Integrative analysis of non-small cell lung cancer patient-derived xenografts identifies distinct proteotypes associated with patient outcomes

Microfabricated Organ-Specific Models of Tumor Microenvironments

Despite the advances in detection, diagnosis, and treatments, cancer remains a lethal disease, claiming the lives of more than 600,000 people in the United States alone in 2024. To accelerate the development of new therapeutic strategies with improved responses, significant efforts have been made to develop microfabricated in vitro models of tumor microenvironments (TMEs) that address the limitations of animal-based cancer models. These models incorporate several advanced tissue engineering techniques to better reflect the organ- and patient-specific TMEs. Additionally, microfabricated models integrated with next-generation single-cell omics technologies provide unprecedented insights into patient's cellular and molecular heterogeneity and complexity. This review provides an overview of the recent understanding of cancer development and outlines the key TME elements that can be captured in microfabricated models to enhance their physiological relevance. We highlight the recent advances in microfabricated cancer models that reflect the unique characteristics of their organs of origin or sites of dissemination.

Comprehensive multimodal and multiomic profiling reveals epigenetic and transcriptional reprogramming in lung tumors

Epigenomic mechanisms are critically involved in mediation of genetic and environmental factors that underlie cancer development. Histone modifications represent highly informative epigenomic marks that reveal activation and repression of gene activities and dysregulation of transcriptional control due to tumorigenesis. Here, we present a comprehensive epigenomic and transcriptomic mapping of 18 stage I and II tumor and 20 non-neoplastic tissues from non-small cell lung adenocarcinoma patients. Our profiling covers 5 histone marks including activating (H3K4me3, H3K4me1, and H3K27ac) and repressive (H3K27me3 and H3K9me3) marks and the transcriptome using only 20 mg of tissue per sample, enabled by low-input omic technologies. Using advanced integrative bioinformatic analysis, we uncover cancer-driving signaling cascade networks, changes in 3D genome modularity, differential expression and functionalities of transcription factors and noncoding RNAs. Many of these identified genes and regulatory molecules show no significant change in their expression or a single epigenomic modality, emphasizing the power of integrative multimodal and multiomic analysis using patient samples.

Patient-derived xenograft model in cancer: establishment and applications

The patient-derived xenograft (PDX) model is a crucial in vivo model extensively employed in cancer research that has been shown to maintain the genomic characteristics and pathological structure of patients across various subtypes, metastatic, and diverse treatment histories. Various treatment strategies utilized in PDX models can offer valuable insights into the mechanisms of tumor progression, drug resistance, and the development of novel therapies. This review provides a comprehensive overview of the establishment and applications of PDX models. We present an overview of the history and current status of PDX models, elucidate the diverse construction methodologies employed for different tumors, and conduct a comparative analysis to highlight the distinct advantages and limitations of this model in relation to other in vivo models. The applications are elucidated in the domain of comprehending the mechanisms underlying tumor development and cancer therapy, which highlights broad applications in the fields of chemotherapy, targeted therapy, delivery systems, combination therapy, antibody-drug conjugates and radiotherapy. Furthermore, the combination of the PDX model with multiomics and single-cell analyses for cancer research has also been emphasized. The application of the PDX model in clinical treatment and personalized medicine is additionally emphasized.

The crosstalk between SND1 and PDCD4 is associated with chemoresistance of non-small cell lung carcinoma cells

Lung cancer is the leading cause of cancer-related deaths worldwide. Non-small cell lung cancer (NSCLC) is highly resistant to chemo- or radiation therapy, which poses a huge challenge for treatment of advanced NSCLC. Previously, we demonstrated the oncogenic role of Tudor Staphylococcal nuclease (TSN, also known as Staphylococcal nuclease domain-containing protein 1, SND1), in regulating chemoresistance in NSCLC cells. Here, we showed that silencing of SND1 augmented the sensitivity of NSCLC cells to different chemotherapeutic drugs. Additionally, the expression of PDCD4 (a tumor suppressor highly associated with lung cancer) in NSCLC cells with low endogenous levels was attenuated by SND1 silencing, implying that SND1 might function as a molecular regulator upstream of PDCD4. PDCD4 is differentially expressed in various NSCLC cells. In the NSCLC cells (A549 and H23 cells) with low expression of PDCD4, despite the downregulation of PDCD4, silencing of SND1 still led to sensitization of NSCLC cells to treatment with different chemotherapeutic agents by the inhibition of autophagic activity. Thus, a novel correlation interlinking SND1 and PDCD4 in the regulation of NSCLC cells concerning chemotherapy was revealed, which contributes to understanding the mechanisms of chemoresistance in NSCLC.

