Phenome-wide association study in 25,639 pregnant Chinese women reveals loci associated with maternal comorbidities and child health.

Phenome-wide association studies (PheWAS) have been less focused on maternal diseases and maternal-newborn comorbidities, especially in the Chinese population. To enhance our understanding of the genetic basis of these related diseases, we conducted a PheWAS on 25,639 pregnant women and 14,151 newborns in the Chinese Han population using ultra-low-coverage whole-genome sequence (ulcWGS). We identified 2,883 maternal trait-associated SNPs associated with 26 phenotypes, among which 99.5% were near established genome-wide association study (GWAS) loci. Further refinement delineated these SNPs to 442 unique trait-associated loci (TALs) predicated on linkage disequilibrium R2 > 0.8, revealing that 75.6% demonstrated pleiotropy and 50.9% were located in genes implicated in analogous phenotypes. Notably, we discovered 21 maternal SNPs associated with 35 neonatal phenotypes, including two SNPs associated with identical complications in both mothers and children. These findings underscore the importance of integrating ulcWGS data to enrich the discoveries derived from traditional PheWAS approaches.

SETA: Semantic-Aware Edge-Guided Token Augmentation for Domain Generalization.

Domain generalization (DG) aims to enhance the model robustness against domain shifts without accessing target domains. A prevalent category of methods for DG is data augmentation, which focuses on generating virtual samples to simulate domain shifts. However, existing augmentation techniques in DG are mainly tailored for convolutional neural networks (CNNs), with limited exploration in token-based architectures, i.e., vision transformer (ViT) and multi-layer perceptrons (MLP) models. In this paper, we study the impact of prior CNN-based augmentation methods on token-based models, revealing their performance is suboptimal due to the lack of incentivizing the model to learn holistic shape information. To tackle the issue, we propose the Semantic-aware Edge-guided Token Augmentation (SETA) method. SETA transforms token features by perturbing local edge cues while preserving global shape features, thereby enhancing the model learning of shape information. To further enhance the generalization ability of the model, we introduce two stylized variants of our method combined with two state-of-the-art (SOTA) style augmentation methods in DG. We provide a theoretical insight into our method, demonstrating its effectiveness in reducing the generalization risk bound. Comprehensive experiments on five benchmarks prove that our method achieves SOTA performances across various ViT and MLP architectures. Our code is available at https://github.com/lingeringlight/SETA.

Essential role of postoperative follow-up in the management of clear cell sarcoma.

Clear cell sarcoma (CCS) is a rare melanocytic soft tissue sarcoma known for its propensity to metastasize to the lymph nodes and typically has an unfavorable prognosis. Currently, surgical resection is the primary treatment for localized CCS, while radiotherapy and chemotherapy are preferred for metastatic cases. The roles of adjuvant chemotherapy, radiotherapy, and lymph node dissection are controversial. Although immunotherapy has emerged as a promising avenue in CCS treatment research, there are no established clinical standards for postoperative follow-up. This editorial discusses a recent article by Liu et al, with a focus on current diagnostic modalities, treatment approaches, and the challenging prognosis associated with CCS. Our aim is to underscore the importance of long-term patient follow-up in CCS management.

Dietary fatty acids and gallstone risk: insights from NHANES and Mendelian randomization analysis.

Background: Prior research suggests polyunsaturated fatty acids (PUFA) may prevent gallstones, but evidence on saturated fatty acids (SFA) and monounsaturated fatty acids (MUFA) is limited. This study aims to explore the associations between fatty acids and gallstones using a large sample of American population and Mendelian randomization (MR) methods. Methods: The cross-sectional study involved 6,629 participants from the National Health and Nutrition Examination Survey (NHANES) 2017-2020. Logistic regression and restricted cubic spline (RCS) analysis were conducted after stratifying by gender subgroups. Two-sample MR analysis was used to explore the causal relationship between fatty acids and gallstones without confounding factors. Results: In females, higher SFA intake was positively associated with gallstone risk, while higher intake of n-3 and n-6 PUFA was negatively associated. No significant associations were found in males. No nonlinear correlations were found in any group by RCS analysis. MR analysis indicated that SFA, n-3, and n-6 PUFA could reduce gallstone risk. Conclusion: The influence of dietary fatty acid composition on gallstone development differs by gender, providing insights into dietary prevention and treatment of gallstones.

From macroautophagy to mitophagy: Unveiling the hidden role of mitophagy in gastrointestinal disorders.

