PubMed. Studies published between 2017 and 2022, reporting data on PD-1/PD-L1 expression and other immune-related biomarkers in patients with BTC, were considered eligible. A total of 61 eligible studies were identified. Despite the great heterogeneity between 39 studies reporting data on PD-L1 expression, we found a mean PD-L1 expression percentage (by choosing the lowest cut-off per study) of 25.6% (95% CI 21.0 to 30.3) in BTCs. The mean expression percentages of PD-L1 were 27.3%, 21.3%, and 27.4% in intrahepatic cholangiocarcinomas (iCCAs-15 studies), perihilar-distal CCAs (p/dCCAs-7 studies), and gallbladder cancer (GBC-5 studies), respectively. Furthermore, 4.6% (95% CI 2.38 to 6.97) and 2.5% (95% CI 1.75 to 3.34) of BTCs could be classified as TMB-H and MSI/MMRd tumors, respectively. From our analysis, PD-L1 expression was found to occur approximately in 26% of BTC patients, with minimal differences based on anatomical location. TMB-H and MSI molecular phenotypes occurred less frequently. We still lack a reliable biomarker, especially in patients with mismatch-proficient tumors, and we must need to make an effort to conceive new prospective biomarker discovery studies.

Kinase Inhibitor Pulldown Assay Identifies a Chemotherapy Response Signature in Triple-negative Breast Cancer Based on Purine-binding Proteins.

The identification of pretreatment predictive biomarkers for pCR in response to neoadjuvant chemotherapy would advance precision treatment for TNBC. To complement standard proteogenomic discovery profiling, a KIPA was deployed and unexpectedly identified a seven-member non-kinase PBP pCR-associated signature. Individual members served diverse pathways including IFN gamma response, nuclear import of DNA repair proteins, and cell death.

Utility of circulating tumour DNA for prognosis and prediction of therapeutic effect in locally recurrent rectal cancer: study protocol for a multi-institutional, prospective observational study (JCOG1801A1, CAP-LR study)

IntroductionIn locally recurrent rectal cancer (LRRC), surgery is a standard treatment for resectable disease. However, short-term and long-term outcomes are unsatisfactory due to the invasive nature of surgical procedures and...

Impact of Colorectal Cancer Sidedness and Location on Therapy and Clinical Outcomes: Role of Blood-Based Biopsy for Personalized Treatment.

Colorectal cancer is one of the most common malignant diseases in the United States and worldwide, and it remains among the top three causes of cancer-related death. A new understanding of molecular characteristics has changed the profile of colorectal cancer and its treatment. Even controlling for known mutational differences, tumor side of origin has emerged as an independent prognostic factor, and one that impacts response to therapy. Left- and right-sided colon cancers differ in a number of key ways, including histology, mutational profile, carcinogenesis pathways, and microbiomes. Moreover, the frequency of certain molecular features gradually changes from the ascending colon to rectum. These, as well as features yet to be identified, are likely responsible for the ongoing role of tumor sidedness and colorectal subsites in treatment response and prognosis. Along with tumor molecular profiling, blood-based biopsy enables the identification of targetable mutations and predictive biomarkers of treatment response. With the application of known tumor characteristics including sidedness and subsites as well as the utilization of blood-based biopsy, along with the development of biomarkers and targeted therapies, the field of colorectal cancer continues to evolve towards the personalized management of a heterogeneous cancer.

Clinician's guide to targeted estrogen receptor degradation using PROTAC in patients with estrogen receptor-positive metastatic breast cancer.

Metastatic breast cancer (MBC) remains a major clinical challenge, necessitating the development of innovative therapeutic strategies. Estrogen receptor (ER) degradation using proteolysis-targeting chimeras (PROTAC) has emerged as a promising approach for overcoming acquired resistance to endocrine therapy. This review will summarize recent findings, highlighting the role of ER degradation by PROTAC in patients with MBC. The application of PROTAC technology for ER degradation has demonstrated initial success in preclinical and early clinical studies. PROTACs, consisting of an ER-targeting moiety, an E3 ubiquitin ligase-recruiting moiety, and a linker, facilitate ER ubiquitination and subsequent proteasomal degradation. Yet, significant challenges persist in the clinical translation of ER degradation by PROTAC. These include the optimization of PROTAC design, elucidation of mechanisms underlying resistance to PROTAC-induced ER degradation, and identification of predictive biomarkers for patient stratification. Additionally, addressing potential off-target effects and toxicity profiles remains a critical aspect of developing PROTAC-based therapies. Recent data demonstrate the potential of ER degradation by PROTAC as a therapeutic strategy for patients with MBC. Continued research efforts and development of synergistic combinations are crucial for further advancing PROTAC-based therapies and improving outcomes in patients with MBC.

