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Background: Antibody-drug conjugates have promising clinical activity in the treatment of solid tumours. BL-B01D1 is a first-in-class EGFR-HER3 bispecific antibody-drug conjugate. We aimed to assess the safety and preliminary antitumour activity of BL-B01D1 in patients with locally advanced or metastatic solid tumours., Methods: This first-in-human, open-label, multicentre, dose-escalation and dose-expansion phase 1 trial was conducted in seven hospitals in China, enrolling patients aged 18-75 years (dose escalation; phase 1a) or older than 18 years (dose expansion; phase 1b), with a life expectancy of at least 3 months, an Eastern Cooperative Oncology Group performance status of 0-1, and histologically or cytologically confirmed locally advanced or metastatic solid tumours that had progressed on current standard treatment. In the phase 1a i3+3 design, patients received intravenous BL-B01D1 at three different schedules: 0·27 mg/kg, 1·5 mg/kg, and 3·0 mg/kg weekly; 2·5 mg/kg, 3·0 mg/kg, and 3·5 mg/kg on days 1 and 8 of each cycle every 3 weeks; or 5·0 mg/kg and 6·0 mg/kg on day 1 of each cycle every 3 weeks. The primary objectives of phase 1a were to identify the safety, maximum tolerated dose, and dose-limiting toxicity. In phase 1b, patients were treated in two schedules: 2·5 and 3·0 mg/kg on days 1 and 8 every 3 weeks, or 4·5, 5·0, and 6·0 mg/kg on day 1 every 3 weeks. The primary objectives of phase 1b were to assess the safety and recommended phase 2 dose of BL-B01D1, and objective response rate was a key secondary endpoint. Safety was analysed in all patients with safety records who received at least one dose of BL-B01D1. Antitumour activity was assessed in the activity analysis set which included all patients who received at least one dose of BL-B01D1 every 3 weeks. This trial is registered with China Drug Trials, CTR20212923, and ClinicalTrials.gov, NCT05194982, and recruitment is ongoing., Findings: Between Dec 8, 2021, and March 13, 2023, 195 patients (133 [65%] men and 62 [32%] women; 25 in phase 1a and 170 in phase 1b) were consecutively enrolled, including 113 with non-small-cell lung cancer, 42 with nasopharyngeal carcinomas, 13 with small-cell lung cancer, 25 with head and neck squamous cell carcinoma, one with thymic squamous cell carcinoma, and one with submandibular lymphoepithelioma-like carcinoma. In phase 1a, four dose-limiting toxicities were observed (two at 3·0 mg/kg weekly and two at 3·5 mg/kg on days 1 and 8 every 3 weeks; all were febrile neutropenia), thus the maximum tolerated dose was reached at 3·0 mg/kg on days 1 and 8 every 3 weeks and 6·0 mg/kg on day 1 every 3 weeks. Grade 3 or worse treatment-related adverse events occurred in 139 (71%) of 195 patients; the most common of which were neutropenia (91 [47%]), anaemia (76 [39%]), leukopenia (76 [39%]), and thrombocytopenia (63 [32%]). 52 (27%) patients had a dose reduction and five (3%) patients discontinued treatment due to treatment-related adverse events. One patient was reported as having interstitial lung disease. Treatment-related deaths occurred in three (2%) patients (one due to pneumonia, one due to septic shock, and one due to myelosuppression). In 174 patients evaluated for activity, median follow-up was 6·9 months (IQR 4·5-8·9) and 60 (34%; 95% CI 27-42) patients had an objective response., Interpretation: Our results suggest that BL-B01D1 has preliminary antitumour activity in extensively and heavily treated advanced solid tumours with an acceptable safety profile. Based on the safety and antitumour activity data from both phase 1a and 1b, 2·5 mg/kg on days 1 and 8 every 3 weeks was selected as the recommended phase 2 dose in Chinese patients., Funding: Sichuan Baili Pharmaceutical., Translation: For the Chinese translation of the abstract see Supplementary Materials section., Competing Interests: Declaration of interests LZ reports receiving research support from Jiangsu Hengrui Pharmaceuticals, Eli Lilly and Company, Novartis, Roche, Chia Tai Tianqing Pharmaceutical Group, Junshi Pharmaceuticals, QiLu Pharmaceutical, Pfizer, and Bristol-Myers Squibb. YZhu, HZhu, and SX are employees of Sichuan Baili Pharmaceutical. All other authors declare no competing interests., (Copyright © 2024 Elsevier Ltd. All rights reserved, including those for text and data mining, AI training, and similar technologies.)