In this editorial, we comment on an article titled "Morphological and biochemical characteristics associated with autophagy in gastrointestinal diseases", which was published in a recent issue of the World Journal of Gastroenterology. We focused on the statement that "autophagy is closely related to the digestion, secretion, and regeneration of gastrointestinal cells". With advancing research, autophagy, and particularly the pivotal role of the macroautophagy in maintaining cellular equilibrium and stress response in the gastrointestinal system, has garnered extensive study. However, the significance of mitophagy, a unique selective autophagy pathway with ubiquitin-dependent and independent variants, should not be overlooked. In recent decades, mitophagy has been shown to be closely related to the occurrence and development of gastrointestinal diseases, especially inflammatory bowel disease, gastric cancer, and colorectal cancer. The interplay between mitophagy and mitochondrial quality control is crucial for elucidating disease mechanisms, as well as for the development of novel treatment strategies. Exploring the pathogenesis behind gastrointestinal diseases and providing individualized and efficient treatment for patients are subjects we have been exploring. This article reviews the potential mechanism of mitophagy in gastrointestinal diseases with the hope of providing new ideas for diagnosis and treatment.

Screening of colorectal cancer: Methods and strategies.

Colorectal cancer (CRC) has high incidence and mortality rates, and the emergence and application of CRC screening have helped us effectively control the occurrence and development of CRC. Currently, common international screening methods include tests based on feces and blood, and examination methods that allow for visualization, such as sigmoidoscopy and colonoscopy. Some methods have been widely used, whereas others such as multi-target stool RNA test are still being explored and developed, and are expected to become front-line screening methods for CRC in the future. The choice of screening method is affected by external conditions and the patients' situation, and the clinician must choose an appropriate strategy according to the actual situation and the patient's wishes. This article introduces various CRC screening methods and analyzes the factors relevant to the screening strategy.

Association between semen microbiome disorder and sperm DNA damage.

DNA fragmentation index (DFI), a new biomarker to diagnose male infertility, is closely associated with poor reproductive outcomes. Previous research reported that seminal microbiome correlated with sperm DNA integrity, suggesting that the microbiome may be one of the causes of DNA damage in sperm. However, it has not been elucidated how the microbiota exerts their effects. Here, we used a combination of 16S rRNA sequencing and untargeted metabolomics techniques to investigate the role of microbiota in high sperm DNA fragmentation index (HDFI). We report that increased specific microbial profiles contribute to high sperm DNA fragmentation, thus implicating the seminal microbiome as a new therapeutic target for HDFI patients. Additionally, we found that the amount of Lactobacillus species was altered: Lactobacillus iners was enriched in HDFI patients, shedding light on the potential influence of L. iners on male reproductive health. Finally, we also identified enrichment of the acetyl-CoA fermentation to butanoate II and purine nucleobase degradation I in the high sperm DNA fragmentation samples, suggesting that butanoate may be the target metabolite of sperm DNA damage. These findings provide valuable insights into the complex interplay between microbiota and sperm quality in HDFI patients, laying the foundation for further research and potential clinical interventions.IMPORTANCEThe DNA fragmentation index (DFI) is a measure of sperm DNA fragmentation. Because high sperm DNA fragmentation index (HDFI) has been strongly associated with adverse reproductive outcomes, this has been linked to the seminal microbiome. Because the number of current treatments for HDFI is limited and most of them have no clear efficacy, it is critical to understand how semen microbiome exerts their effects on sperm DNA. Here, we evaluated the semen microbiome and its metabolites in patients with high and low sperm DNA fragmentation. We found that increased specific microbial profiles contribute to high sperm DNA fragmentation. In particular, Lactobacillus iners was uniquely correlated with high sperm DNA fragmentation. Additionally, butanoate may be the target metabolite produced by the microbiome to damage sperm DNA. Our findings support the interaction between semen microbiome and sperm DNA damage and suggest that seminal microbiome should be a new therapeutic target for HDFI patients.

EMM-Promoted Pd-Catalyzed Solid State Intramolecular Heck-Type Cyclization/Boronation and Suzuki Couplings: Access to Functionalized Indolines.

EMM (electromagnetic mill)-promoted Pd-catalyzed solid state intramolecular Heck-type cyclization/boronation and Suzuki couplings are reported. Compared to previous mechanochemistry that constructed one chemical bond through a cross-coupling reaction, this strategy realizes cascade transformation along with multiple chemical bond formation. This conversion does not require organic solvents or additional heating, and it shows a good substrate scope and high functional group tolerance.

