Precision Clinical Medicine最新文献

{"title":"Loss of chromosome 9p21 is associated with a poor prognosis in adenosquamous carcinoma of the pancreas","authors":"Yina Jiang, YinYing Wu, Liwen Zhang, Yan Wang, Guiping Xu, Yuan Deng, Liang Han, Enxiao Li, Qingyong Ma, Mian Xu, Zheng Wu, Zheng Wang","doi":"10.1093/pcmedi/pbad030","DOIUrl":"https://doi.org/10.1093/pcmedi/pbad030","url":null,"abstract":"Abstract Adenosquamous carcinoma of the pancreas (ASCP) is a rare histological subtype of pancreatic cancer with a poor prognosis and a high metastasis rate. However, little is known about its genomic landscape and prognostic biomarkers. Forty-eight ASCP specimens and 98 pancreatic ductal adenocarcinoma (PDAC) tumours pecimens were sequenced to explore the genomic landscape and prognostic biomarkers. The homozygous deletion of the 9p21.3 region (including CDKN2A, CDKN2B, and MTAP) (9p21 loss) occurred in both ASCP and PDAC, and a higher frequency of 9p21 loss was observed in ASCP (12.5% vs. 2.0%, p = 0.022). Notably, 9p21 loss was significantly associated with poor disease-free survival (DFS) in ASCP patients (mDFS = 4.17 vs. 7.33 months, HR = 3.70, p = 0.009). The most common gene alterations in patients with ASCP were KRAS (96%), TP53 (81%), CDKN2A (42%), SMAD4 (21%), CDKN2B (13%), and FAT3 (13%). The mutation rates of ACVR2A (6.25% vs. 0), FANCA (6.25% vs. 0), RBM10 (6.25% vs. 0), and SPTA1 (8.33% vs. 1.02%) were significantly higher in ASCP than in PDAC. In conclusion, we have comprehensively described the genomic landscape of the largest cohort of ASCP patients to date and highlight that 9p21 loss may be a promising prognostic biomarker for ASCP, which provides a molecular basis for prognosis prediction and new therapeutic strategies for ASCP.","PeriodicalId":33608,"journal":{"name":"Precision Clinical Medicine","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135541640","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A pairwise radiomics algorithm - lesion pair relation estimation (PRE) model for distinguishing multiple primary lung cancer (MPLC) from intrapulmonary metastasis (IPM)","authors":"Ting-Fei Chen, Lei Yang, Hai-Bin Chen, Zhi-Guo Zhou, Zhen-Tian Wu, Hong-He Luo, Qiong Li, Ying Zhu","doi":"10.1093/pcmedi/pbad029","DOIUrl":"https://doi.org/10.1093/pcmedi/pbad029","url":null,"abstract":"Abstract Background Distinguishing multiple primary lung cancer (MPLC) from intrapulmonary metastasis (IPM) is critical for their disparate treatment strategy and prognosis. This study aimed to establish a non-invasive model to make the differentiation pre-operatively. Methods We retrospectively studied 168 patients with multiple lung cancers (307 pairs of lesions) including 118 cases for modeling and internal validation, and 50 cases for independent external validation. Radiomic features on computed tomography (CT) were extracted to calculate the absolute deviation of paired lesions. Features were then selected by correlation coefficients and random forest classifier five-fold cross-validation, based on which the lesion pair relation estimation (PRE) model was developed. A major voting strategy was used to decide diagnosis for cases with multiple pairs of lesions. Cases from another institute were included as the external validation set for the PRE model to compete with two experienced clinicians. Results Seven radiomic features were selected for the PRE model construction. With major voting strategy, the mean area under receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity of the training vs. internal validation vs. external validation cohort to distinguish MPLC were 0.983 vs. 0.844 vs. 0.793, 0.942 vs. 0.846 vs. 0.760, 0.905 vs. 0.728 vs. 0.727, and 0.962 vs. 0.910 vs. 0.769, respectively. AUCs of the two clinicians were 0.619 and 0.580. Conclusions The CT radiomic feature-based lesion PRE model is potentially an accurate diagnostic tool for the differentiation of MPLC and IPM, which could help with clinical decision making.","PeriodicalId":33608,"journal":{"name":"Precision Clinical Medicine","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136069325","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Investigating the gut microbiota's influence on psoriasis and psoriatic arthritis risk: a Mendelian randomization analysis.","authors":"Nianzhou Yu, Jiayi Wang, Yuancheng Liu, Yeye Guo","doi":"10.1093/pcmedi/pbad023","DOIUrl":"https://doi.org/10.1093/pcmedi/pbad023","url":null,"abstract":"<p><strong>Background: </strong>Numerous investigations have revealed the interplay between gut microbiota (GM) and psoriasis (Ps) and psoriatic arthritis (PsA). However, the causal relationship between them remains unknown.