Xiaojing Guo

Tianjin Medical University Cancer Institute and Hospital

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Jia He

First Affiliated Hospital of Anhui Medical University

Xiaofei Ye

Second Military Medical University

Jinfang Xu

Second Military Medical University

Feng Gu

Tianjin Medical University Cancer Institute and Hospital

Li Fu

Qilu Hospital of Shandong University

Ronggang Lang

Tianjin Medical University Cancer Institute and Hospital

Xiaolong Qian

Tianjin Medical University Cancer Institute and Hospital

Yi Zheng

Shanghai University of Medicine and Health Sciences

Xinmin Zhang

Donald & Barbara Zucker School of Medicine at Hofstra/Northwell

Yu Fan

Jiangsu University

Cooperative Institutions

Tianjin Medical University Cancer Institute and Hospital

125

Shanghai Jiao Tong University

Chinese Academy of Medical Sciences & Peking Union Medical College

Tianjin Medical University

Chinese Academy of Sciences

Sun Yat-sen University

Second Military Medical University

Shanghai University of Traditional Chinese Medicine

Peking University

Qingdao University

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Triple‐negative breast cancer survival prediction using artificial intelligence through integrated analysis of tertiary lymphoid structures and tumor budding

Cancer (2024)

Xupeng Hou Xueyang Li Yunwei Han Hua Xu Yongjie Xie

Abstract Background Triple‐negative breast cancer (TNBC) is a highly heterogeneous and clinically aggressive disease. Accumulating evidence indicates that tertiary lymphoid structures (TLSs) and tumor budding (TB) are significantly correlated with the outcomes of patients who have TNBC, but no integrated TLS‐TB profile has been established to predict their survival. The objective of this study was to investigate the relationship between the TLS/TB ratio and clinical outcomes of patients with TNBC using artificial intelligence (AI)‐based analysis. Methods The infiltration levels of TLSs and TB were evaluated using hematoxylin and eosin staining, immunohistochemistry staining, and AI‐based analysis. Various cellular subtypes within TLS were determined by multiplex immunofluorescence. Subsequently, the authors established a nomogram model, conducted calibration curve analyses, and performed decision curve analyses using R software. Results In both the training and validation cohorts, the antitumor/protumor model established by the authors demonstrated a positive correlation between the TLS/TB index and the overall survival (OS) and relapse‐free survival (RFS) of patients with TNBC. Notably, patients who had a high percentage of CD8‐positive T cells, CD45RO‐positive T cells, or CD20‐positive B cells within the TLSs experienced improved OS and RFS. Furthermore, the authors developed a comprehensive TLS‐TB profile nomogram based on the TLS/TB index. This novel model outperformed the classical tumor‐lymph node‐metastasis staging system in predicting the OS and RFS of patients with TNBC. Conclusions A novel strategy for predicting the prognosis of patients with TNBC was established through integrated AI‐based analysis and a machine‐learning workflow. The TLS/TB index was identified as an independent prognostic factor for TNBC. This nomogram‐based TLS‐TB profile would help improve the accuracy of predicting the prognosis of patients who have TNBC.

Triple-negative breast cancer

Nomogram

Multiplex

10.1002/cncr.35261

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Citations (7)

[Promoter methylation status and protein expression of p14ARF gene in squamous cell carcinoma and adenocarcinoma of the lung].

Zhongguo feiai zazhi/Zhongguo fei'ai zazhi (2006)

