Systematic discovery of mutation-directed neo-protein-protein interactions in cancer.

Comprehensive sequencing of patient tumors reveals genomic mutations across tumor types that enable tumorigenesis and progression. A subset of oncogenic driver mutations results in neomorphic activity where the mutant protein mediates functions not engaged by the parental molecule. Here, we identify prevalent variant-enabled neomorph-protein-protein interactions (neoPPI) with a quantitative high-throughput differential screening (qHT-dS) platform. The coupling of highly sensitive BRET biosensors with miniaturized coexpression in an ultra-HTS format allows large-scale monitoring of the interactions of wild-type and mutant variant counterparts with a library of cancer-associated proteins in live cells. The screening of 17,792 interactions with 2,172,864 data points revealed a landscape of gain of interactions encompassing both oncogenic and tumor suppressor mutations. For example, the recurrent BRAF V600E lesion mediates KEAP1 neoPPI, rewiring a BRAFV600E/KEAP1 signaling axis and creating collateral vulnerability to NQO1 substrates, offering a combination therapeutic strategy. Thus, cancer genomic alterations can create neo-interactions, informing variant-directed therapeutic approaches for precision medicine.

Integrative Proteomic Characterization of Human Lung Adenocarcinoma.

Genomic studies of lung adenocarcinoma (LUAD) have advanced our understanding of the disease's biology and accelerated targeted therapy. However, the proteomic characteristics of LUAD remain poorly understood. We carried out a comprehensive proteomics analysis of 103 cases of LUAD in Chinese patients. Integrative analysis of proteome, phosphoproteome, transcriptome, and whole-exome sequencing data revealed cancer-associated characteristics, such as tumor-associated protein variants, distinct proteomics features, and clinical outcomes in patients at an early stage or with EGFR and TP53 mutations. Proteome-based stratification of LUAD revealed three subtypes (S-I, S-II, and S-III) related to different clinical and molecular features. Further, we nominated potential drug targets and validated the plasma protein level of HSP 90ß as a potential prognostic biomarker for LUAD in an independent cohort. Our integrative proteomics analysis enables a more comprehensive understanding of the molecular landscape of LUAD and offers an opportunity for more precise diagnosis and treatment.

A Translation-Activating Function of MIWI/piRNA during Mouse Spermiogenesis.

Spermiogenesis is a highly orchestrated developmental process during which chromatin condensation decouples transcription from translation. Spermiogenic mRNAs are transcribed earlier and stored in a translationally inert state until needed for translation; however, it remains largely unclear how such repressed mRNAs become activated during spermiogenesis. We previously reported that the MIWI/piRNA machinery is responsible for mRNA elimination during late spermiogenesis in preparation for spermatozoa production. Here we unexpectedly discover that the same machinery is also responsible for activating translation of a subset of spermiogenic mRNAs to coordinate with morphological transformation into spermatozoa. Such action requires specific base-pairing interactions of piRNAs with target mRNAs in their 3' UTRs, which activates translation through coupling with cis-acting AU-rich elements to nucleate the formation of a MIWI/piRNA/eIF3f/HuR super-complex in a developmental stage-specific manner. These findings reveal a critical role of the piRNA system in translation activation, which we show is functionally required for spermatid development.

Leveraging cross-species transcription factor binding site patterns: from diabetes risk loci to disease mechanisms.

Genome-wide association studies have revealed numerous risk loci associated with diverse diseases. However, identification of disease-causing variants within association loci remains a major challenge. Divergence in gene expression due to cis-regulatory variants in noncoding regions is central to disease susceptibility. We show that integrative computational analysis of phylogenetic conservation with a complexity assessment of co-occurring transcription factor binding sites (TFBS) can identify cis-regulatory variants and elucidate their mechanistic role in disease. Analysis of established type 2 diabetes risk loci revealed a striking clustering of distinct homeobox TFBS. We identified the PRRX1 homeobox factor as a repressor of PPARG2 expression in adipose cells and demonstrate its adverse effect on lipid metabolism and systemic insulin sensitivity, dependent on the rs4684847 risk allele that triggers PRRX1 binding. Thus, cross-species conservation analysis at the level of co-occurring TFBS provides a valuable contribution to the translation of genetic association signals to disease-related molecular mechanisms.

Structure-preserved integration of scRNA-seq data using heterogeneous graph neural network.