Microorganisms are commonly detected in tumor tissues, and the species and abundance have been reported to affect cancer initiation, progression, and therapy. Host genetics have been associated with gut microbial abundances, while the relationships between genetic variants and the cancer microbiome still require systematic interrogation. Therefore, identification of cancer microbiome quantitative trait loci (mbQTL) across cancer types might elucidate the contributions of genetic variants to tumor development. Using genotype data from The Cancer Genome Atlas and microbial abundance levels from Kraken-derived data, we developed a computational pipeline to identify mbQTLs in 32 cancer types. This study systematically identified 38,660 mbQTLs across cancers, ranging 50 in endometrial carcinoma to 3,133 in thyroid carcinoma. Furthermore, a strong enrichment of mbQTLs was observed among transcription factor binding sites and chromatin regulatory elements, such as H3K27ac. Notably, mbQTLs were significantly enriched in cancer genome-wide association studies (GWAS) loci and explained an average of 2% for cancer heritability, indicating that mbQTLs could provide additional insights into cancer etiology. Correspondingly, 24,443 mbQTLs overlapping with GWAS linkage disequilibrium regions were identified. Survival analyses identified 318 mbQTLs associated with patient overall survival. Moreover, we uncovered 135,248 microbiome-immune infiltration associations and 166,603 microbiome-drug response associations that might provide clues for microbiome-based biomarkers. Finally, a user-friendly database, Cancer-mbQTL (http://canmbqtl.whu.edu.cn/#/), was constructed for users to browse, search, and download data of interest. This study provides a valuable resource for investigating the roles of genetics and microorganisms in human cancer., Significance: This study provides insights into the host-microbiome interactions for multiple cancer types, which could help the research community understand the effects of inherited variants in tumorigenesis and development., (©2022 American Association for Cancer Research.)

Background: Cancer cachexia is a complex metabolic syndrome characterised by a loss of muscle with or without loss of fat mass, and is associated with high morbidity and mortality. Despite its clinical importance, there is a lack of simple tools to screen patients for cancer cachexia. The aim of this study was to evaluate and validate the patient-generated subjective global assessment (PG-SGA) as a screening tool for cancer cachexia., Methods: This is a secondary analysis of a multicentre, cross-sectional, observational study. Cancer cachexia was diagnosed when there was weight loss ≥5% during the past 12 months and at least three of the five following conditions were present: decreased muscle strength, fatigue, anorexia, low Fat-Free Mass Index (FFMI) and abnormal laboratory findings. A quadratic discriminant analysis was conducted for the ability of PG-SGA to predict cachexia., Results: A total of 4231 patients with cancer were included in this analysis, and 351 patients (8.3%) were diagnosed as having cachexia. The highest incidence of cachexia was found among patients with pancreatic cancer (32.5%), oesophageal cancer (21.5%) and gastric cancer (17.9%). Compared with patients without cachexia, patients with cachexia had a lower body mass index, FFMI, hand grip strength, total protein, prealbumin, albumin, haemoglobin and Karnofsky performance status (p<0.05), while they had a higher C reactive protein level and PG-SGA Score (4.71±3.71 vs 10.87±4.84, p<0.05). The best cut-off value for PG-SGA was 6.5, with 79.8% of sensitivity and 72.3% specificity for cachexia, and the area under the receiver operating characteristic curve was 0.846 (95% CI 0.826 to 0.866, p<0.001)., Conclusions: PG-SGA is a highly specific tool that can be used to screen patients for cancer cachexia., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2022. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Completing Patient-Generated Subjective Global Assessment (PG-SGA) questionnaires is time consuming. This study aimed to develop and validate an easy-to-use modified PG-SGA (mPG-SGA) for cancer patients., Methods: Seventy professionals assessed the content validity, comprehensibility, and difficulty of the full PG-SGA. A survey including the PG-SGA and other questionnaires was completed by 34 071 adult hospitalized cancer patients with first cancer diagnosis or recurrent disease with any tumour comorbidities from the INSCOC study. Among them, 1558 patients were followed for 5 years after admission. Reliability and rank correlation were estimated to assess the consistency between PG-SGA items and to select mPG-SGA items. The external and internal validity, test-retest reliability, and predictive validity were tested for the mPG-SGA via comparison with both the PG-SGA and abridged PG-SGA (abPG-SGA)., Results: After deleting items that more than 50% of professionals considered difficult to evaluate (Worksheet 4) and items with an item-total correlation <0.1, the mPG-SGA was constructed. Nutritional status was categorized using mPG-SGA scores as well-nourished (0 points) or mildly (1-2 points), moderately (3-6 points), or severely malnourished (≥7 points) based on the area under curve (0.962, 0.989, and 0.985) and maximal sensitivity (0.924, 0.918, and 0.945) and specificity (1.000, 1.000, and 0.938) of the cut-off scores. The external and internal validity and test-retest reliability were good. Significant median overall survival differences were found among nutritional status groups categorized by the mPG-SGA: 24, 18, 14, and 10 months for well-nourished, mildly malnourished, moderately malnourished, and severely malnourished, respectively (all Ps < 0.05). Neither the PG-SGA nor the abridged PG-SGA could discriminate the median overall survival differences between the well-nourished and mildly malnourished groups., Conclusions: We systematically developed and validated the mPG-SGA as an easier-to-use nutritional assessment tool for cancer patients. The mPG-SGA appears to have better predictive validity for survival than the PG-SGA and abridged PG-SGA., (© 2021 The Authors. Journal of Cachexia, Sarcopenia and Muscle published by John Wiley & Sons Ltd on behalf of Society on Sarcopenia, Cachexia and Wasting Disorders.)

Background: Increasing evidence indicates that nutritional status could influence the survival of cancer patients. This study aims to develop and validate a nomogram with nutrition-related parameters for predicting the overall survival of cancer patients., Patients and Methods: A total of 8749 patients from the multicentre cohort study in China were included as the primary cohort to develop the nomogram, and 696 of these patients were recruited as a validation cohort. Patients' nutritional status were assessed using the PG-SGA. LASSO regression models and Cox regression analysis were used for factor selection and nomogram development. The nomogram was then evaluated for its effectiveness in discrimination, calibration, and clinical usefulness by the C-index, calibration curves, and decision curve analysis. Kaplan-Meier survival curves were used to compare the survival rate., Results: Seven independent prognostic factors were identified and integrated into the nomogram. The C-index was 0.73 (95% CI, 0.72 to 0.74) and 0.77 (95% CI, 0.74 to 0.81) for the primary cohort and validation cohort, which were both higher than 0.59 (95% CI, 0.58 to 0.61) of the TNM staging system. DCA demonstrated that the nomogram was higher than the TNM staging system and the TNM staging system combined with PG-SGA. Significantly median overall survival differences were found by stratifying patients into different risk groups (score < 18.5 and ≥ 18.5) for each TNM category (all Ps < 0.001)., Conclusion: Our study screened out seven independent prognostic factors and successfully generated an easy-to-use nomogram, and validated and shown a better predictive validity for the overall survival of cancer patients., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Background: The newly proposed Global Leadership Initiative on Malnutrition (GLIM) framework is promising to gain global acceptance for diagnosing malnutrition. However, the role of machine learning in facilitating its application in clinical practice remains largely unknown., Methods: We performed a multicenter, observational cohort study including 3998 patients with cancer. Baseline malnutrition was defined using the GLIM criteria, and the study population was randomly divided into a derivation group (n = 2998) and a validation group (n = 1000). A classification and regression