Remnant cholesterol is an effective biomarker for predicting survival in patients with breast cancer.

BACKGROUND: Breast cancer is the most common malignancy in women worldwide. The relationship between remnant cholesterol (RC) and the prognosis of patients with breast cancer has not been clearly reported. This study investigated the prognostic value of RC in predicting mortality in patients with breast cancer. METHODS: This study prospectively analysed 709 women patients with breast cancer from the Investigation on Nutrition Status and Clinical Outcome of Common Cancers (INSCOC) project. Restricted cubic splines were used to analyse the dose-response relationship between RC and breast cancer mortality. The Kaplan-Meier method was used to evaluate the overall survival of patients with breast cancer. A Cox regression analyses was performed to assess the independent association between RC and breast cancer mortality. Inverse probability of treatment weighting (IPTW) using the propensity score was used to reduce confounding. Sensitivity analysis was performed after excluding patients with underlying diseases and survival times shorter than one year. RESULTS: A linear dose-response relationship was identified between RC and the risk of all-cause mortality in patients with breast cancer (p = 0.036). Kaplan-Meier survival analysis and log-rank test showed that patients with high RC levels had poorer survival than those with low RC levels (p = 0.007). Univariate and multivariate Cox regression analyses showed that RC was an independent risk factor for mortality in women patients with breast cancer. IPTW-adjusted analyses and sensitivity analyses showed that CR remained a prognostic factor. CONCLUSIONS: RC is an independent risk factor for the prognosis of patients with breast cancer, and patients with higher RC levels have poorer survival.

Liquid biopsy techniques and lung cancer: diagnosis, monitoring and evaluation.

Lung cancer stands as the most prevalent form of cancer globally, posing a significant threat to human well-being. Due to the lack of effective and accurate early diagnostic methods, many patients are diagnosed with advanced lung cancer. Although surgical resection is still a potential means of eradicating lung cancer, patients with advanced lung cancer usually miss the best chance for surgical treatment, and even after surgical resection patients may still experience tumor recurrence. Additionally, chemotherapy, the mainstay of treatment for patients with advanced lung cancer, has the potential to be chemo-resistant, resulting in poor clinical outcomes. The emergence of liquid biopsies has garnered considerable attention owing to their noninvasive nature and the ability for continuous sampling. Technological advancements have propelled circulating tumor cells (CTCs), circulating tumor DNA (ctDNA), extracellular vesicles (EVs), tumor metabolites, tumor-educated platelets (TEPs), and tumor-associated antigens (TAA) to the forefront as key liquid biopsy biomarkers, demonstrating intriguing and encouraging results for early diagnosis and prognostic evaluation of lung cancer. This review provides an overview of molecular biomarkers and assays utilized in liquid biopsies for lung cancer, encompassing CTCs, ctDNA, non-coding RNA (ncRNA), EVs, tumor metabolites, TAAs and TEPs. Furthermore, we expound on the practical applications of liquid biopsies, including early diagnosis, treatment response monitoring, prognostic evaluation, and recurrence monitoring in the context of lung cancer.

A genetic variant study of bortezomib-induced peripheral neuropathy in Chinese multiple myeloma patients.