</p><p><strong>Methods: </strong>We curated a collection of genetic variants (<i>P</i> < 1 × 10^-5) associated with GM (<i>n</i> = 18 340) derived from the MiBioGen study. To explore the intricate relationship between GM and Ps as well as PsA, we harnessed the comprehensive resources of the FinnGen database, encompassing a vast cohort of individuals, including 4510 Ps cases and 212 242 controls and 1637 PsA cases and 212 242 controls. Mendelian randomization (MR) was used, including an inverse variance weighting method, followed by a sensitivity analysis to verify the robustness of the results.</p><p><strong>Results: </strong>For Ps, some bacterial taxa, including <i>Lactococcus, Ruminiclostridium 5</i>, and <i>Eubacterium fissicatena</i>, were identified as risk factors; but <i>Odoribacter</i> demonstrated a protective effect against Ps. In the case of PsA, <i>Lactococcus, Verrucomicrobiales, Akkermansia, Coprococcus 1</i>, and <i>Verrucomicrobiaceae</i> were identified as risk factors; <i>Odoribacter</i> and <i>Rikenellaceae</i> exhibited a protective effect against the development of PsA.</p><p><strong>Conclusion: </strong>Our study establishes a causal link between the GM and Ps and PsA. These findings provide insights into the underlying mechanisms and suggest potential therapeutic targets.</p>","PeriodicalId":33608,"journal":{"name":"Precision Clinical Medicine","volume":null,"pages":null},"PeriodicalIF":5.3,"publicationDate":"2023-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10680138/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138463075","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Trajectory of fecal lactoferrin for predicting prognosis in ulcerative colitis.","authors":"Rirong Chen, Li Li, Yizhe Tie, Minhu Chen, Shenghong Zhang","doi":"10.1093/pcmedi/pbad022","DOIUrl":"10.1093/pcmedi/pbad022","url":null,"abstract":"<p><strong>Objectives: </strong>To investigate the characteristics and prognostic value of fecal lactoferrin trajectories in ulcerative colitis (UC).</p><p><strong>Methods: </strong>This study used data from the UNIFI trial (ClinicalTrials.gov, NCT02407236) and included patients who received ustekinumab during induction for trajectory modeling (<i>n</i> = 637). Patients who received ustekinumab during maintenance therapy were used for 1-year outcome analyses (<i>n</i> = 403). The levels of fecal lactoferrin, fecal calprotectin, and serum C-reactive protein were measured at weeks 0, 2, 4, and 8. The trajectories of these biomarkers were developed using a latent class growth mixed model.</p><p><strong>Results: </strong>The trajectories of fecal lactoferrin, fecal calprotectin, and serum C-reactive protein were distinct, but all were associated with prior exposure to anti-tumor necrosis factor agents and vedolizumab. Furthermore, the fecal lactoferrin trajectory was the most valuable predictor of endoscopic, clinical, and histological remission. Compared to the high/moderate-rapid decrease trajectory group, the moderate-slow decrease, high-slow decrease, and high-stable groups had adjusted odds ratios (95% confidence interval) of 0.38 (0.18, 0.78; <i>P </i>= 0.010), 0.47 (0.23, 0.93; <i>P </i>= 0.032), and 0.33 (0.17, 0.63; <i>P</i> = 0.001), respectively, of 1-year endoscopic remission. Patients with high/moderate-rapid decrease trajectories also had the highest likelihood of achieving clinical and histological remission. Finally, we developed a patient-stratification scheme based on fecal lactoferrin trajectories and concentrations. Patients with good, moderate, and poor prognoses in the scheme had a distinct probability of achieving 1-year endoscopic remission (52.7%, 30.9%, and 12.8%, respectively).</p><p><strong>Conclusions: </strong>The trajectory of fecal lactoferrin is a valuable prognostic factor for 1-year remission in UC.