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Deep learning framework for comprehensive molecular and prognostic stratifications of triple-negative breast cancer

Fundamental Research 2024年第3期4卷 678-689页

作者： Shen Zhao Chao-Yang Yan Hong Lv Jing-Cheng Yang Chao You Zi-Ang Li Ding Ma Yi Xiao Jia Hu Wen-Tao Yang Yi-Zhou Jiang Jun Xu Zhi-Ming Shao Key Laboratory of Breast Cancer in Shanghai Department of Breast SurgeryFudan University Shanghai Cancer CenterShanghai 200032China Institute for AI in Medicine School of Artificial IntelligenceNanjing University of Information Science and TechnologyNanjing 210044China Department of Pathology Fudan University Shanghai Cancer CenterShanghai 200032China Greater Bay Area Institute of Precision Medicine Guangzhou 511466China Department of Radiology Fudan University Shanghai Cancer CenterShanghai 200032China

Triple-negative breast cancer(TNBC)is the most challenging breast cancer subtype.Molecular stratification and target therapy bring clinical benefit for TNBC patients,but it is difficult to implement comprehensive molecular testing in clinical practice.Here,using our multi-omics TNBC cohort(N=425),a deep learning-based framework was devised and validated for comprehensive predictions of molecular features,subtypes and prognosis from pathological whole slide images.The framework first incorporated a neural network to decompose the tissue on WSIs,followed by a second one which was trained based on certain tissue types for predicting different targets.Multi-omics molecular features were analyzed including somatic mutations,copy number alterations,germline mutations,biological pathway activities,metabolomics features and immunotherapy biomarkers.It was shown that the molecular features with therapeutic implications can be predicted including the somatic PIK3CA mutation,germline BRCA2 mutation and PD-L1 protein expression(area under the curve[AUC]:0.78,0.79 and 0.74 respectively).The molecular subtypes of TNBC can be identified(AUC:0.84,0.85,0.93 and 0.73 for the basal-like immune-suppressed,immunomodulatory,luminal androgen receptor,and mesenchymal-like subtypes respectively)and their distinctive morphological patterns were revealed,which provided novel insights into the heterogeneity of TNBC.A neural network integrating image features and clinical covariates stratified patients into groups with different survival outcomes(log-rank Ppatient population.For potential clinical translation,we built a novel online platform,where we modularized and deployed our framework along with the validated models.It can realize real-time one-stop prediction for new cases.In summary,using only pathological WSIs,our proposed framework can enable comprehensive stratifications of TNBC

关键词： Triple-negative breast cancer Deep learning Digital pathology patient stratification Online platform

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patient-specific monocyte-derived microglia as a screening tool for neurodegenerative diseases

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Neural Regeneration Research 2023年第5期18卷 955-958页

作者： Hazel Quek Anthony R.White Mental Health and Neuroscience QIMR Berghofer Medical Research Institute School of Biomedical Science The University of QueenslandBrisbaneQLDAustralia

Microglia, the main driver of neuroinflammation, play a central role in the initiation and exacerbation of various neurodegenerative diseases and are now considered a promising therapeutic target. Previous studies on in vitro human microglia and in vivo rodent models lacked scalability, consistency, or physiological relevance, which deterred successful therapeutic outcomes for the past decade. Here we review human blood monocyte-derived microglia-like cells as a robust and consistent approach to generate a patient-specific microglia-like model that can be used in extensive cohort studies for drug testing. We will highlight the strength and applicability of human blood monocyte-derived microglia-like cells to increase translational outcomes by reviewing the advantages of human blood monocyte-derived microglia-like cells in addressing patient heterogeneity and stratification, the basis of personalized medicine.

关键词： human in vitro microglia models neurodegeneration neuroinflammation patient heterogeneity patient stratification peripheral blood monocyte-derived microglia-like cells therapeutic target transdifferentiation translational outcomes

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patient-derived xenograft platform of OSCC： a renewable human bio-bank for preclinical cancer research and a new co-clinical model for treatment optimization

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Frontiers of Medicine 2016年第1期10卷 104-110页

作者： Shuyang Sun Zhiyuan Zhang Department of Oral and Maxillofacial-Head Neck Oncology Ninth People's Hospital Shanghai Jiao Tong University School of Medicine'Shanghai Key Laboratory of Stomatology Shanghai 200011 China

Advances in next-generation sequencing and bioinformatics have begun to reveal the complex genetic landscape in human cancer genomes, including oral squamous cell carcinoma （OSCC）. Sophisticated preclinical models that fully represent intra- and inter-tumoral heterogeneity are required to understand the molecular diversity of cancer and achieve the goal of personalized therapies. patient-derived xenograft （PDX） models generated from human tumor samples that can retain the histological and genetic features of their donor tumors have been shown to be the preferred preclinical tool in translational cancer research compared with other conventional preclinical models. Specifically, genetically well-defined PDX models can be applied to accelerate targeted antitumor drug development and biomarker discovery. Recently, we have successfully established and characterized an OSCC PDX panel as part of our tumor bio-bank for translational cancer research. In this paper, we discuss the establishment, characterization, and preclinical applications of the PDX models. In particular, we focus on the classification and applications of the PDX models based on validated annotations, including clinicopathological features, genomic profiles, and pharmacological testing information. We also explore the translational value of this well-annotated PDX panel in the development of co-clinical trials for patient stratification and treatment optimization in the near future. Although various limitations still exist, this preclinical approach should be further tested and improved.