Kaihua Tian Le-sheng Lin Zhaotong Jia Xiaojing Guo Lin Zhang

Recently, the p14 ARF gene has emerged as a new putative tumor suppressor gene, and the alteration of p14 ARF gene is closely related to development of multiple human tumors. The aberrant promoter methylation as a mechanism of inactivation of p14 ARF gene might participate in tumorigenesis. The aim of this study is to investigate promoter methylation status and protein expression of p14 ARF gene in pulmonary squamous cell carcinoma and adenocarcinoma, and to value the role of p14 ARF promoter methylation in carcinogenesis of non-small cell lung cancer.Promoter methylation status and protein expression of p14 ARF gene were analyzed in 40 cases of pulmonary squamous cell carcinoma and adenocarcinoma by methylation specific polymerase chain reaction (MSP), restriction enzyme-related polymerase chain reaction (RE-PCR) and immunohistochemistry (IHC).The positive rate of p14 ARF promoter methylation in tumor tissues and normal tissues adjacent to cancer was 17.5% (7/40) and 2.5% (1/40) respectively (P= 0.025 ). The results of RE-PCR were consistent with the above. The positive rate of p14 ARF protein in tumor tissues was significantly lower than that in normal tissues adjacent to cancer (P=0.003). Promoter methylation and protein expression of p14 ARF gene showed a significantly negative correlation (r=-0.56, P= 0.001 ), and both of them did not correlate statistically with the clinicopathologic characteristics of patients such as histological classification, TNM stages, differentiation grade and lymph node involvement.Promoter methylation is a crucial mechanism of inactivation of p14 ARF gene. Promoter methylation of p14 ARF gene might be involved in carcinogenesis of non-small cell lung cancer, and it is an early event in development process of non-small cell lung cancer.

p14arf

Bisulfite sequencing

10.3779/j.issn.1009-3419.2006.01.11

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Citations (6)

Combination of Bacillus and Low Fertigation Input Promoted the Growth and Productivity of Chinese Cabbage and Enriched Beneficial Rhizosphere Bacteria Lechevalieria

Biology (2023)

Shichang Zhang Yulu Zhang Xiaojing Guo Ming Luo Shidong Li

Long-term overfertilization increases soil salinity and disease occurrence and reduces crop yield. Integrated application of microbial agents with low fertigation input might be a sustainable and cost-effective strategy. Herein, the promoting effects of

Fertigation

10.3390/biology12081130

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Citations (3)

Bone metastases of prostate cancer: Molecular mechanisms, targeted diagnosis and targeted therapy (Review)

Oncology Reports (2025)

Xiaojing Guo Shaojun Li

Targeted Therapy

10.3892/or.2025.8879

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Citations (0)

Tucidinostat Plus Exemestane as a Neoadjuvant in Early-Stage, Hormone Receptor-Positive, Human Epidermal Growth Factor Receptor 2-Negative Breast Cancer

The Oncologist (2024)

Hongmeng Zhao Dan Li Qian Li Bin Zhang Chunhua Xiao

Abstract Background To assess the efficacy and safety of tucidinostat plus exemestane as a neoadjuvant strategy in early-stage breast cancer. Methods This prospective, open-label, single-arm phase II trial enrolled patients with stage II-III breast cancer with hormone receptor-positive and human epidermal growth factor receptor 2 (HER2)-negative. Eligible patients received tucidinostat plus exemestane, and then breast-conserving surgery (BCS) or modified radical mastectomy. Results Among 20 enrolled patients, 3 of them achieved preoperative endocrine prognostic index (PEPI) score of 0. Additionally, complete cell cycle arrest was observed in 7, radiologic objective response rate in 10, and disease control rate in 20 patients, pathological complete response in 1 patient, and 5 patients performed BCS. Ki67 suppression from baseline to surgery was observed in 17 of patients, with the Ki67 change ratio of −73.5%. Treatment-emergent adverse event included neutropenia, leukopenia, thrombocytopenia, lymphopenia, hypoalbuminemia, aspartate aminotransferase elevation, glutamyl transpeptidase elevation, anemia, and alanine aminotransferase elevation. Conclusions Despite the rate of PEPI score 0 was not high, tucidinostat plus exemestane as a neoadjuvant therapy might be well tolerated and showed promising clinical responses in patients with early hormone receptor-positive, HER2-negative breast cancer. To clarify the safety and efficacy of this strategy, further investigation is warranted. Clinical Trial Registration ChiCTR2100046678.