Background: Bortezomib results in peripheral neuropathy (PN) in approximately 50% of patients, during multiple myeloma (MM) treatment, a complication known as Bortezomib-induced peripheral neuropathy (BIPN). The drug response varies among individuals. Genetic factor may play an important role in BIPN. Methods: A next-generation sequencing (NGS) panel containing 1659 targets from 233 genes was used to identify risk variants for developing BIPN in 204 MM patients who received bortezomib therapy. mRNA expression of MTHFR and ALDH1A1 in 62 peripheral blood samples was detected by real-time quantitative PCR (RT-qPCR). Serum homocysteine (Hcy) levels were detected in 40 samples by chemiluminescent microparticle immunoassay (CMIA). Results: Compared with the non-BIPN group (n = 89), a total of 8 significantly associated single nucleotide polymorphisms (SNPs) were identified in the BIPN group (n = 115): MTHFR (rs1801131, rs1801133, rs17421511), EPHX1 (rs1051740), MME (rs2016848), ALDH1A1 (rs6151031), HTR7 (rs1935349) and CYP2A6 (rs8192720). The mRNA expression level of MTHFR in newly diagnosed patients with peripheral neuritis after treatment (NP group) was lower than that of newly diagnosed patients without peripheral neuritis after treatment (NnP group) (1.70 ± 0.77 vs. 2.81 ± 0.97, p= 0.009). Serum Hcy levels were significantly higher in BIPN group than in non-BIPN group (11.66 ± 1.79 µmol/L vs. 8.52 ± 3.29 µmol/L, p= 0.016) and healthy controls (11.66 ± 1.79 µmol/L vs. 8.55 ± 2.13 µmol/L, p≤ 0.001). Conclusion: CYP2A6, EPHX1, MTHFR, ALDH1A1, HTR7, MME and BIPN are linked in Chinese MM patients. BIPN is more likely to occur in patients with lower MTHFR mRNA expression, which might result in higher serum Hcy levels.

The relationship between different fatty acids intake and the depressive symptoms: A population-based study.

BACKGROUND: Depression is a common psychological disorder worldwide, affecting mental and physical health. Previous studies have explored the benefits of polyunsaturated fatty acids (PUFAs) intake in depressive symptoms; however, few studies have focused on the association between all types of fatty acids intake and depressive symptoms. Therefore, we explored the relationship between the intake of different fatty acids intake and the risk of depressive symptoms. METHODS: The study was based on the data from the 2005-2018 National Health and Nutrition Examination Survey (NHANES), a large US-based database. We used a nutrient residual model and multi-nutrient density model for the analysis. We calculated the nutrient density and residual in men and women separately, and the fatty acids intake was divided into quartiles based on the sex distribution. The relationship between the depressive symptoms and the intake of different fatty acids was examined using logistic regression; furthermore, we explored the relationships separately in men and women. RESULTS: The intake of monounsaturated fatty acids (MUFAs) and PUFAs, particularly n-3 and n-6 PUFAs, were associated with reduced odds ratios for depressive symptoms. The inverse relationship between the intake of MUFAs, PUFAs, n-3, and n-6 PUFAs and depressive symptoms was stronger in women. The inverse relationship between total fatty acid (TFAs) intake and depressive symptoms existed only in a single model. In contrast, saturated fatty acid (SFAs) intake was not related to depressive symptoms. CONCLUSION: Consuming MUFAs and PUFAs can counteract the depressive symptoms, especially in women.

Developing a cognitive model of solid geometry based on Interpretive Structural Modeling method.

With the advancement of science and artificial intelligence, education is experiencing significant innovation. The adaptive learning system is emerging as a promising approach to achieving personalized learning. The cognitive model plays a crucial role as the fundamental rationale behind the adaptive learning system. Currently, there is no uniform and highly operational method for constructing cognitive models. This study adopts Interpretive Structural Modeling (ISM) as the foundational approach for constructing a cognitive model of solid geometry. Based on literature and expert opinions, 17 cognitive attributes of high school solid geometry were identified. Subsequently, a questionnaire survey involving 40 experts was conducted to establish the contextual relationships among these attributes. Applying the ISM method resulted in a seven-level model. This model was then revised based on expert opinions to create the final cognitive model, revealing three primary paths within the domain of high school solid geometry. This paper contends that the use of the ISM method for constructing cognitive models is effective and objective. The resulting cognitive model unveils the content structure of high school solid geometry, and provides an innovative perspective on the construction of cognitive models.

Deconvolving Passive and Active Targeting of Liposomes Bearing LDL Receptor Binding Peptides Using the Zebrafish Embryo Model.