Identification of Potential Predictive and Diagnostic Urinary Biomarkers for Acute Rejection in Renal Transplant Recipients: A Proteomics Study

Acute rejection (AR) is one of the main predictors of long-term survival of allograft. The development of noninvasive diagnostic biomarkers of AR is an unmet need for the timely detection. This study aimed to identify novel detective biomarkers of AR by analyzing the urine proteome profile of transplant patients. Forty-two transplant patients including 30 biopsy-proven AR patients (including antibody and T-cell mediated rejection) and 12 transplant patients with stable renal function (control group) were enrolled. Label-free quantification (LFQ) proteomics technique was performed on urine samples. Multivariate statistical analysis was applied for biomarker identification. The ELISA method validated EGF (epidermal growth factor) from the top 10 candidate biomarkers in an independent cohort. Gene ontology and possible pathways were also analyzed. LFQ analysis revealed 453 identified proteins differentially expressed between groups that mainly participated in complement and coagulation pathways and proteolysis. Ten proteins with the highest AUCs (Area under the ROC Curve) were identified as candidate diagnostic biomarkers. Candidate biomarkers were mainly associated with extracellular matrix (ECM) degradation and epithelial-to-mesenchymal transition (EMT). Reduction of urinary EGF measured by ELISA in an independent group confirmed proteomics results. We introduced a unique set of diagnostic urinary biomarkers for AR. Interactions of biomarkers and validation of EGF among biomarker panels revealed that ECM remodeling and EMT might be the consequence of immunological processes in AR. If validated as a panel, the mentioned biomarkers might shed light on the pathogenesis of chronic injury after AR and point out the potential treatment strategies.

New approaches in childhood asthma treatment.

This review aims to summarize the most recent advances in asthma management, focusing on novel approaches to pediatric asthma. In recent years, the therapeutic tools for pediatric asthma have expanded significantly for both the nonsevere and severe forms. The use of anti-inflammatory treatment, even for the mildest cases, and the withdrawal of symptomatic bronchodilation as monotherapy have been included in the most recent guidelines. Also, different biological therapies have revolutionized the therapeutical approach for severe uncontrolled asthma in children and adolescents. With the expanding landscape of novel therapeutic approaches for pediatric asthma, further evidence is needed to help clinicians choose the best option for patients, particularly those with severe asthma. The identification of novel predictive biomarkers may also help pediatricians in selecting children and adolescents for innovative therapies.

A Prospective Analysis of the Retinopathy of Prematurity Correlated with the Inflammatory Status of the Extremely Premature and Very Premature Neonates.

Retinopathy of Prematurity (ROP) is a major cause of blindness in premature infants. This study aimed to evaluate the association between inflammatory markers and ROP development in extremely premature and very premature neonates and identify potential inflammatory biomarkers for ROP risk prediction. This prospective study was conducted from January 2021 to January 2023 in two clinical hospitals associated with the "Victor Babes" University of Medicine and Pharmacy Timisoara. The study population comprised neonates with a gestational age of less than 32 weeks. Various inflammatory markers, including total white blood cell count, polymorphonuclear leukocytes, C-reactive protein, interleukin-6, and lactate dehydrogenase, were analyzed from blood samples collected at birth and three days postnatally. ROP was diagnosed and classified following the International Classification of Retinopathy of Prematurity. The study included 48 neonates, 12 Extremely Premature Infants (EPI), and 36 Very Premature Infants (VPI). The EPI group had significantly higher mean interleukin-6 and lactate dehydrogenase levels at birth and three days postnatally than the VPI group. C-reactive protein levels at three days were significantly higher in the VPI group. Umbilical cord inflammation and ROP severity were found to have a statistically significant positive correlation. Half of the EPIs had moderate to severe ROP, significantly more than in the VPI group. The duration of oxygen supplementation, mechanical ventilation, Continuous Positive Airway Pressure (CPAP), gestational age less than 28 weeks, and umbilical cord inflammation at or above stage 3 were significant risk factors for developing ROP stage 2 or above. Elevated CRP and IL-6 were also significantly associated with an increased risk of developing ROP stage 2 or above, highlighting their potential as biomarkers for ROP risk prediction. This study suggests a significant association between inflammatory markers and ROP development in extremely premature and very premature neonates. These findings could contribute to the identification of potential inflammatory biomarkers for ROP risk prediction, improving early diagnosis and intervention strategies for this condition.