Phosphoproteomics profiling of sorafenib-resistant hepatocellular carcinoma patient-derived xenografts reveals potential therapeutic strategies

Hepatocellular carcinoma (HCC) is the most common form of primary liver cancer with poor prognosis. Sorafenib, a first-line treatment for advanced HCC, has shown limited clinical benefits due to the onset of drug resistance. Thus, it is imperative to comprehend the mechanisms underlying sorafenib resistance and explore strategies to overcome or delay it. Here, we established HCC patient-derived xenograft (PDX) models with acquired resistance to sorafenib and performed comprehensive proteomic and phosphoproteomic analyses on these models. The active cell cycle pathway along with the active cyclin-dependent kinase CDK1 and DNA-dependent protein kinase PRKDC was identified through KEGG pathway enrichment and kinase substrate enrichment analyses. Upon investigating the potential of combining sorafenib with putative kinase inhibitors, we found that the combination displays synergistic anti-proliferative effects in the sorafenib-resistant liver cancer cell line, thus providing a proof of concept for phosphoproteomic-guided design of precision medicine.

Investigating proteogenomic divergence in patient-derived xenograft models of ovarian cancer

Within ovarian cancer research, patient-derived xenograft (PDX) models recapitulate histologic features and genomic aberrations found in original tumors. However, conflicting data from published studies have demonstrated significant transcriptional differences between PDXs and original tumors, challenging the fidelity of these models. We employed a quantitative mass spectrometry-based proteomic approach coupled with generation of patient-specific databases using RNA-seq data to investigate the proteogenomic landscape of serially-passaged PDX models established from two patients with distinct subtypes of ovarian cancer. We demonstrate that the utilization of patient-specific databases guided by transcriptional profiles increases the depth of human protein identification in PDX models. Our data show that human proteomes of serially passaged PDXs differ significantly from their patient-derived tumor of origin. Analysis of differentially abundant proteins revealed enrichment of distinct biological pathways with major downregulated processes including extracellular matrix organization and the immune system. Finally, we investigated the relative abundances of ovarian cancer-related proteins identified from the Cancer Gene Census across serially passaged PDXs, and found their protein levels to be unstable across PDX models. Our findings highlight features of distinct and dynamic proteomes of serially-passaged PDX models of ovarian cancer.

Downregulation of MGLL and microRNAs (miR-302b-5p, miR-190a-3p, miR-450a-2-3p) in non-small cell lung cancer: potential roles in pathogenesis

Genes involved in lipid metabolism have been considered potential therapeutic targets in lung cancer because lipid metabolism is severely disrupted in this cancer. Monoglyceride lipase (MGLL) is a lipolytic enzyme that converts monoacylglycerides to fatty acids and glycerol. MicroRNAs (miRNA), one of the most important epigenetic regulators of gene expression, are also considered potential biomarkers in diagnosing, treating, and prognosis lung cancer. This study aimed to investigate the potential effects of MGLL and related miRNAs (miR-302b-5p, miR-190a-3p, miR-450a-2-3p) in the pathogenesis of non-small cell lung cancer (NSCLC) by examining their expression levels and regulatory mechanisms. We analysed the expression levels of MGLL and miRNAs in 30 NSCLC and 20 non-cancerous tissues by qPCR. We performed in silico analyses to determine the biological functions of MGLL and miRNAs in NSCLC. A protein-protein interaction (PPI) network was constructed for MGLL, and gene ontology (GO) analysis, and the interacting genes were analysed using the TCGAnalyzer tool. Our study showed that the expression levels of MGLL, miR-302b-5p, miR-190a-3p and miR-450a-2-3p were significantly decreased in NSCLC tissues (p < 0.05). Also, according to TCGAnalyzer, MSRB3, HTR4, and FCER1G genes were downregulated genes for NSCLC. We showed that miR-302b-5p, miR-190a-3p, and miR-450a-2-3p significantly regulate the TGF-β signalling pathway. In conclusion, this study provides evidence for the potential role of MGLL and microRNAs (miR-302b-5p, miR-190a-3p, miR-450a-2-3p) in NSCLC. In subsequent studies, it was determined that MSRB3, FCER1G and LTB4R2 genes, especially the HTR4 gene, could be potential target genes for lung cancer.