Improving target versus off-target ratio in nanomedicine remains a major challenge for increasing drug bioavailability and reducing toxicity. Active targeting using ligands on nanoparticle surfaces is a key approach but has limited clinical success. A potential issue is the integration of targeting ligands also changes the physicochemical properties of nanoparticles (passive targeting). Direct studies to understand the mechanisms of active targeting and off-targeting in vivo are limited by the lack of suitable tools. Here, the biodistribution of a representative active targeting liposome is analyzed, modified with an apolipoprotein E (ApoE) peptide that binds to the low-density lipoprotein receptor (LDLR), using zebrafish embryos. The ApoE liposomes demonstrated the expected liver targeting effect but also accumulated in the kidney glomerulus. The ldlra-/- zebrafish is developed to explore the LDLR-specificity of ApoE liposomes. Interestingly, liver targeting depends on the LDLR-specific interaction, while glomerular accumulation is independent of LDLR and peptide sequence. It is found that cationic charges of peptides and the size of liposomes govern glomerular targeting. Increasing the size of ApoE liposomes can avoid this off-targeting. Taken together, the study shows the potential of the zebrafish embryo model for understanding active and passive targeting mechanisms, that can be used to optimize the design of nanoparticles.

Prolyl hydroxylase inhibitor FG-4592 alleviates neuroinflammation via HIF-1/BNIP3 signaling in microglia.

BACKGROUND: Neuroinflammation is responsible for neuropsychiatric dysfunction following acute brain injury and neurodegenerative diseases. This study describes how a hypoxia-inducible factor prolyl hydroxylase (HIF-PHD) inhibitor FG-4592 prevents the lipopolysaccharide (LPS)-induced acute neuroinflammation in microglia. METHODS: The distribution of FG-4592 in mouse brain tissues was determined by collision-induced dissociation tandem mass spectrometry. Microglial activation in the hippocampus was analyzed by immunofluorescence. Moreover, we determined the activation of HIF-1 and nuclear factor-κB (NF-κB) signaling pathways, proinflammatory responses using molecular biological techniques. Transcriptome sequencing and BNIP3 silencing were conducted to explore signaling pathway and molecular mechanisms underlying FG-4592 anti-inflammatory activity. RESULTS: FG-4592 was transported into the brain tissues and LPS increased its transportation. FG-4592 promoted the expression of HIF-1α and induced the downstream gene transcription in the hippocampus. Administration with FG-4592 significantly inhibited microglial hyperactivation and decreased proinflammatory cytokine levels following LPS treatment in the hippocampus. The LPS-induced inflammatory responses and the NF-κB signaling pathway were also downregulated by FG-4592 pretreatment in microglial cells. Mechanistically, Venn diagram analysis of transcriptomic changes of BV2 cells identified that BNIP3 was a shared and common differentially expressed gene among different treatment groups. FG-4592 markedly upregulated the protein levels of BNIP3 in microglia. Importantly, BNIP3 knockdown aggravated the LPS-stimulated inflammatory responses and partially reversed the protection of FG-4592 against microglial inflammatory signaling and microglial activation in the mouse hippocampus. CONCLUSIONS: FG-4592 alleviates neuroinflammation through facilitating microglial HIF-1/BNIP3 signaling pathway in mice. Targeting HIF-PHD/HIF-1/BNIP3 axis is a promising strategy for the development of anti-neuroinflammation drugs.

Deubiquitinase Mysm1 regulates neural stem cell proliferation and differentiation by controlling Id4 expression.