A physiologically relevant culture platform for long-term studies of in vitro gingival tissue

There is a clinical need to understand the etiologies of periodontitis, considering the growing socio-economic impact of the disease. Despite recent advances in oral tissue engineering, experimental approaches have failed to develop a physiologically relevant gingival model that combines tissue organization with salivary flow dynamics and stimulation of the shedding and non-shedding oral surfaces. Herein, we develop a dynamic gingival tissue model composed of a silk scaffold, replicating the cyto-architecture and oxygen profile of the human gingiva, along with a saliva-mimicking medium that reflected the ionic composition, viscosity, and non-Newtonian behavior of human saliva. The construct was cultured in a custom designed bioreactor, in which force profiles on the gingival epithelium were modulated through analysis of inlet position, velocity and vorticity to replicate the physiological shear stress of salivary flow. The gingival bioreactor supported the long-term in vivo features of the gingiva and improved the integrity of the epithelial barrier, critical against the invasion of pathogenic bacteria. Furthermore, the challenge of the gingival tissue with P. gingivalis lipopolysaccharide, as an in vitro surrogate for microbial interactions, indicated a greater stability of the dynamic model in maintaining tissue homeostasis and, thus, its applicability in long-term studies. The model will be integrated into future studies with the human subgingival microbiome to investigate host-pathogen and host-commensal interactions. Statement of significanceThe major societal impact of human microbiome had reverberated up to the establishment of the Common Fund's Human Microbiome Project, that has the intent of studying the role of microbial communities in human health and diseases, including periodontitis, atopic dermatitis, or asthma and inflammatory bowel disease. In addition, these chronic diseases are emergent drivers of global socioeconomic status. Not only common oral diseases have been shown to be directly correlated with several systemic conditions, but they are differentially impacting some racial/ethnic and socioeconomic groups. To address this growing social disparity, the development of in vitro gingival model would provide a time and cost-effective experimental platform, able to mimic the spectrum of periodontal disease presentation, for the identification of predictive biomarkers for early-stage diagnosis.

Nomogram for predicting survival in patients with advanced hepatocellular carcinoma treated with PD-1 inhibitors: incorporating pre-treatment and post-treatment clinical parameters

BackgroundImmunotherapy has transformed cancer treatment patterns for advanced hepatocellular carcinoma (aHCC) in recent years. Therefore, the identification of predictive biomarkers has important clinical implications.MethodsWe collected medical records from 117 aHCC patients treated with anti-PD-1 antibody. Kaplan-Meier analysis and Cox proportional hazard regression were used to evaluate the association between peripheral blood biomarkers and overall survival (OS) and progression-free survival (PFS). Finally, the prognostic nomogram was constructed.ResultsThe mPFS and mOS were 7.0 months and 18.7 months, respectively. According to Kaplan-Meier analysis and Cox regression analysis, we regarded the treatment regimen (p = 0.020), hemoglobin (Hb) at 6-week (p = 0.042), neutrophil-to-lymphocyte ratio (NLR) at 6-week (p < 0.001), system immune inflammation index (SII) at 6-week (p = 0.125) as predictors of PFS, and alpha fetoprotein (AFP) (p = 0.035), platelet-to-lymphocyte ratio (PLR) (p = 0.012), Hb at 6-week (p = 0.010) and NLR at 6-week (p = 0.020) as predictors of OS. Furthermore, the results suggest that the OS and PFS nomogram model were in agreement with actual observations.ConclusionBiomarkers in peripheral blood can predict the prognosis of patients with aHCC treated with anti-PD-1 antibody. The development of nomogram models can help us to screen potential patients who can benefit from immunotherapy.

Chasing Immune Checkpoint Inhibitors in Ovarian Cancer: Novel Combinations and Biomarker Discovery.

