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

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.

Combination of squamous cell carcinoma antigen immunocomplex and alpha-fetoprotein in mid-and long-term prediction of hepatocellular carcinoma among cirrhotic patients

BACKGROUND The combination of alpha-fetoprotein(AFP)and squamous cell carcinoma antigen immunocomplex(SCCA-IgM)have been proposed for its use in the screening of hepatocellular carcinoma(HCC).Current screening programs for all cirrhotic patients are controversial and a personalized screening is an unmet need in the precision medicine era.AIM To determine the role of the combination of SCCA-IgM and AFP in predicting mid-and long-term appearance of HCC.METHODS Two-hundred and three cirrhotic patients(Child A 74.9%,B 21.2%,C 3.9%)were followed-up prospectively every six months to screen HCC by ultrasound and AFP according to European Association for the Study of the Liver guidelines.The estimation cohort was recruited in Italy(30.5%;62/203)and validation cohort from Spain(69.5%;141/203).Patients underwent to evaluate SCCA-IgM by enzyme-linked immunosorbent assay(Hepa-IC,Xeptagen,Italy)and AFP levels at baseline.Patients were followed-up for 60 mo,being censored at the time of the appearance of HCC.RESULTS There were 10.8%and 23.1%of HCC development at two-and five-years followup.Patients with HCC showed higher levels of SCCA-IgM than those without it(425.72±568.33 AU/mL vs 195.93±188.40 AU/mL,P=0.009)during the fiveyear follow-up.In multivariate analysis,after adjusting by age,sex,aspartate transaminase and Child-Pugh,the following factors were independently associated with HCC:SCCA-IgM[Hazard ratio(HR)=1.001,95%CI:1.000-1.002;P=0.003],AFP(HR=1.028,95%CI:1.009-1.046;P=0.003)and creatinine(HR=1.56495%CI:1.151-2.124;P=0.004).The log-rank test of the combination resulted in 7.488(P=0.024)in estimation cohort and 11.061(P=0.004)in the validation cohort,and a 100%of correctly classified rate identifying a low-risk group in both cohorts in the two-year follow-up.CONCLUSION We have constructed a predictive model based on the combination of SCCA-IgM and AFP that provides a new HCC screening method,which could be followed by tailored HCC surveillance for individual patients,especially for those cirrhotic patients belonging to the subgroup identified as low-risk of HCC development.

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

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 P<0.001).Our prediction framework and neural network models were externally validated on the TNBC cases from TCGA(N=143)and appeared robust to the changes in patient 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 patients and provide valuable information for therapeutic decision-making.It had the potential to be clinically implemented and promote the personalized management of TNBC.

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

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.

Acupuncture combined with medication for blood-stasis in unstable angina patients with different thrombolysis in myocardial infarction risk stratification

Objective To observe the intervention effects of acupuncture combined with standardized treatment of western medicine on blood-stasis syndrome in unstable angina(UA)patients with different thrombolysis in myocardial infarction(TIMI)risk stratification.Methods According to TIMI risk score,a total of 72 UA patients were included,24 cases in low-risk(0 to 2 points)group,24

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

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.

Revisiting ovarian cancer microenvironment： a friend or a foe？

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.

Persistent EGFR/K-RAS/SIAH pathway activation drives chemo-resistance and early tumor relapse in triple-negative breast cancer

Triple-negative breast cancer(TNBC)is the most aggressive breast cancer subtype.It disproportionately affects BRCA mutation carriers and young women,especially African American(AA)women.Chemoresistant TNBC is a heterogeneous and molecularly unstable disease that challenges our ability to apply personalized therapies.With the approval of immune checkpoint blockade(ICB)for TNBC,the addition of pembrolizumab to systemic chemotherapy has become standard of care(SOC)in neoadjuvant systemic therapy(NST)for high-risk early-stage TNBC.Pembrolizumab plus chemotherapy significantly increased the pathologic complete response(pCR)and improved event-free survival in TNBC.However,clinical uncertainties remain because similarly treated TNBC partial responders with comparable tumor responses to neoadjuvant therapy often experience disparate clinical outcomes.Current methods fall short in accurately predicting which high-risk patients will develop chemo-resistance and tumor relapse.Therefore,novel treatment strategies and innovative new research initiatives are needed.We propose that the EGFR-K-RAS-SIAH pathway activation is a major tumor driver in chemoresistant TNBC.Persistent high expression of SIAH in residual tumors following NACT/NST reflects that the EGFR/K-RAS pathway remains activated(ON),indicating an ineffective response to treatment.These chemoresistant tumor clones persist in expressing SIAH(SIAH^(High/ON))and are linked to early tumor relapse and poorer prognosis.Conversely,the loss of SIAH expression(SIAH^(Low/OFF))in residual tumors post-NACT/NST reflects EGFR/K-RAS pathway inactivation(OFF),indicating effective therapy and chemo-sensitive tumor cells.SIAH^(Low/OFF) signal is linked to tumor remission and better prognosis post-NACT/NST.Therefore,SIAH is well-positioned to become a novel tumor-specific,therapy-responsive,and prognostic biomarker.Potentially,this new biomarker(SIAH^(High/ON))could be used to quantify therapy response,predict chemo-resistance,and identify those patients at the highest risk for tumor relapse and poor survival in TNBC.