Neural stem cells (NSCs) are critical for brain development and maintenance of neurogenesis. However, the molecular mechanisms that regulate NSC proliferation and differentiation remain unclear. Mysm1 is a deubiquitinase and is essential for the self-renewal and differentiation of several stem cells. It is unknown whether Mysm1 plays an important role in NSCs. Here, we found that Mysm1 was expressed in NSCs and its expression was increased with age in mice. Mice with Mysm1 knockdown by crossing Mysm1 floxed mice with Nestin-Cre mice exhibited abnormal brain development with microcephaly. Mysm1 deletion promoted NSC proliferation and apoptosis, resulting in depletion of the stem cell pool. In addition, Mysm1-deficient NSCs skewed toward neurogenesis instead of astrogliogenesis. Mechanistic investigations with RNA sequencing and genome-wide CUT&Tag analysis revealed that Mysm1 epigenetically regulated Id4 transcription by regulating histone modification at the promoter region. After rescuing the expression of Id4, the hyperproliferation and imbalance differentiation of Mysm1-deficient NSCs was reversed. Additionally, knockdown Mysm1 in aged mice could promote NSC proliferation. Collectively, the present study identified a new factor Mysm1 which is essential for NSC homeostasis and Mysm1-Id4 axis may be an ideal target for proper NSC proliferation and differentiation.

Evaluation and validation of neutrophil to albumin ratio as a promising prognostic marker for all-cause mortality in patients with cancer: a multicenter cohort study.

OBJECTIVES: The practicality and effectiveness of using the prognostic value of the neutrophil-to-albumin ratio (NAR) in evaluating patients with cancer remain unclear, and research is needed to fully understand its potential application in the cancer population. METHODS: The Kaplan-Meier method was used for survival analysis, and the log-rank test was employed for comparison. Univariate and multivariate Cox proportional hazards models were used to determine the prognostic biomarkers, and Logistic regression analysis was conducted to investigate the relationship between NAR and 90-day outcomes and cachexia. RESULTS: The study included 14 682 patients with cancer, divided into discovery (6592 patients), internal validation (2820 patients), and external validation groups (5270 patients). Patients with high NAR had higher all-cause mortality than those with low NAR in the discovery (50.15% versus 69.29%, P < 0.001), internal validation (54.18% versus 70.91%, P < 0.001), and external validation cohorts (40.60% versus 66.68%, P < 0.001). In the discovery cohort, high NAR was observed to be independently associated with all-cause mortality in patients (HR 1.16, 95% CI 1.12-1.19; P < 0.001). Moreover, we validated the promising prognostic value of NAR as a predictor of survival in patients with cancer through internal validation (HR 1.21, 95% CI 1.16-1.27, P < 0.001) and external validation cohorts (HR 1.27, 95% CI 1.21-1.34, P < 0.001). Additionally, in the subgroup analysis by tumor type, high NAR was identified as a risk factor for most cancers, except for breast cancer. CONCLUSIONS: This study showed that NAR is a feasible and promising biomarker for predicting prognosis and cancer cachexia in cancer patients.

Systemic inflammation and insulin resistance-related indicator predicts poor outcome in patients with cancer cachexia.