The integration of single-cell RNA sequencing (scRNA-seq) data from multiple experimental batches enables more comprehensive characterizations of cell states. Given that existing methods disregard the structural information between cells and genes, we proposed a structure-preserved scRNA-seq data integration approach using heterogeneous graph neural network (scHetG). By establishing a heterogeneous graph that represents the interactions between multiple batches of cells and genes, and combining a heterogeneous graph neural network with contrastive learning, scHetG concurrently obtained cell and gene embeddings with structural information. A comprehensive assessment covering different species, tissues and scales indicated that scHetG is an efficacious method for eliminating batch effects while preserving the structural information of cells and genes, including batch-specific cell types and cell-type specific gene co-expression patterns.

Restoration of energy homeostasis under oxidative stress: Duo synergistic AMPK pathways regulating arginine kinases.

Rapid depletion of cellular ATP can occur by oxidative stress induced by reactive oxygen species (ROS). Maintaining energy homeostasis requires the key molecular components AMP-activated protein kinase (AMPK) and arginine kinase (AK), an invertebrate orthologue of the mammalian creatine kinase (CK). Here, we deciphered two independent and synergistic pathways of AMPK acting on AK by using the beetle Tribolium castaneum as a model system. First, AMPK acts on transcriptional factor forkhead box O (FOXO) leading to phosphorylation and nuclear translocation of the FOXO. The phospho-FOXO directly promotes the expression of AK upon oxidative stress. Concomitantly, AMPK directly phosphorylates the AK to switch the direction of enzymatic catalysis for rapid production of ATP from the phosphoarginine-arginine pool. Further in vitro assays revealed that Sf9 cells expressing phospho-deficient AK mutants displayed the lower ATP/ADP ratio and cell viability under paraquat-induced oxidative stress conditions when compared with Sf9 cells expressing wild-type AKs. Additionally, the AMPK-FOXO-CK pathway is also involved in the restoration of ATP homeostasis under oxidative stress in mammalian HEK293 cells. Overall, we provide evidence that two distinct AMPK-AK pathways, transcriptional and post-translational regulations, are coherent responders to acute oxidative stresses and distinguished from classical AMPK-mediated long-term metabolic adaptations to energy challenge.

The pleiotropic AMPK-CncC signaling pathway regulates the trade-off between detoxification and reproduction.

The association of decreased fecundity with insecticide resistance and the negative sublethal effects of insecticides on insect reproduction indicates the typical trade-off between two highly energy-demanding processes, detoxification and reproduction. However, the underlying mechanisms are poorly understood. The energy sensor adenosine monophosphate-activated protein kinase (AMPK) and the transcription factor Cap "n" collar isoform C (CncC) are important regulators of energy metabolism and xenobiotic response, respectively. In this study, using the beetle Tribolium castaneum as a model organism, we found that deltamethrin-induced oxidative stress activated AMPK, which promoted the nuclear translocation of CncC through its phosphorylation. The CncC not only acts as a transcription activator of cytochrome P450 genes but also regulates the expression of genes coding for ecdysteroid biosynthesis and juvenile hormone (JH) degradation enzymes, resulting in increased ecdysteroid levels as well as decreased JH titer and vitellogenin (Vg) gene expression. These data show that in response to xenobiotic stress, the pleiotropic AMPK-CncC signaling pathway mediates the trade-off between detoxification and reproduction by up-regulating detoxification genes and disturbing hormonal homeostasis.

The acyl-acyl carrier protein thioesterases GmFATA1 and GmFATA2 are essential for fatty acid accumulation and growth in soybean.

Acyl-acyl carrier protein (ACP) thioesterases (FAT) hydrolyze acyl-ACP complexes to release FA in plastids, which ultimately affects FA biosynthesis and profiles. Soybean GmFATA1 and GmFATA2 are homoeologous genes encoding oleoyl-ACP thioesterases whose role in seed oil accumulation and plant growth has not been defined. Using CRISPR/Cas9 gene editing mutation of Gmfata1 or 2 led to reduced leaf FA content and growth defect at the early seedling stage. In contrast, no homozygous double mutants were obtained. Combined this indicates that GmFATA1 and GmFATA2 display overlapping, but not complete functional redundancy. Combined transcriptomic and lipidomic analysis revealed a large number of genes involved in FA synthesis and FA chain elongation are expressed at reduced level in the Gmfata1 mutant, accompanied by a lower triacylglycerol abundance at the early seedling stage. Further analysis showed that the Gmfata1 or 2 mutants had increased composition of the beneficial FA, oleic acid. The growth defect of Gmfata1 could be at least partially attributed to reduced acetyl-CoA carboxylase activity, reduced abundance of five unsaturated monogalactosyldiacylglycerol lipids, and altered chloroplast morphology. On the other hand, overexpression of GmFATA in soybean led to significant increases in leaf FA content by 5.7%, vegetative growth, and seed yield by 26.9%, and seed FA content by 23.2%. Thus, overexpression of GmFATA is an effective strategy to enhance soybean oil content and yield.