Exemestane

Leukopenia

Neoadjuvant Therapy

10.1093/oncolo/oyae033

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Citations (2)

Six polymorphisms in the lncRNA H19 gene and the risk of cancer: a systematic review and meta-analysis

BMC Cancer (2023)

Maoquan Yang Mingwei Zhang Qiong Wang Xiaojing Guo Peizhen Geng

Abstract Background Numerous studies have demonstrated long noncoding RNA (lncRNA) play an important role in the occurrence and progression of cancer, and single nucleotide polymorphisms (SNPs) located in lncRNA are considered to affect cancer suspensibility. Herein, a meta-analysis was carried out to better assess the relationship of H19 polymorphisms and cancer susceptibility. Methods A literature search was conducted through using PubMed, EMBASE, and Web of Science databases to obtain relevant publications before Aug 23, 2022. The reference lists of the retrieved studies were also investigated to identify additional relevant articles. The pooled odds ratios (ORs) with 95% confidence intervals (CIs) were calculated to appraise the risk of various cancers. Results There appeared to be a remarkable correlation between the rs2107425 variation and decreased cancer risk among Caucasians. Nevertheless, the rs217727 polymorphism was significantly associated with an increased risk of lung cancer, hepatocellular carcinoma and oral squamous cell carcinoma. Also, we found a significant correlation between the rs2839698 polymorphism and increased cancer risk among Asians, gastric cancer, hepatocellular carcinoma, hospital-based control and larger simple size subgroups, respectively. Similarly, the rs3741219 mutation was notably related to cancer risk in higher quality score. As for rs3024270 polymorphism, the homozygous model was markedly linked to cancer risk in overall analysis and population-based controls. There was no significant association between the rs3741216 polymorphism and cancer risk. Conclusion H19 rs2839698 and rs3024270 were closely associated with overall cancer risk. H19 rs2107425 was related to lower cancer risk among Caucasians, while the rs2839698 was related to increased cancer risk among Asians. Our results supported that H19 SNPs were significantly correlated with cancer risk.

Surgical oncology

Liver Cancer

10.1186/s12885-023-11164-y

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Citations (4)

The Expression of Cripto-1 and Its Prognostic Significance in Breast Cancer

Clinical Oncology and Cancer Research (2010)

Ting Lei Xiaojing Guo Xinxin Wang Yu Fan Ronggang Lang

10.3969/j.issn.1000-8179.2010.12.002

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Citations (0)

Tumor vascular permeabilization using localized mild hyperthermia to improve macromolecule transport

Nanomedicine Nanotechnology Biology and Medicine (2013)

Dickson Kirui Eugene J. Koay Xiaojing Guo Vittorio Cristini Haifa Shen

10.1016/j.nano.2013.11.001

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Citations (65)

Development of a CRISPR‐Cas9 Based Luciferase Turn‐On System as Nonhomologous End Joining Pathway Reporter

ChemBioChem (2021)

Yi Wang Yanjie Zhao Weijun Su Xiaojing Guo Shuai Li

There is a need of a non-homologous end joining (NHEJ) pathway reporter system that facilitates screening and discovery of NHEJ chemical inhibitors. In this study, we developed a CRISPR-Cas9 based luciferase turn-on system as a NHEJ pathway reporter. By substituting nucleotide 205C with ATC, we introduced a reading-frame shift and a pre-stop codon into the luciferase coding region and thereby generated a bioluminescent signal mute HEK293T reporter cell line. Then, a CRISPR-Cas9 plasmid expressing a guide RNA targeting luciferase coding region was introduced into the reporter cell line to generate NHEJ-associated indel to restore the reading frame and subsequently turn on the bioluminescent signal. We observed over three-thousand fold increase in signal after CRISPR-Cas9 vector transfection. Different known chemical inhibitors of the NHEJ pathway, such as NU7441, KU0060648, and KU55933, could significantly inhibit the bioluminescent signal generated by CRISPR-Cas9 targeting. In addition, we validated our system by high throughput sequencing.

Turn (biochemistry)

Luciferases

Non-homologous end joining

10.1002/cbic.202100128

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Citations (2)

Identification of immunological characteristics and cuproptosis-related molecular clusters in Rheumatoid arthritis

International Immunopharmacology (2023)

Aihua Wang Wei Liu Yue Jin Bowen Wei Yihua Fan

10.1016/j.intimp.2023.110804

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Citations (3)