BACKGROUND: The C-reactive protein (CRP)-triglyceride-glucose (TyG) index (CTI), which is a measure representing the level of inflammation and insulin resistance (IR), is related to poor cancer prognosis; however, the CTI has not been validated in patients with cancer cachexia. Thus, this study aimed to explore the potential clinical value of the CTI in patients with cancer cachexia. METHODS: In this study, our prospective multicenter cohort included 1411 patients with cancer cachexia (mean age 59.45 ± 11.38, 63.3% male), which was a combined analysis of multiple cancer types. We randomly selected 30% of the patients for the internal test cohort (mean age 58.90 ± 11.22% 61.4% male). Additionally, we included 307 patients with cancer cachexia in the external validation cohort (mean age 61.16 ± 11, 58.5% male). Receiver operating characteristic (ROC) and calibration curves were performed to investigate the prognostic value of CTI. The prognostic value of the CTI was also investigated performing univariate and multivariate survival analyses. RESULTS: The survival curve indicated that the CTI showed a significant prognostic value in the total, internal, and external validation cohorts. Prognostic ROC curves and calibration curves revealed that the CTI showed good consistency in predicting the survival of patients with cancer cachexia. Multivariate survival analysis showed that an elevated CTI increased the risk of death by 22% (total cohort, 95% confidence interval [CI] = 1.13-1.33), 34% (internal test cohort, 95%CI = 1.11-1.62), and 35% (external validation cohort, 95%CI = 1.14-1.59) for each increase in the standard deviation of CTI. High CTI reliably predicted shorter survival (total cohort, hazard ratio [HR] = 1.45, 95%CI = 1.22-1.71; internal test cohort, HR = 1.62, 95%CI = 1.12-2.36; external validation cohort, HR = 1.61, 95%CI = 1.15-2.26). High CTI significantly predicted shorter survival in different tumor subgroups, such as esophageal [HR = 2.11, 95%CI = 1.05-4.21] and colorectal cancer [HR = 2.29, 95%CI = 1.42-3.71]. The mediating effects analysis found that the mediating proportions of PGSGA, ECOG PS, and EORTC QLQ-C30 on the direct effects of CTI were 21.72%, 19.63%, and 11.61%, respectively We found that there was a significant positive correlation between the CTI and 90-day [HR = 2.48, 95%CI = 1.52-4.14] and 180-day mortality [HR = 1.77,95%CI = 1.24-2.55] in patients with cancer cachexia. CONCLUSION: The CTI can predict the short- and long-term survival of patients with cancer cachexia and provide a useful prognostic tool for clinical practice.

Nucleic acid degradation as barrier to gene delivery: a guide to understand and overcome nuclease activity.

Gene therapy is on its way to revolutionize the treatment of both inherited and acquired diseases, by transferring nucleic acids to correct a disease-causing gene in the target cells of patients. In the fight against infectious diseases, mRNA-based therapeutics have proven to be a viable strategy in the recent Covid-19 pandemic. Although a growing number of gene therapies have been approved, the success rate is limited when compared to the large number of preclinical and clinical trials that have been/are being performed. In this review, we highlight some of the hurdles which gene therapies encounter after administration into the human body, with a focus on nucleic acid degradation by nucleases that are extremely abundant in mammalian organs, biological fluids as well as in subcellular compartments. We overview the available strategies to reduce the biodegradation of gene therapeutics after administration, including chemical modifications of the nucleic acids, encapsulation into vectors and co-administration with nuclease inhibitors and discuss which strategies are applied for clinically approved nucleic acid therapeutics. In the final part, we discuss the currently available methods and techniques to qualify and quantify the integrity of nucleic acids, with their own strengths and limitations.

Association of systemic inflammation with the obesity paradox in cancer: results from multi-cohort studies.

AIMS: This study aimed to explore whether the obesity paradox exists in overall and specific cancers and to investigate the role of systemic inflammation in the obesity paradox. METHODS: The Cox proportional hazard model was used to explore the relationship between body mass index (BMI) and all-cause mortality. The mediated effect was used to investigate the proportion of systemic inflammation mediating the relationship between BMI and cancer survival risk. RESULTS: The survival probability showed a step-like increase with an increase in BMI regardless of pathological stage. Approximately 10.8%-24.0% of the overall association between BMI and all-cause mortality in cancer was mediated by inflammation. In the internal validation, we found evidence of the obesity paradox in all body composition obtained using BIA, with inflammation remaining an important mediating factor. Furthermore, we also validated the existence of the obesity paradox of cancer in NHANES. Systemic inflammation remains an important factor in mediating the association between BMI and prognosis in cancer patients. CONCLUSIONS: The obesity paradox is prevalent in most cancers, except for hepatic biliary cancer and breast cancer. Inflammation may be one of the true features of the obesity paradox in cancer.

Crystalline Polyphenylene Covalent Organic Frameworks.

The synthesis of crystalline polyphenylene covalent organic frameworks (COFs) was accomplished by linking fluorinated tris(4-acetylphenyl)benzene building units using aldol cyclotrimerization. The structures of the two COFs, reported here, were confirmed by powder X-ray diffraction techniques, Fourier transform infrared, and solid-state 13C CP/MAS NMR spectroscopy. The results showed that the COFs were porous and chemically stable in corrosive, harsh environments for at least 1 week. Accordingly, postsynthetically modified derivatives of these COFs using primary amines showed CO2 uptake from air and flue gas.