Bile metabolic fingerprints distinguish biliary tract cancer from benign biliary diseases.

BACKGROUND AND AIMS: Biliary tract cancers are aggressive gastrointestinal malignancies characterized by a dismal 5-year overall survival rate <20%. Current diagnostic modalities suffer from limitations regarding sensitivity and specificity. This study aimed to develop a bile metabolite-based platform for precise discrimination between malignant and benign biliary diseases. APPROACH AND RESULTS: Samples were collected from 336 patients with biliary tract cancer or benign biliary diseases across 3 independent cohorts. Untargeted metabolic fingerprinting was performed on 300 bile samples using novel nanoparticle-enhanced laser desorption/ionization mass spectrometry. Subsequently, a diagnostic assay was developed based on the exploratory cohort using a selected bile metabolic biomarker panel, with performance evaluated in the validation cohort. Further external validation of disease-specific metabolites from bile samples was conducted in a prospective cohort (n = 36) using quantitative analysis. As a result, we established a novel bile-based assay, BileMet, for the rapid and precise detection of malignancies in the biliary tract system with an AUC of 0.891. We identified 6-metabolite biomarker candidates and discovered the critical role of the chenodeoxycholic acid glycine conjugate as a protective metabolite associated with biliary tract cancer. CONCLUSIONS: Our findings confirmed the improved diagnostic capabilities of BileMet assay in a clinical setting. If applied, the BileMet assay enables intraoperative testing and fast medical decision-making for cases with suspected malignancy where brush cytology detection fails to support malignancy, ultimately reducing the economic burden by over 90%.

Diagnosis and prognosis of breast cancer by high-performance serum metabolic fingerprints.

High-performance metabolic analysis is emerging in the diagnosis and prognosis of breast cancer (BrCa). Still, advanced tools are in demand to deliver the application potentials of metabolic analysis. Here, we used fast nanoparticle-enhanced laser desorption/ionization mass spectrometry (NPELDI-MS) to record serum metabolic fingerprints (SMFs) of BrCa in seconds, achieving high reproducibility and low consumption of direct serum detection without treatment. Subsequently, machine learning of SMFs generated by NPELDI-MS functioned as an efficient readout to distinguish BrCa from non-BrCa with an area under the curve of 0.948. Furthermore, a metabolic prognosis scoring system was constructed using SMFs with effective prediction performance toward BrCa (P < 0.005). Finally, we identified a biomarker panel of seven metabolites that were differentially enriched in BrCa serum and their related pathways. Together, our findings provide an efficient serum metabolic tool to characterize BrCa and highlight certain metabolic signatures as potential diagnostic and prognostic factors of diseases including but not limited to BrCa.

Integration of scRNA-seq data by disentangled representation learning with condition domain adaptation.

BACKGROUND: The integration of single-cell RNA sequencing data from multiple experimental batches and diverse biological conditions holds significant importance in the study of cellular heterogeneity. RESULTS: To expedite the exploration of systematic disparities under various biological contexts, we propose a scRNA-seq integration method called scDisco, which involves a domain-adaptive decoupling representation learning strategy for the integration of dissimilar single-cell RNA data. It constructs a condition-specific domain-adaptive network founded on variational autoencoders. scDisco not only effectively reduces batch effects but also successfully disentangles biological effects and condition-specific effects, and further augmenting condition-specific representations through the utilization of condition-specific Domain-Specific Batch Normalization layers. This enhancement enables the identification of genes specific to particular conditions. The effectiveness and robustness of scDisco as an integration method were analyzed using both simulated and real datasets, and the results demonstrate that scDisco can yield high-quality visualizations and quantitative outcomes. Furthermore, scDisco has been validated using real datasets, affirming its proficiency in cell clustering quality, retaining batch-specific cell types and identifying condition-specific genes. CONCLUSION: scDisco is an effective integration method based on variational autoencoders, which improves analytical tasks of reducing batch effects, cell clustering, retaining batch-specific cell types and identifying condition-specific genes.