trees (CART) algorithm was used to develop a decision tree for classifying the severity of malnutrition in the derivation group. Model performance was evaluated in the validation group., Results: GLIM criteria diagnosed 588 patients (14.7%) with moderate malnutrition and 532 patients (13.3%) with severe malnutrition among the study population. The CART cross-validation identified 5 key predictors for the decision tree construction, including age, weight loss within 6 months, body mass index, calf circumference, and the Nutritional Risk Screening 2002 score. The decision tree showed high performance, with an area under the curve of 0.964 (κ = 0.898, P < .001, accuracy = 0.955) in the validation group. Subgroup analysis showed that the model had apparently good performance in different cancers. Among the 5 predictors constituting the tree, age contributed the least to the classification power., Conclusion: Using the machine learning, we visualized and validated a decision tool based on the GLIM criteria that can be conveniently used to accelerate the pretreatment identification of malnutrition in patients with cancer., (© 2021 American Society for Parenteral and Enteral Nutrition.)

yki-induced gut tumors in Drosophila are associated with host wasting, including muscle dysfunction, lipid loss, and hyperglycemia, a condition reminiscent of human cancer cachexia. We previously used this model to identify tumor-derived ligands that contribute to host wasting. To identify additional molecular networks involved in host-tumor interactions, we develop PathON, a web-based tool analyzing the major signaling pathways in Drosophila, and uncover the Upd3/Jak/Stat axis as an important modulator. We find that yki-gut tumors secrete Upd3 to promote self-overproliferation and enhance Jak/Stat signaling in host organs to cause wasting, including muscle dysfunction, lipid loss, and hyperglycemia. We further reveal that Upd3/Jak/Stat signaling in the host organs directly triggers the expression of ImpL2, an antagonistic binding protein for insulin-like peptides, to impair insulin signaling and energy balance. Altogether, our results demonstrate that yki-gut tumors produce a Jak/Stat pathway ligand, Upd3, that regulates both self-growth and host wasting., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Malnutrition is prevalent that can impair multiple clinical outcomes in oncology populations. This study aimed to develop and utilize a tool to optimize the early identification of malnutrition in patients with cancer., Methods: We performed an observational cohort study including 3998 patients with cancer at two teaching hospitals in China. Hierarchical clustering was performed to classify the patients into well-nourished or malnourished clusters based on 17 features reflecting the phenotypic and etiologic dimensions of malnutrition. Associations between the identified clusters and patient characteristics were analyzed. A nomogram for predicting the malnutrition probability was constructed and independent validation was performed to explore its clinical significance., Results: The cluster analysis identified a well-nourished cluster (n = 2736, 68.4%) and a malnourished cluster (n = 1262, 31.6%) in the study population, which showed significant agreement with the Patient-Generated Subjective Global Assessment and the Global Leadership Initiative on Malnutrition criteria (both P < 0.001). The malnourished cluster was negatively associated with the nutritional status, physical status, quality of life, short-term outcomes and was an independent risk factor for survival (HR = 1.38, 95%CI = 1.22-1.55, P < 0.001). Sex, gastrointestinal symptoms, weight loss percentages (within and beyond 6 months), calf circumference, and body mass index were incorporated to develop the nomogram, which showed high performance to predict malnutrition (AUC = 0.972, 95%CI = 0.960-0.983). The decision curve analysis and independent external validation further demonstrated the effectiveness and clinical usefulness of the tool., Conclusions: Nutritional features-based clustering analysis is a feasible approach to define malnutrition. The derived nomogram shows effectiveness for the early identification of malnutrition in patients with cancer., (© 2021. The Author(s), under exclusive licence to Springer Nature Limited part of Springer Nature.)