Photo-activatable Reagents for Bioorthogonal Ligation Reactions.

Light-induced bioorthogonal reactions offer spatiotemporal control over selective biomolecular labeling. This review covers the recent advances in the design of photo-activatable reagents for bioorthogonal conjugation reactions in living systems. These reagents are stable in the absence of light, but transformed into reactive species upon light illumination, which then undergo rapid ligation reactions. The light wavelength has been tuned from ultraviolet to near infrared to enable efficient photo-activation in reactions in deep tissues. The most prominent photo-activatable reagents are presented, including tetrazoles, tetrazines, 9,10-phenanthrenequinone, diarylsydnones, and others. A particular focus is on the strategies for improving reaction kinetics and biocompatibility accomplished through careful molecular engineering. The utilities of these photo-activatable reagents are illustrated through a broad range of biological applications, including in vivo protein labeling, positron emission tomography (PET) imaging, responsive hydrogels, and fluorescence microscopy. The further development and optimization of these biocompatible photo-activatable reagents should lead to new chemical biology strategies for studying biomolecular structure and function in living systems.

Cholesterol-modified prognostic nutritional index (CPNI) as an effective tool for assessing the nutrition status and predicting survival in patients with breast cancer.

BACKGROUND: Malnutrition is associated with poor overall survival (OS) in breast cancer patients; however, the most predictive nutritional indicators for the prognosis of patients with breast cancer are not well-established. This study aimed to compare the predictive effects of common nutritional indicators on OS and to refine existing nutritional indicators, thereby identifying a more effective nutritional evaluation indicator for predicting the prognosis in breast cancer patients. METHODS: This prospective study analyzed data from 776 breast cancer patients enrolled in the "Investigation on Nutritional Status and its Clinical Outcome of Common Cancers" (INSCOC) project, which was conducted in 40 hospitals in China. We used the time-dependent receiver operating characteristic curve (ROC), Kaplan-Meier survival curve, and Cox regression analysis to evaluate the predictive effects of several nutritional assessments. These assessments included the patient-generated subjective nutrition assessment (PGSGA), the global leadership initiative on malnutrition (GLIM), the controlling nutritional status (CONUT), the nutritional risk index (NRI), and the prognostic nutritional index (PNI). Utilizing machine learning, these nutritional indicators were screened through single-factor analysis, and relatively important variables were selected to modify the PNI. The modified PNI, termed the cholesterol-modified prognostic nutritional index (CPNI), was evaluated for its predictive effect on the prognosis of patients. RESULTS: Among the nutritional assessments (including PGSGA, GLIM, CONUT, NRI, and PNI), PNI showed the highest predictive ability for patient prognosis (time-dependent ROC = 0.58). CPNI, which evolved from PNI, emerged as the superior nutritional index for OS in breast cancer patients, with the time-dependent ROC of 0.65. It also acted as an independent risk factor for mortality (p < 0.05). Moreover, the risk of malnutrition and mortality was observed to increase gradually among both premenopausal and postmenopausal age women, as well as among women categorized as non-overweight, overweight, and obese. CONCLUSIONS: The CPNI proves to be an effective nutritional assessment tool for predicting the prognosis of patients with breast cancer.

Case Report: CD19 CAR T-cell therapy following autologous stem cell transplantation: a successful treatment for R/R CD20-negative transformed follicular lymphoma with TP53 mutation.