Discovery of FERM domain protein-protein interaction inhibitors for MSN and CD44 as a potential therapeutic approach for Alzheimer's disease.

Proteomic studies have identified moesin (MSN), a protein containing a four-point-one, ezrin, radixin, moesin (FERM) domain, and the receptor CD44 as hub proteins found within a coexpression module strongly linked to Alzheimer's disease (AD) traits and microglia. These proteins are more abundant in Alzheimer's patient brains, and their levels are positively correlated with cognitive decline, amyloid plaque deposition, and neurofibrillary tangle burden. The MSN FERM domain interacts with the phospholipid phosphatidylinositol 4,5-bisphosphate (PIP2) and the cytoplasmic tail of CD44. Inhibiting the MSN-CD44 interaction may help limit AD-associated neuronal damage. Here, we investigated the feasibility of developing inhibitors that target this protein-protein interaction. We have employed structural, mutational, and phage-display studies to examine how CD44 binds to the FERM domain of MSN. Interestingly, we have identified an allosteric site located close to the PIP2 binding pocket that influences CD44 binding. These findings suggest a mechanism in which PIP2 binding to the FERM domain stimulates CD44 binding through an allosteric effect, leading to the formation of a neighboring pocket capable of accommodating a receptor tail. Furthermore, high-throughput screening of a chemical library identified two compounds that disrupt the MSN-CD44 interaction. One compound series was further optimized for biochemical activity, specificity, and solubility. Our results suggest that the FERM domain holds potential as a drug development target. Small molecule preliminary leads generated from this study could serve as a foundation for additional medicinal chemistry efforts with the goal of controlling microglial activity in AD by modifying the MSN-CD44 interaction.

Interfacial Self-Assembly Nanostructures: Constructions and Applications.

Interfacial self-assembly nanoarrays refer to the spontaneously organized nanostructures at interfaces, relying on the intrinsic properties of involved materials, such as surface energy, molecular structure, and interactions. In recent years, the exponential growth of self-assembly nanotechnology has substantially expanded the utility of nanomaterials. Particularly, non-covalent interactions-based interfacial self-assembly represents a viable and promising approach for the synthesis of novel nanostructure. This review introduces the significance and current development status of interfacial self-assembly technology, focusing on the driving mode, application, and prospects of interfacial self-assembly nanoarrays over the past few years.

3'UTR of ALV-J can affect viral replication through promoting transcription and mRNA nuclear export.

IMPORTANCE: 3'UTRs can affect gene transcription and post-transcriptional regulation in multiple ways, further influencing the function of proteins in a unique manner. Recently, ALV-J has been mutating and evolving rapidly, especially the 3'UTR of viral genome. Meanwhile, clinical symptoms caused by ALV-J have changed significantly. In this study, we found that the ALV-J strains containing △-r-TM-type 3'UTR are the most abundant. By constructing ALV-J infectious clones and subgenomic vectors containing different 3'UTRs, we prove that 3'UTRs directly affect viral tissue preference and can promote virus replication as an enhancer. ALV-J strain containing 3'UTR of △-r-TM proliferated fastest in primary cells. All five forms of 3'UTRs can assist intron-containing viral mRNA nuclear export, with similar efficiency. ALV-J mRNA half-life is not influenced by different 3'UTRs. Our results dissect the roles of 3'UTR on regulating viral replication and pathogenicity, providing novel insights into potential anti-viral strategies.

scAce: an adaptive embedding and clustering method for single-cell gene expression data.