关键词： patient-derived xenograft models personalized medicine co-clinical trial patient stratification oral squamous cellcarcinoma

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Revisiting ovarian cancer microenvironment： a friend or a foe？

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Protein & Cell 2018年第8期9卷 674-692页

作者： Boyi Zhang Fei Chen Qixia Xu Liu Han Jiaqian Xu Libin Gao Xiaochen Sun Yiwen Li Yan Li Min Qian Yu Sun Key Laboratory of Stem Cell Biology Institute of Health Sciences Shanghai Institutes for Biological Sciences Chinese Academy of Sciences and Shanghai Jiao Tong University School of Medicine University of Chinese Academy of Sciences Shanghai 200031 China Institute of Health Sciences Shanghai Jiao Tong University School of Medicine and Shanghai Institutes for Biological Sciences Chinese Academy of Sciences Shanghai 200031 China Department of Medicine and VAPSHCS Univers"ity of Washington Seattle WA 98195 USA

Development of ovarian cancer involves the co-evolu- tion of neoplastic cells together with the adjacent microenvironment. Steps of malignant progression including primary tumor outgrowth, therapeutic resis- tance, and distant metastasis are not determined solely by genetic alterations in ovarian cancer cells, but con- siderably shaped by the fitness advantage conferred by benign components in the ovarian stroma. As the dynamic cancer topography varies drastically during disease progression, heterologous cell types within the tumor microenvironment （TME） can actively determine the pathological track of ovarian cancer. Resembling many other solid tumor types, ovarian malignancy is nurtured by a TME whose dark side may have been overlooked, rather than overestimated. Further, har- nessing breakthrough and targeting cures in human ovarian cancer requires insightful understanding of the merits and drawbacks of current treatment modalities, which mainly target transformed cells. Thus, designing novel and precise strategies that both eliminate cancer cells and manipulate the TME is increasingly recognized as a rational avenue to improve therapeutic outcome and prevent disease deterioration of ovarian cancer patients.

关键词： ovarian cancer stromal cells tumormicroenvironment therapeutic resistance ectopicmetastasis combinational treatment patient stratification

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Histone deacetylase inhibitor pre-treatment enhances the efficacy of DNA-interacting chemotherapeutic drugs in gastric cancer

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World Journal of Gastroenterology 2020年第6期26卷 598-613页

作者： Ramchandra Vigay Amnekar Shafqat Ali Khan Mudasir Rashid Bharat Khade Rahul Thorat Poonam Gera Shailesh V Shrikhande Duane T Smoot Hassan Ashktorab Sanjay Gupta Epigenetics and Chromatin Biology Group Gupta LaboratoryCancer Research InstituteAdvanced Centre for Treatment Research and Education in CancerTata Memorial CentreKhargharNavi MumbaiMaharashtra 410210India Homi Bhabha National Institute Training School ComplexAnushakti NagarMumbaiMaharashtra 400085India Department of Developmental Biology School of MedicineWashington University in St.LouisSaint LouisMO 63130United States Animal House Facility Cancer Research InstituteAdvanced Centre for Treatment Research and Education in CancerTata Memorial CentreKhargharNavi MumbaiMaharashtra 410210India Biorepository Lab Advanced Centre for Treatment Research and Education in CancerTata Memorial CentreKhargharNavi MumbaiMaharashtra 410210India Gastrointestinal and Hepato-Pancreato-Biliary Service Department of Surgical OncologyTata Memorial HospitalParelMumbai 400012India Department of Medicine Meharry Medical CenterNashvilleTN 37208United States Department of Medicine and Cancer Center College of MedicineHoward UniversityWashington DCWA 20060United States

BACKGROUND The prognosis of gastric cancer continues to remain poor,and epigenetic drugs like histone deacetylase inhibitors(HDACi)have been envisaged as potential therapeutic agents.Nevertheless,clinical trials are facing issues with toxicity and efficacy against solid tumors,which may be partly due to the lack of patient stratification for effective treatments.To study the need of patient stratification before HDACi treatment,and the efficacy of pre-treatment of HDACi as a chemotherapeutic drug sensitizer.METHODS The expression activity of class 1 HDACs and histone acetylation was examined in human gastric cancer cells and tissues.The potential combinatorial regime of HDACi and chemotherapy drugs was defined on the basis of observed drug binding assays,chromatin remodeling and cell death.RESULTS In the present study,the data suggest that the differential increase in HDAC activity and the expression of class 1 HDACs are associated with hypoacetylation of histone proteins in tumors compared to normal adjacent mucosa tissue samples of gastric cancer.The data highlights for the first time that pretreatment of HDACi results in an increased amount of DNA-bound drugs associated with enhanced histone acetylation,chromatin relaxation and cell cycle arrest.Fraction-affected plots and combination index-based analysis show that pre-HDACi chemo drug combinatorial regimes,including valproic acid with cisplatin or oxaliplatin and trichostatin A with epirubicin,exhibit synergism with maximum cytotoxic potential due to higher cell death at low combined doses in gastric cancer cell lines.CONCLUSION Expression or activity of class 1 HDACs among gastric cancer patients present an effective approach for patient stratification.Furthermore,HDACi therapy in pretreatment regimes is more effective with chemotherapy drugs,and may aid in predicting individual patient prognosis.

关键词： Chemotherapy Combinatorial index Gastric cancer Histone acetylation Histone deacetylase inhibitor patient stratification

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