Background: Follicular lymphoma (FL), a common indolent B-cell lymphoma, has the potential to transform into an aggressive lymphoma, such as diffuse large B-cell lymphoma (DLBCL). The outcome of patients with transformed follicular lymphoma (tFL) is poor, especially in patients with transformed lymphoma after chemotherapy and patients with progression within 24 months (POD24). Chimeric antigen receptor (CAR) T-cell therapy combined with autologous stem cell transplantation (ASCT) has promising antitumor efficacy. Case presentation: Here, we described a 39-year-old male patient who was initially diagnosed with FL that transformed into DLBCL with POD24, CD20 negativity, TP53 mutation, and a bulky mass after 3 lines of therapy, all of which were adverse prognostic factors. We applied a combination approach: CD19 CAR T-cell infusion following ASCT. Ibrutinib was administered continuously to enhance efficacy, DHAP was administered as a salvage chemotherapy, and ICE was administered as a bridging regimen. The patient underwent BEAM conditioning on days -7~ -1, a total of 3.8 × 106/kg CD34+ stem cells were infused on days 01~02, and a total of 108 CAR T cells (relmacabtagene autoleucel, relma-cel, JWCAR029) were infused on day 03. The patient experienced grade 2 cytokine release syndrome (CRS), manifesting as fever and hypotension according to institutional standards. There was no immune effector cell-associated neurotoxicity syndrome (ICANS) after CAR T-cell infusion. Finally, the patient achieved CMR at +1 month, which has been maintained without any other adverse effects. Conclusion: This case highlights the amazing efficacy of CD19 CAR T-cell therapy following ASCT for R/R tFL, thus providing new insight on therapeutic strategies for the future.

Predicted lean body mass trajectories, and cancer risk and cancer-specific and all-cause mortality: A prospective cohort study.

BACKGROUND: Although many studies have investigated the association between body composition, cancer risk and mortality, predicting these risks through a single body composition measurement undoubtedly increases the limitations of the study. Few studies have explored the association between the trajectory of changes in body composition and the risk of cancer and death. We aimed to explore the association of predicted lean mass trajectories with cancer risk, cancer-specific mortality and all-cause mortality. METHODS: The participants in this study were all from the Kailuan cohort, a prospective, periodic, resurvey cohort study initiated in 2006. Latent mixture modelling was used to identify predicted lean mass trajectories for 2006-2010. The hazard ratios (HRs) and 95% confidence intervals (95% CIs) of the Cox proportional hazard models were used to describe the association between predicted lean mass trajectories and cancer risk and cancer-specific and all-cause mortality during follow-up (2010-2021). RESULTS: A total of 44 374 participants (average age, 53.01 ± 11.41 years, 78.99% men and 21.01% women) were enrolled in this study. Five distinct trajectories were identified: low-stable (n = 12 060), low-increasing (n = 8027), moderately stable-decreasing (n = 4725), moderately stable-increasing (n = 8053) and high-stable (n = 11 509). During the 11-year follow-up period, 2183 cancer events were recorded. After adjusting for age, predicted fat mass in 2010, sex, BMI, sedentary, physical activity, smoke, alcohol use, salt consumption, high-fat diet, high-sensitivity C-reactive protein, serum creatinine, family history of tumour, hypertension, diabetes mellitus, compared with the low-stable group, participants in the low-increasing group (HR = 0.851, 95% CI, 0.748-0.969), moderately stable-increasing group (HR = 0.803, 95% CI, 0.697-0.925) and high-stable group (HR = 0.770, 95% CI, 0.659-0.901) had a lower cancer risk, but not in the moderately stable-decreasing group (HR = 0.864, 95% CI, 0.735-1.015). Compared with the low-stable group, the risk of cancer-specific mortality was reduced by 25.4% (8.8-38.9%), 36.5% (20.3-49.4%) and 35.4% (17.9-49.2%), and the risk of all-cause mortality was reduced by 24.2% (16.9-30.8%), 37.0% (30.0-43.2%) and 47.4% (41.0-53.1%) in the low-increasing, moderately stable-increasing group and high-stable groups, respectively. CONCLUSIONS: Predicted lean mass trajectories may be closely associated with cancer risk and cancer-specific and all-cause mortality. Regular monitoring of body composition is necessary.