MOTIVATION: Since the development of single-cell RNA sequencing (scRNA-seq) technologies, clustering analysis of single-cell gene expression data has been an essential tool for distinguishing cell types and identifying novel cell types. Even though many methods have been available for scRNA-seq clustering analysis, the majority of them are constrained by the requirement on predetermined cluster numbers or the dependence on selected initial cluster assignment. RESULTS: In this article, we propose an adaptive embedding and clustering method named scAce, which constructs a variational autoencoder to simultaneously learn cell embeddings and cluster assignments. In the scAce method, we develop an adaptive cluster merging approach which achieves improved clustering results without the need to estimate the number of clusters in advance. In addition, scAce provides an option to perform clustering enhancement, which can update and enhance cluster assignments based on previous clustering results from other methods. Based on computational analysis of both simulated and real datasets, we demonstrate that scAce outperforms state-of-the-art clustering methods for scRNA-seq data, and achieves better clustering accuracy and robustness. AVAILABILITY AND IMPLEMENTATION: The scAce package is implemented in python 3.8 and is freely available from https://github.com/sldyns/scAce.

Development of an FAP-Targeted PET Probe Based on a Novel Quinolinium Molecular Scaffold.

Fibroblast activation protein (FAP) has recently gained significant attention as a promising tumor biomarker for both diagnosis and therapeutic applications. A series of radiopharmaceuticals based on fibroblast activation protein inhibitors (FAPIs) have been developed and translated into the clinic. Though some of them such as radiolabeled FAPI-04 probes have achieved favorable in vivo imaging performance, further improvement is still highly desired for obtaining radiopharmaceuticals with a high theranostics potential. In this study, we innovatively designed an FAPI ligand SMIC-3002 by changing the core quinoline motif of FAPI-04 to the quinolinium scaffold. The engineered molecule was further radiolabeled with 68Ga to generate a positron emission tomography (PET) probe, [68Ga]Ga-SMIC-3002, which was then evaluated in vitro and in vivo. [68Ga]Ga-SMIC-3002 demonstrated high in vitro stability, nanomolar affinity for FAP (8 nM for protein, 23 nM for U87MG cells), and specific uptake in FAP-expressing tumors, with a tumor/muscle ratio of 19.1 and a tumor uptake of 1.48 ± 0.03 ID/g% at 0.5 h in U87MG tumor-bearing mice. In summary, the quinolinium scaffold can be successfully used for the development of the FAP-targeted tracer. [68Ga]Ga-SMIC-3002 not only shows high potential for clinical translation but also offers insights into designing a new generation of FAPI tracers.

Prognostic biomarker discovery based on proteome landscape of Chinese lung adenocarcinoma.

Despite recent innovations in imaging and genomic screening promotes advance in diagnosis and treatment of lung adenocarcinoma (LUAD), there remains high mortality of LUAD and insufficient understanding of LUAD biology. Our previous study performed an integrative multi-omic analysis of LUAD, filling the gap between genomic alterations and their biological proteome effects. However, more detailed molecular characterization and biomarker resources at proteome level still need to be uncovered. In this study, a quantitative proteomic experiment of patient-derived benign lung disease samples was carried out. After that, we integrated the proteomic data with previous dataset of 103 paired LUAD samples. We depicted the proteomic differences between non-cancerous and tumor samples and among diverse pathological subtypes. We also found that up-regulated mitophagy was a significant characteristic of early-stage LUAD. Additionally, our integrative analysis filtered out 75 potential prognostic biomarkers and validated two of them in an independent LUAD serum cohort. This study provided insights for improved understanding proteome abnormalities of LUAD and the novel prognostic biomarker discovery offered an opportunity for LUAD precise management.

Quinazoline-2,4(1 H,3 H)-dione Scaffold for development of a novel PARP-targeting PET probe for tumor imaging.

PURPOSE: Overexpression of Poly (ADP-ribose) polymerase (PARP) is associated with many diseases such as oncological diseases. Several PARP-targeting radiotracers have been developed to detect tumor in recent years. Two 18F labelled probes based on Olaparib and Rucaparib molecular scaffolds have been evaluated in clinical trials, but their slow hepatic clearance hinders their tumor imaging performance. Although a number of positron emission tomography (PET) probes with lower liver uptake have been designed, the tumor to background ratios remains to be low. Therefore, we designed a probe with low lipid-water partition coefficient to solve this problem. METHODS: A pyridine-containing quinazoline-2,4(1 H,3 H)-dione PARP-targeting group was rationally designed and used to conjugate with the chelator 2,2',2'',2'''-(1,4,7,10-tetraazacyclododecane-1,4,7,10-tetrayl)tetraacetic acid (DOTA) to prepare the lead compound named as SMIC-2001 for radiolabeling. In vitro experiments, the lipid-water partition coefficient, stability, binding affinity, and cellular uptake of [68Ga]Ga-SMIC-2001 were determined. In vivo experiments, the U87MG xenograft models were used to evaluate its tumor imaging properties. RESULTS: [68Ga]Ga-SMIC-2001 showed a low Log D7.4 (-3.82 ± 0.06) and high affinity for PARP-1 (48.13 nM). In vivo study revealed that it exhibited a high tumor-to-background contrast in the U87MG xenograft models and mainly renal clearance. And the ratios of tumor to main organs were high except for the kidney (e.g. tumor to liver ratio reached 2.20 ± 0.51) at 60 min p.i. CONCLUSION: In summary, pyridine-containing quinazoline-2,4(1 H,3 H)-dione is a novel PARP-targeting molecular scaffold for imaging probe development, and [68Ga]Ga-SMIC-2001 is a highly promising PET probe capable of imaging tumors with PARP overexpression.