</p>","PeriodicalId":33608,"journal":{"name":"Precision Clinical Medicine","volume":null,"pages":null},"PeriodicalIF":5.3,"publicationDate":"2023-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10680133/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75218419","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of apolipoprotein A1 on tumor immune microenvironment, clinical prognosis and genomic landscape in hepatocellular carcinoma.","authors":"Ying Wang, Shipeng Chen, Xiao Xiao, Fan Yang, Jinhan Wang, Hui Zong, Yuzhen Gao, Chenjun Huang, Xuewen Xu, Meng Fang, Xiaoyan Zhang, Chunfang Gao","doi":"10.1093/pcmedi/pbad021","DOIUrl":"https://doi.org/10.1093/pcmedi/pbad021","url":null,"abstract":"<p><strong>Background: </strong>Current knowledge on apolipoprotein A1 (APOA1) in hepatocellular carcinoma (HCC) is fragmented and even contradictory. Multi-dimensional analyses are required to comprehensively elucidate its value and underlying mechanism.</p><p><strong>Methods: </strong>We collected 49 RNA-seq datasets, 40 cell line types data and 70 scRNA pan-cancer datasets public available, including 17 HCC datasets (1754 tumor samples), and enrolled 73 pairs of HCC tissue and 516 blood samples independently from our clinics. APOA1 impacting on the HCC tumor microenvironment (TME) was analyzed using intensive data mining. Methylation sequencing, flow cytometry, quantitative PCR, western blot, immunohistochemistry and clinical chemistry assays were conducted for wet experimental investigation.</p><p><strong>Results: </strong>The APOA1 ontology fingerprint indicated that it played various crucial biological roles in HCC, primarily involved in cholesterol efflux. Consistent findings at histology, serology, and clinical follow-up revealed that high APOA1 was a good prognosis indicator of HCC. Hypermethylation in the APOA1 promoter region was found in clinical samples which is in accordance with the reduction of APOA1 in HCC. The cell cycle, DNA replication, mismatch repair pathways, and tumor cell proliferation were less observed in the HCC APOA1^high subgroup. The favorable immunoregulatory abilities of APOA1 showed interesting findings: a positive correlation between APOA1 and anti-tumor immune cells (NK, CD8⁺ T cells) and a negative association with immune cells exerting immunosuppressive effects, including M2 macrophages.</p><p><strong>Conclusion: </strong>This is an integrative multidimensional exploration of APOA1 using bioinformatics and experiments. Both the prognostic value and anti-tumor effects based on APOA1 panoramic exploration in the HCC TME demonstrate a new potential clinical target for HCC assessment and intervention in the future.</p>","PeriodicalId":33608,"journal":{"name":"Precision Clinical Medicine","volume":null,"pages":null},"PeriodicalIF":5.3,"publicationDate":"2023-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10680024/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138463074","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Artificial intelligence-based non-invasive tumor segmentation, grade stratification and prognosis prediction for clear-cell renal-cell carcinoma.","authors":"Siteng Chen, Dandan Song, Lei Chen, Tuanjie Guo, Beibei Jiang, Aie Liu, Xianpan Pan, Tao Wang, Heting Tang, Guihua Chen, Zhong Xue, Xiang Wang, Ning Zhang, Junhua Zheng","doi":"10.1093/pcmedi/pbad019","DOIUrl":"10.1093/pcmedi/pbad019","url":null,"abstract":"Abstract Due to the complicated histopathological characteristics of clear-cell renal-cell carcinoma (ccRCC), non-invasive prognosis before operative treatment is crucial in selecting the appropriate treatment. A total of 126 345 computerized tomography (CT) images from four independent patient cohorts were included for analysis in this study. We propose a V Bottleneck multi-resolution and focus-organ network (VB-MrFo-Net) using a cascade framework for deep learning analysis. The VB-MrFo-Net achieved better performance than VB-Net in tumor segmentation, with a Dice score of 0.87. The nuclear-grade prediction model performed best in the logistic regression classifier, with area under curve values from 0.782 to 0.746. Survival analysis revealed that our prediction model could significantly distinguish patients with high survival risk, with a hazard ratio (HR) of 2.49 [95% confidence interval (CI): 1.13–5.45, P = 0.023] in the General cohort. Excellent performance had also been verified in the Cancer Genome Atlas cohort, the Clinical Proteomic Tumor Analysis Consortium cohort, and the Kidney Tumor Segmentation Challenge cohort, with