Conserved methylation signatures associate with the tumor immune microenvironment and immunotherapy response.

BACKGROUND: Aberrant DNA methylation is a major characteristic of cancer genomes. It remains unclear which biological processes determine epigenetic reprogramming and how these processes influence the variants in the cancer methylome, which can further impact cancer phenotypes. METHODS: We performed pairwise permutations of 381,900 loci in 569 paired DNA methylation profiles of cancer tissue and matched normal tissue from The Cancer Genome Atlas (TCGA) and defined conserved differentially methylated positions (DMPs) based on the resulting null distribution. Then, we derived independent methylation signatures from 2,465 cancer-only methylation profiles from the TCGA and 241 cell line-based methylation profiles from the Genomics of Drug Sensitivity in Cancer (GDSC) cohort using nonnegative matrix factorization (NMF). We correlated DNA methylation signatures with various clinical and biological features, including age, survival, cancer stage, tumor immune microenvironment factors, and immunotherapy response. We inferred the determinant genes of these methylation signatures by integrating genomic and transcriptomic data and evaluated the impact of these signatures on cancer phenotypes in independent bulk and single-cell RNA/methylome cohorts. RESULTS: We identified 7,364 differentially methylated positions (2,969 Hyper-DMPs and 4,395 Hypo-DMPs) in nine cancer types from the TCGA. We subsequently retrieved three highly conserved, independent methylation signatures (Hyper-MS1, Hypo-MS1, and Hypo-MS4) from cancer tissues and cell lines based on these Hyper and Hypo-DMPs. Our data suggested that Hypo-MS4 activity predicts poor survival and is associated with immunotherapy response and distant tumor metastasis, and Hypo-MS4 activity is related to TP53 mutation and FOXA1 binding specificity. In addition, we demonstrated a correlation between the activities of Hypo-MS4 in cancer cells and the fractions of regulatory CD4 + T cells with the expression levels of immunological genes in the tumor immune microenvironment. CONCLUSIONS: Our findings demonstrated that the methylation signatures of distinct biological processes are associated with immune activity in the cancer microenvironment and predict immunotherapy response.

Role of albumin-bilirubin score in non-malignant liver disease.

The albumin-bilirubin (ALBI) score, which was proposed to assess the prognosis of patients with hepatocellular carcinoma, has gradually been extended to other liver diseases in recent years, including primary biliary cholangitis, liver cirrhosis, hepatitis, liver transplantation, and liver injury. The ALBI score is often compared with classical scores such as the Child-Pugh and model for end-stage liver disease scores or other noninvasive prediction models. It is widely employed because of its immunity to subjective evaluation indicators and ease of obtaining detection indicators. An increasing number of studies have confirmed that it is highly accurate for assessing the prognosis of patients with chronic liver disease; additionally, it has demonstrated good predictive performance for outcomes beyond survival in patients with liver diseases, such as decompensation events. This article presents a review of the application of ALBI scores in various non-malignant liver diseases.

CDSKNNXMBD: a novel clustering framework for large-scale single-cell data based on a stable graph structure.

BACKGROUND: Accurate and efficient cell grouping is essential for analyzing single-cell transcriptome sequencing (scRNA-seq) data. However, the existing clustering techniques often struggle to provide timely and accurate cell type groupings when dealing with datasets with large-scale or imbalanced cell types. Therefore, there is a need for improved methods that can handle the increasing size of scRNA-seq datasets while maintaining high accuracy and efficiency. METHODS: We propose CDSKNNXMBD (Community Detection based on a Stable K-Nearest Neighbor Graph Structure), a novel single-cell clustering framework integrating partition clustering algorithm and community detection algorithm, which achieves accurate and fast cell type grouping by finding a stable graph structure. RESULTS: We evaluated the effectiveness of our approach by analyzing 15 tissues from the human fetal atlas. Compared to existing methods, CDSKNN effectively counteracts the high imbalance in single-cell data, enabling effective clustering. Furthermore, we conducted comparisons across multiple single-cell datasets from different studies and sequencing techniques. CDSKNN is of high applicability and robustness, and capable of balancing the complexities of across diverse types of data. Most importantly, CDSKNN exhibits higher operational efficiency on datasets at the million-cell scale, requiring an average of only 6.33 min for clustering 1.46 million single cells, saving 33.3% to 99% of running time compared to those of existing methods. CONCLUSIONS: The CDSKNN is a flexible, resilient, and promising clustering tool that is particularly suitable for clustering imbalanced data and demonstrates high efficiency on large-scale scRNA-seq datasets.