Nature Products Chlorophyll Derivatives for NIR-II Fluorescence Bioimaging and Plant-Imaging.

The second near-infrared window (NIR-II, 1000-1700 nm) fluorescence imaging has attracted significant attention in research fields because of its unique advantages compared with conventional optical windows (400-900 nm). A variety of NIR-II fluorophores have been actively studied because they serve as a key component of fluorescence imaging. Among them, organic small molecule NIR-II fluorophores display outstanding imaging performance and many advantages, but types of small molecule NIR-II fluorophores with high biocompatibility are still quite limited. Novel molecular scaffolds based NIR-II dyes are highly desired. Herein, we hypothesized that chlorophyll is a new promising molecular platform for discovery NIR-II fluorophores. Thus, seven derivatives of derivatives were selected to characterize their optical properties. Interestingly, six chlorophyll derivatives displayed NIR-II fluorescence imaging capability. This characteristic allowed the successful NIR-II imaging of green leaves of various plants. Furthermore, most of these fluorophores showed capacity to monitor viscosity change because of their sensitive for viscosity. For demonstration of its biomedical applications, these probes were successfully used for NIR-II fluorescence-guided surgical resection of lymph nodes. In summary, chlorophylls are novel valuable tool molecules for NIR-II fluorescence imaging and have potential to expand their applications in biomedical field and plant science.

Development and validation of a nomogram for preoperatively predicting permanent stoma after rectal cancer surgery with ileostomy: a retrospective cohort study.

BACKGROUND: For patients with rectal cancer, the utilization of temporary ileostomy (TI) has proven effective in minimizing the occurrence of severe complications post-surgery, such as anastomotic leaks; however, some patients are unable to reverse in time or even develop a permanent stoma (PS). We aimed to determine the preoperative predictors associated with TS failure and develop and validate appropriate predictive models to improve patients' quality of life. METHODS: This research included 403 patients with rectal cancer who underwent temporary ileostomies between January 2017 and December 2021. All patients were randomly divided into either the developmental (70%) or validation (30%) group. The independent risk factors for PS were determined using univariate and multivariate logistic regression analyses. Subsequently, a nomogram was constructed, and the prediction probability was estimated by calculating the area under the curve (AUC) using receiver operating characteristic (ROC) analysis. A calibration plot was used to evaluate the nomogram calibration. RESULTS: Of the 403 enrolled patients, 282 were randomized into the developmental group, 121 into the validation group, and 58 (14.39%) had a PS. The development group consisted of 282 patients, of whom 39 (13.81%) had a PS. The validation group consisted of 121 patients, of whom, 19 (15.70%) had a PS; 37 related factors were analyzed in the study. Multivariate logistic regression analysis demonstrated significant associations between the occurrence of PS and various factors in this patient cohort, including tumor location (OR = 6.631, P = 0.005), tumor markers (OR = 2.309, P = 0.035), American Society of Anesthesiologists (ASA) score (OR = 4.784, P = 0.004), T4 stage (OR = 2.880, P = 0.036), lymph node metastasis (OR = 4.566, P = 0.001), and distant metastasis (OR = 4.478, P = 0.036). Furthermore, a preoperative nomogram was constructed based on these data and subsequently validated in an independent validation group. CONCLUSION: We identified six independent preoperative risk factors associated with PS following rectal cancer resection and developed a validated nomogram with an area under the ROC curve of 0.7758, which can assist surgeons in formulating better surgical options, such as colostomy, for patients at high risk of PS.