HRs of 2.77 (95%CI: 1.58–4.84, P = 0.0019), 3.83 (95%CI: 1.22–11.96, P = 0.029), and 2.80 (95%CI: 1.05–7.47, P = 0.025), respectively. In conclusion, we propose a novel VB-MrFo-Net for the renal tumor segmentation and automatic diagnosis of ccRCC. The risk stratification model could accurately distinguish patients with high tumor grade and high survival risk based on non-invasive CT images before surgical treatments, which could provide practical advice for deciding treatment options.","PeriodicalId":33608,"journal":{"name":"Precision Clinical Medicine","volume":null,"pages":null},"PeriodicalIF":5.3,"publicationDate":"2023-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10680020/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76120002","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advances in diagnosis and prediction for aggression of pure solid T1 lung cancer.","authors":"Junhao Mu, Jing Huang, Min Ao, Weiyi Li, Li Jiang, Li Yang","doi":"10.1093/pcmedi/pbad020","DOIUrl":"https://doi.org/10.1093/pcmedi/pbad020","url":null,"abstract":"<p><p>A growing number of early-stage lung cancers presenting as malignant pulmonary nodules have been diagnosed because of the increased adoption of low-dose spiral computed tomography. But pure solid T1 lung cancer with ≤3 cm in the greatest dimension is not always at an early stage, despite its small size. This type of cancer can be highly aggressive and is associated with pathological involvement, metastasis, postoperative relapse, and even death. However, it is easily misdiagnosed or delay diagnosed in clinics and thus poses a serious threat to human health. The percentage of nodal or extrathoracic metastases has been reported to be >20% in T1 lung cancer. As such, understanding and identifying the aggressive characteristics of pure solid T1 lung cancer is crucial for prevention, diagnosis, and therapeutic strategies, and beneficial to improving the prognosis. With the widespread of lung cancer screening, these highly invasive pure solid T1 lung cancer will become the main advanced lung cancer in future. However, there is limited information regarding precision medicine on how to identify these \"early-stage\" aggressive lung cancers. To provide clinicians with new insights into early recognition and intervention of the highly invasive pure solid T1 lung cancer, this review summarizes its clinical characteristics, imaging, pathology, gene alterations, immune microenvironment, multi-omics, and current techniques for diagnosis and prediction.</p>","PeriodicalId":33608,"journal":{"name":"Precision Clinical Medicine","volume":null,"pages":null},"PeriodicalIF":5.3,"publicationDate":"2023-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10680022/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138463073","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The latest breakthrough on genetic characteristics of inflammatory bowel disease in Chinese and other East Asian ancestries.","authors":"Han Gao,&nbsp;Zhanju Liu","doi":"10.1093/pcmedi/pbad017","DOIUrl":"https://doi.org/10.1093/pcmedi/pbad017","url":null,"abstract":"<p><p>Inflammatory bowel diseases (IBDs) are complex chronic disorders of the gastrointestinal tract with the following two subtypes: Crohn's disease and ulcerative colitis. Disease presentation and progression within and across IBDs, especially Crohn's disease, are highly heterogeneous in the location, severity of inflammation, intestinal stenosis and obstruction, and extraintestinal manifestations. Clinical classifications fail to accurately predict the disease course and response to therapies. To date, most IBD genetic associations are derived from individuals of European ancestries, leading to a limitation of the discovery and application of IBD genetics in the rest of the world populations. In this mini-review, we summarize the latest progress of genome-wide association studies of IBD across global ancestries especially the Chinese population, the similarities and differences in genetic architecture between European and East Asian ancestries, as well as, the clinical significances relevant to IBD genetic study.</p>","PeriodicalId":33608,"journal":{"name":"Precision Clinical Medicine","volume":null,"pages":null},"PeriodicalIF":5.3,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/ab/8d/pbad017.PMC10346401.