A deep understanding of the tumor microenvironment and the recognition of tumor-infiltrating lymphocytes as a prognostic factor have resulted in major milestones in immunotherapy that have led to therapeutic advances in treating many cancers. Yet, the translation of this knowledge to clinical success for ovarian cancer remains a challenge. The efficacy of immune checkpoint inhibitors as single agents or combined with chemotherapy has been unsatisfactory, leading to the exploration of alternative combination strategies with targeted agents (e.g., poly-ADP-ribose inhibitors (PARP)and angiogenesis inhibitors) and novel immunotherapy approaches. Among the different histological subtypes, clear cell ovarian cancer has shown a higher sensitivity to immunotherapy. A deeper understanding of the mechanism of immune resistance within the context of ovarian cancer and the identification of predictive biomarkers remain central discovery benchmarks to be realized. This will be critical to successfully define the precision use of immune checkpoint inhibitors for the treatment of ovarian cancer.

Targeting growth hormone in cancer: future perspectives.

Decades of published research supports a role for growth hormone (GH) in cancer. Accordingly, there is increasing interest in targeting GH in oncology, with GH antagonists exhibiting efficacy in xenograft studies as single agents and in combination with anticancer therapy or radiation. Here we discuss challenges associated with using growth hormone receptor (GHR) antagonists in preclinical models and considerations for translation, such as the identification of predictive biomarkers for selecting patients and for monitoring drug efficacy. Ongoing research will determine whether suppressing GH signalling pharmacologically will also reduce the risk of developing cancer. An increase in GH-targeted drugs in preclinical development will ultimately provide researchers with new tools to test anti-cancer efficacy of blocking the GH signalling pathway in preclinical models.

Identification of predictive biomarkers for diagnosis and radiation sensitivity of uterine cervical cancer using wide-targeted metabolomics.

Uterine cervical cancer (UCC) is the fourth most common cancer in women, responsible for more than 300 000 deaths worldwide. Its early detection, by cervical cytology, and prevention, by vaccinating against human papilloma virus, greatly contribute to reducing cervical cancer mortality in women. However, penetration of the effective prevention of UCC in Japan remains low. Plasma metabolome analysis is widely used for biomarker discovery and the identification of cancer-specific metabolic pathways. Here, we aimed to identify predictive biomarkers for the diagnosis and radiation sensitivity of UCC using wide-targeted plasma metabolomics. We analyzed 628 metabolites in plasma samples obtained from 45 patients with UCC using ultra-high-performance liquid chromatography with tandem mass spectrometry. The levels of 47 metabolites were significantly increased and those of 75 metabolites were significantly decreased in patients with UCC relative to healthy controls. Increased levels of arginine and ceramides, and decreased levels of tryptophan, ornithine, glycosylceramides, lysophosphatidylcholine, and phosphatidylcholine were characteristic of patients with UCC. Comparison of metabolite profiles in groups susceptible and non-susceptible to radiation therapy, a treatment for UCC, revealed marked variations in polyunsaturated fatty acid, nucleic acid, and arginine metabolism in the group not susceptible to treatment. Our findings suggest that the metabolite profile of patients with UCC may be an important indicator for distinguishing these patients from healthy cohorts, and may also be useful for predicting sensitivity to radiotherapy.

Optimizing the safety of antibody-drug conjugates for patients with solid tumours.

Over the past 5 years, improvements in the design of antibody-drug conjugates (ADCs) have enabled major advances that have reshaped the treatment of several advanced-stage solid tumours. Considering the intended rationale behind the design of ADCs, which is to achieve targeted delivery of cytotoxic molecules by linking them to antibodies targeting tumour-specific antigens, ADCs would be expected to be less toxic than conventional chemotherapy. However, most ADCs are still burdened by off-target toxicities that resemble those of the cytotoxic payload as well as on-target toxicities and other poorly understood and potentially life-threatening adverse effects. Given the rapid expansion in the clinical indications of ADCs, including use in curative settings and various combinations, extensive efforts are ongoing to improve their safety. Approaches currently being pursued include clinical trials optimizing the dose and treatment schedule, modifications of each ADC component, identification of predictive biomarkers for toxicities, and the development of innovative diagnostic tools. In this Review, we describe the determinants of the toxicities of ADCs in patients with solid tumours, highlighting key strategies that are expected to improve tolerability and enable improvements in the treatment outcomes of patients with advanced-stage and those with earlystage cancers in the years to come.