Background: The number of cancer patients with diabetes mellitus (DM) is steadily rising. Little is known about the nutritional status of this population. This study characterized the nutritional status and survival of cancer patients with diabetes compared with those without diabetes., Methods: A total of 8247 cancer patients were prospectively enrolled from 72 hospitals in China and followed until August 2019. A global estimation of the nutritional status was performed for each participant using standardized tools. The outcomes were cancer-specific survival (CSS) and overall survival (OS)., Results: The incidence of diabetes was 7.6% in the whole population. In comparison with the non-DM group, the DM group had greater body weight, but a similar fat-free mass, a lower handgrip strength and a decreased Karnofsky performance score. A higher proportion of patients with diabetes were overweight/obese as indicated by BMI. The percentage of patients who were at risk of malnutrition (evaluated by PG-SGA) was higher in the DM group (score ≥ 4, 56.7% vs 52.9%). Patients with DM showed a worse CSS (4-year CSS, 62% vs 73%) and OS (4-year OS 39% vs 52%). Diabetes was associated with an increased risk of both cancer-specific (hazard ratio (HR) = 1.282, 95% confidence interval (CI) 1.070-1.536) and overall (HR = 1.206, 95% CI 1.040-1.399) mortality., Conclusions: Cancer patients with diabetes had a larger body mass but lower muscle strength, poorer performance status and higher incidence of malnourishment. Diabetes was associated with compromised survival. Tailored nutritional intervention is necessary for this subpopulation of patients., (© 2020 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.)

Although this is an exciting time for translational medicine, systematic approaches and strategies to conduct translational research are sparse. We highlight in this editorial the opportunities to collaborate across disciplines and to forge new interdisciplinary collaborative ventures from the perspective of epidemiology. We specifically outline some feasible research areas, wherein Translational Epidemiology may readily speed up the translation of research for Precision Medicine., Competing Interests: None

Background: Tobacco smoking is a major risk factor for many diseases. We sought to quantify the burden of tobacco-smoking-related deaths in Asia, in parts of which men's smoking prevalence is among the world's highest., Methods and Findings: We performed pooled analyses of data from 1,049,929 participants in 21 cohorts in Asia to quantify the risks of total and cause-specific mortality associated with tobacco smoking using adjusted hazard ratios and their 95% confidence intervals. We then estimated smoking-related deaths among adults aged ≥45 y in 2004 in Bangladesh, India, mainland China, Japan, Republic of Korea, Singapore, and Taiwan-accounting for ∼71% of Asia's total population. An approximately 1.44-fold (95% CI = 1.37-1.51) and 1.48-fold (1.38-1.58) elevated risk of death from any cause was found in male and female ever-smokers, respectively. In 2004, active tobacco smoking accounted for approximately 15.8% (95% CI = 14.3%-17.2%) and 3.3% (2.6%-4.0%) of deaths, respectively, in men and women aged ≥45 y in the seven countries/regions combined, with a total number of estimated deaths of ∼1,575,500 (95% CI = 1,398,000-1,744,700). Among men, approximately 11.4%, 30.5%, and 19.8% of deaths due to cardiovascular diseases, cancer, and respiratory diseases, respectively, were attributable to tobacco smoking. Corresponding proportions for East Asian women were 3.7%, 4.6%, and 1.7%, respectively. The strongest association with tobacco smoking was found for lung cancer: a 3- to 4-fold elevated risk, accounting for 60.5% and 16.7% of lung cancer deaths, respectively, in Asian men and East Asian women aged ≥45 y., Conclusions: Tobacco smoking is associated with a substantially elevated risk of mortality, accounting for approximately 2 million deaths in adults aged ≥45 y throughout Asia in 2004. It is likely that smoking-related deaths in Asia will continue to rise over the next few decades if no effective smoking control programs are implemented. Please see later in the article for the Editors' Summary.