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9828935","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Circulating biomarkers in perioperative management of cancer patients.","authors":"Qiyuan Huang, Ruihao Zhou, Xuechao Hao, Weiyi Zhang, Guo Chen, Tao Zhu","doi":"10.1093/pcmedi/pbad018","DOIUrl":"10.1093/pcmedi/pbad018","url":null,"abstract":"<p><p>Owing to the advances in surgical technology, most solid tumours can be controlled by surgical excision. The priority should be tumour control, while some routine perioperative management might influence cancer progression in an unnoticed way. Moreover, it is increasingly recognized that effective perioperative management should include techniques to improve postoperative outcomes. These influences are elucidated by the different functions of circulating biomarkers in cancer patients. Here, circulating biomarkers with two types of clinical functions were reviewed: (i) circulating biomarkers for cancer progression monitoring, for instance, those related to cancer cell malignancy, tumour microenvironment formation, and early metastasis, and (ii) circulating biomarkers with relevance to postoperative outcomes, including systemic inflammation, immunosuppression, cognitive dysfunction, and pain management. This review aimed to provide new perspectives for the perioperative management of patients with cancer and highlight the potential clinical translation value of circulating biomarkers in improving outcomes.</p>","PeriodicalId":33608,"journal":{"name":"Precision Clinical Medicine","volume":null,"pages":null},"PeriodicalIF":5.3,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10634636/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78263519","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Construction of regulatory network for alopecia areata progression and identification of immune monitoring genes based on multiple machine-learning algorithms.","authors":"Jiachao Xiong,&nbsp;Guodong Chen,&nbsp;Zhixiao Liu,&nbsp;Xuemei Wu,&nbsp;Sha Xu,&nbsp;Jun Xiong,&nbsp;Shizhao Ji,&nbsp;Minjuan Wu","doi":"10.1093/pcmedi/pbad009","DOIUrl":"https://doi.org/10.1093/pcmedi/pbad009","url":null,"abstract":"<p><strong>Objectives: </strong>Alopecia areata (AA) is an autoimmune-related non-cicatricial alopecia, with complete alopecia (AT) or generalized alopecia (AU) as severe forms of AA. However, there are limitations in early identification of AA, and intervention of AA patients who may progress to severe AA will help to improve the incidence rate and prognosis of severe AA.</p><p><strong>Methods: </strong>We obtained two AA-related datasets from the gene expression omnibus database, identified the differentially expressed genes (DEGs), and identified the module genes most related to severe AA through weighted gene co-expression network analysis. Functional enrichment analysis, construction of a protein-protein interaction network and competing endogenous RNA network, and immune cell infiltration analysis were performed to clarify the underlying biological mechanisms of severe AA. Subsequently, pivotal immune monitoring genes (IMGs) were screened through multiple machine-learning algorithms, and the diagnostic effectiveness of the pivotal IMGs was validated by receiver operating characteristic.</p><p><strong>Results: </strong>A total of 150 severe AA-related DEGs were identified; the upregulated DEGs were mainly enriched in immune response, while the downregulated DEGs were mainly enriched in pathways related to hair cycle and skin development. Four IMGs (LGR5, SHISA2, HOXC13, and S100A3) with good diagnostic efficiency were obtained. As an important gene of hair follicle stem cells stemness, we verified <i>in vivo</i> that LGR5 downregulation may be an important link leading to severe AA.</p><p><strong>Conclusion: </strong>Our findings provide a comprehensive understanding of the pathogenesis and underlying biological processes in patients with AA, and identification of four potential IMGs, which is helpful for the early diagnosis of severe AA.</p>","PeriodicalId":33608,"journal":{"name":"Precision Clinical Medicine","volume":null,"pages":null},"PeriodicalIF":5.3,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/7e/f9/pbad009.PMC10268596.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9716786","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}