Epigenome-augmented eQTL-hotspots reveal genome-wide transcriptional programs in 36 human tissues.

Expression quantitative trait loci (eQTLs) are used to inform the mechanisms of transcriptional regulation in eukaryotic cells. However, the specificity of genome-wide eQTL identification is limited by stringent control for false discoveries. Here, we described a method based on the non-homogeneous Poisson process to identify 125 489 regions with highly frequent, multiple eQTL associations, or 'eQTL-hotspots', from the public database of 59 human tissues or cell types. We stratified the eQTL-hotspots into two classes with their distinct sequence and epigenomic characteristics. Based on these classifications, we developed a machine-learning model, E-SpotFinder, for augmented discovery of tissue- or cell-type-specific eQTL-hotspots. We applied this model to 36 tissues or cell types. Using augmented eQTL-hotspots, we recovered 655 402 eSNPs and reconstructed a comprehensive regulatory network of 2 725 380 cis-interactions among eQTL-hotspots. We further identified 52 012 modules representing transcriptional programs with unique functional backgrounds. In summary, our study provided a framework of epigenome-augmented eQTL analysis and thereby constructed comprehensive genome-wide networks of cis-regulations across diverse human tissues or cell types.

Learning Generalizable Models via Disentangling Spurious and Enhancing Potential Correlations.

Domain generalization (DG) intends to train a model on multiple source domains to ensure that it can generalize well to an arbitrary unseen target domain. The acquisition of domain-invariant representations is pivotal for DG as they possess the ability to capture the inherent semantic information of the data, mitigate the influence of domain shift, and enhance the generalization capability of the model. Adopting multiple perspectives, such as the sample and the feature, proves to be effective. The sample perspective facilitates data augmentation through data manipulation techniques, whereas the feature perspective enables the extraction of meaningful generalization features. In this paper, we focus on improving the generalization ability of the model by compelling it to acquire domain-invariant representations from both the sample and feature perspectives by disentangling spurious correlations and enhancing potential correlations. 1) From the sample perspective, we develop a frequency restriction module, guiding the model to focus on the relevant correlations between object features and labels, thereby disentangling spurious correlations. 2) From the feature perspective, the simple Tail Interaction module implicitly enhances potential correlations among all samples from all source domains, facilitating the acquisition of domain-invariant representations across multiple domains for the model. The experimental results show that Convolutional Neural Networks (CNNs) or Multi-Layer Perceptrons (MLPs) with a strong baseline embedded with these two modules can achieve superior results, e.g., an average accuracy of 92.30% on Digits-DG. Source code is available at https://github.com/RubyHoho/DGeneralization.

Alternative Splicing Reveals Acute Stress Response of Litopenaeus vannamei at High Alkalinity.

Alkalinity is regarded as one of the primary stressors for aquatic animals in saline-alkaline water. Alternative splicing (AS) can significantly increase the diversity of transcripts and play key roles in stress response; however, the studies on AS under alkalinity stress of crustaceans are still limited. In the present study, we devoted ourselves to the study of AS under acute alkalinity stress at control (50 mg/L) and treatment groups (350 mg/L) by RNA-seq in pacific white shrimp (Litopenaeus vannamei). We identified a total of 10,556 AS events from 4865 genes and 619 differential AS (DAS) events from 519 DAS genes in pacific white shrimp. Functional annotation showed that the DAS genes primarily involved in spliceosome. Five splicing factors (SFs), U2AF1, PUF60, CHERP, SR140 and SRSF2 were significantly up-regulated and promoted AS. Furthermore, alkalinity activated the Leukocyte transendothelial migration, mTOR signaling pathway and AMPK signaling pathway, which regulated MAPK1, EIF3B and IGFP-RP1 associated with these pathways. We also studied three SFs (HSFP1, SRSF2 and NHE-RF1), which underwent AS to form different transcript isoforms. The above results demonstrated that AS was a regulatory mechanism in pacific white shrimp in response to acute alkalinity stress. SFs played vital roles in AS of pacific white shrimp, such as HSFP1, SRSF2 and NHE-RF1. DAS genes were significantly modified in immunity of pacific white shrimp to cope with alkalinity stress. This is the first study on the response of AS to acute alkalinity stress, which provided scientific basis for AS mechanism of crustaceans response to alkalinity stress.

The role of amygdala-ventral pallidum pathway in depression-like behaviors in male mice.

The basolateral amygdala (BLA) appears to serve an important function in the pathophysiology of depression. Depressive symptoms, such as anhedonia are largely caused by dysfunction in the brain's reward system, in which the ventral pallidum (VP) participates in by controlling dopamine release. However, the role of the BLA-VP pathway in the development of depression remains poorly understood. To investigate this pathway, we employed the Chronic Unpredictable Mild Stress (CUMS) mouse model, in which we injected retroAAV expressing GFP-Cre into the VP and AAV expressing hM4Di-mCherry into the BLA. We then used CNO to activate the Designer Receptors Exclusively Activated by Designer Drugs (DREADDs) for all behavioral tests. The CUMS procedure resulted in significant depression symptoms such as decreased sucrose preference, limited weight gain, decreased immobile latency, and increased immobile time in the forced swim and tail suspension tests. Inhibition of the BLA-VP glutamatergic projections reversed these depression-like behaviors. We found that suppressing the BLA-VP circuitry had beneficial effects on CUMS-induced depression-like behaviors such as anorexia, anhedonia, and despair. Specifically, upon suppression of glutamatergic projections in the BLA-VP circuitry, these depression-like behaviors were significantly alleviated, which highlights the vital role of this circuitry in the development of depression. Furthermore, the beneficial effects of suppressing this circuitry seem to be associated with the brain's reward system, warranting further investigation.

Circulating tumor cells as potential prognostic biomarkers for early-stage pancreatic cancer: A systematic review and meta-analysis.

BACKGROUND: Pancreatic cancer is difficult to be diagnosed early clinically, while often leads to poor prognosis. If optimal personalized treatment plan can be provided to pancreatic cancer patient at an earlier stage, this can greatly improve overall survival (OS). Circulating tumor cells (CTCs) are a collective term for various types of tumor cells present in the peripheral blood (PB), which are formed by detachment during the development of solid tumor lesions. Most CTCs undergo apoptosis or are phagocytosed after entering the PB, whereas a few can escape and anchor at distal sites to develop metastasis, increasing the risk of death for patients with malignant tumors. AIM: To investigate the significance of CTCs in predicting the prognosis of early pancreatic cancer patients. METHODS: The PubMed, EMBASE, Web of Science, Cochrane Library, China National Knowledge Infrastructure, China Biology Medicine, and ChinaInfo databases were searched for articles published through December 2022. Studies were considered qualified if they included patients with early pancreatic cancer, analyzed the prognostic value of CTCs, and were full papers reported in English or Chinese. Researches were selected and assessed using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses protocol and the Newcastle-Ottawa Scale criteria. We used a funnel plot to assess publication bias. RESULTS: From 1595 publications, we identified eight eligible studies that collectively enrolled 355 patients with pancreatic cancer. Among these original studies, two were carried out in China; three in the United States; and one each in Italy, Spain, and Norway. All eight studies analyzed the relevance between CTCs and the prognosis of patients with early-stage pancreatic cancer after surgery. A meta-analysis showed that the patients that were positive pre-treatment or post-treatment for CTCs were associated with decreased OS [hazard ratio (HR) = 1.93, 95% confidence interval (CI): 1.197-3.126, P = 0.007] and decreased relapse-free/disease-free/progression-free survival (HR = 1.27, 95%CI: 1.137-1.419, P < 0.001) in early-stage pancreatic cancer. Additionally, the results suggest no statistically noticeable publication bias for overall, disease-free, progression-free, and recurrence-free survival. CONCLUSION: This pooled meta-analysis shows that CTCs, as biomarkers, can afford reliable prognostic information for patients with early-stage pancreatic cancer and help develop individualized treatment plans.

Organoids to Remodel SARS-CoV-2 Research: Updates, Limitations and Perspectives.

The novel COVID-19 pneumonia caused by the SARS-CoV-2 virus poses a significant threat to human health. Scientists have made significant efforts to control this virus, consequently leading to the development of novel research methods. Traditional animal and 2D cell line models might not be suitable for large-scale applications in SARS-CoV-2 research owing to their limitations. As an emerging modelling method, organoids have been applied in the study of various diseases. Their advantages include their ability to closely mirror human physiology, ease of cultivation, low cost, and high reliability; thus, they are considered to be a suitable choice to further the research on SARS-CoV-2. During the course of various studies, SARS-CoV-2 was shown to infect a variety of organoid models, exhibiting changes similar to those observed in humans. This review summarises the various organoid models used in SARS-CoV-2 research, revealing the molecular mechanisms of viral infection and exploring the drug screening tests and vaccine research that have relied on organoid models, hence illustrating the role of organoids in remodelling SARS-CoV-2 research.

Chinese Pedigree with Hereditary Gastrointestinal Stromal Tumors: A Case Report and Literature Review.

Familial gastrointestinal stromal tumor (GIST) is a rare autosomal dominant genetic disorder with only a few affected families reported to date. Here, we report a case of familial GISTs harboring a novel germline mutation within exon 18 of KIT. A 58-year-old male patient presented with gastric subepithelial lesions accompanied by cutaneous hyperpigmentation, which were subsequently diagnosed as multinodular GISTs. Endoscopic surgery was initially conducted to remove the larger lesions, and pathological examinations were then conducted for the diagnosis of GISTs. Family history revealed that some other family members had similar cutaneous pigmentations. Whole-exome sequencing was used to search for potential driver mutations, and Sanger sequencing was used for mutation validation. A novel primary driver mutation of KIT (c.G2485C, p.A829P) was detected in these hereditary GISTs, which has been reported in some targeted chemotherapy-resistant GISTs. Cell models were subsequently established for the rapid screening of candidate drugs and exploring potential mechanisms. This mutation could lead to cell proliferation and imatinib resistance by ligand-independent activation of KIT; however, ripretinib administration was identified as an applicable targeted therapy for this mutation. The mutation activated the JAK/STAT3 and MAPK/ERK pathways, which could be inhibited by ripretinib administration. To the best of our knowledge, this is the first report of the KIT-A829P mutation in familial GISTs, complementing the pathogenesis of familial GISTs and providing valuable information for the precision treatment of this disease.

Palladium-catalyzed cascade cyclization of allenamide with 2-iodoanilines to access functionalized indoloquinolines.

A novel and efficient palladium-catalyzed cascade cyclization to indoloquinoline derivatives in one pot has been developed by using allenamide derivatives and 2-iodoanilines as the key building blocks. The process involved two cyclizations: intramolecular cyclization/π-allylic substitution and intramolecular 6-endo Heck cyclization. Furthermore, dihydrobenzofuro[2,3-b]quinoline derivatives could also be achieved via this strategy using allenyl ethers instead of allenamides. The readily available substrates, mild conditions, high efficiency and step economy make this strategy a promising method in the synthesis of polycyclic motifs.

Exploring KRAS-mutant pancreatic ductal adenocarcinoma: a model validation study.

Introduction: Pancreatic ductal adenocarcinoma (PDAC) has the highest mortality rate among all solid tumors. Tumorigenesis is promoted by the oncogene KRAS, and KRAS mutations are prevalent in patients with PDAC. Therefore, a comprehensive understanding of the interactions between KRAS mutations and PDAC may expediate the development of therapeutic strategies for reversing the progression of malignant tumors. Our study aims at establishing and validating a prediction model of KRAS mutations in patients with PDAC based on survival analysis and mRNA expression. Methods: A total of 184 and 412 patients with PDAC from The Cancer Genome Atlas (TCGA) database and the International Cancer Genome Consortium (ICGC), respectively, were included in the study. Results: After tumor mutation profile and copy number variation (CNV) analyses, we established and validated a prediction model of KRAS mutations, based on survival analysis and mRNA expression, that contained seven genes: CSTF2, FAF2, KIF20B, AKR1A1, APOM, KRT6C, and CD70. We confirmed that the model has a good predictive ability for the prognosis of overall survival (OS) in patients with KRAS-mutated PDAC. Then, we analyzed differential biological pathways, especially the ferroptosis pathway, through principal component analysis, pathway enrichment analysis, Gene Ontology (GO) enrichment analysis, and gene set enrichment analysis (GSEA), with which patients were classified into low- or high-risk groups. Pathway enrichment results revealed enrichment in the cytokine-cytokine receptor interaction, metabolism of xenobiotics by cytochrome P450, and viral protein interaction with cytokine and cytokine receptor pathways. Most of the enriched pathways are metabolic pathways predominantly enriched by downregulated genes, suggesting numerous downregulated metabolic pathways in the high-risk group. Subsequent tumor immune infiltration analysis indicated that neutrophil infiltration, resting CD4 memory T cells, and resting natural killer (NK) cells correlated with the risk score. After verifying that the seven gene expression levels in different KRAS-mutated pancreatic cancer cell lines were similar to that in the model, we screened potential drugs related to the risk score. Discussion: This study established, analyzed, and validated a model for predicting the prognosis of PDAC based on risk stratification according to KRAS mutations, and identified differential pathways and highly effective drugs.