Complete remission after pembrolizumab monotherapy in a non-small cell lung cancer patient with PD-L1 negative, high tumor mutational burden, and positive tumor-infiltrating lymphocytes: A case report

RATIONALE

Immune checkpoint inhibitors have been used to treat cancer patients. Non-small cell lung cancer (NSCLC) patients with a high expression level of programmed cell death ligand-1 (PD-L1) could benefit from immune checkpoint inhibitor monotherapy. However, treating NSCLC patients with PD-L1 negative is still a clinical challenge. The utilization of new-type tumor markers as predictive indicators of therapeutic efficacy, with the aim of guiding clinical medication strategies, has emerged as a paramount focus of clinical investigation and interest.

PATIENT CONCERNS AND DIAGNOSES

We reported a 72-year-old male with cough diagnosed as poorly differentiated metastatic lung adenocarcinoma (cT3N2M1, stage IV). He tested negative for driver gene mutations, and PD-L1 negative (＜1%), but a high tumor mutational burden (30.9 and 39.1 mutations/Mb in the lung tissue and blood, respectively), and positive tumor-infiltrating lymphocytes.

INTERVENTIONS

The patient received pembrolizumab monotherapy.

OUTCOMES

After 8 treatment cycles over 5 months, repeat examinations showed significantly reduced lung mass and circulating tumor DNA abundance. The patient reached clinical complete remission and had long-term survival with no significant adverse events.

LESSONS

A comprehensive evaluation of multiple tumor biomarkers should be considered in NSCLC patients. Pembrolizumab monotherapy could benefit NSCLC patients with negative driver genes, PD-L1 negative, a high tumor mutational burden, and positive tumor-infiltrating lymphocytes.

Peripheral Inflammation Featuring Eosinophilia or Neutrophilia Is Associated with the Survival and Infiltration of Eosinophils within the Tumor among Various Histological Subgroups of Patients with NSCLC

Immune activation status determines non-small cell lung cancer (NSCLC) prognosis, with reported positive/negative associations for T helper type 2 (TH2) responses, including allergen-specific IgE and eosinophils. Our study seeks to explore the potential impact of these comorbid immune responses on the survival rates of patients with NSCLC. Our retrospective study used data from the Data Warehouse of the German Center for Lung Research (DZL) and Lung Biobank at Thoraxklinik Heidelberg. We estimated the association of blood eosinophilia and neutrophilia on survival rates in an inflammatory cohort of 3143 patients with NSCLC. We also tested sensitization to food and inhalants and high-sensitivity C-reactive protein (hs-CRP) in a comorbidity cohort of 212 patients with NSCLC. Finally, we estimated the infiltration of immune-relevant cells including eosinophils, T-cells, and mast cells in a tissue inflammatory sub-cohort of 60 patients with NSCLC. Sensitization to at least one food or inhalant (sIgE) was higher in patients with adenocarcinoma (adeno-LC) than the non-adenocarcinoma (non-adeno-LC). Furthermore, hs-CRP was higher in non-adeno-LC compared with adeno-LC. Peripheral inflammation, particularly eosinophilia and neutrophilia, was associated with poor survival outcomes in NSCLC with a clear difference between histological subgroups. Finally, blood eosinophilia was paralleled by significant eosinophil infiltration into the peritumoral tissue in the lung. This study provides novel perspectives on the crucial role of peripheral inflammation, featuring eosinophilia and neutrophilia, with overall survival, underscoring distinctions between NSCLC subgroups (adeno-LC vs. non-adeno-LC). Peripheral eosinophilia enhances eosinophil infiltration into tumors. This sheds light on the complex interplay between inflammation, eosinophil infiltration, and NSCLC prognosis among various histological subtypes. Further studies are required to underscore the role of eosinophils in NSCLC among different histological subgroups and their role in shaping the tumor microenvironment.

DSBSO-Based XL-MS Analysis of Breast Cancer PDX Tissues to Delineate Protein Interaction Network in Clinical Samples

Protein-protein interactions (PPIs) are fundamental to understanding biological systems as protein complexes are the active molecular modules critical for carrying out cellular functions. Dysfunctional PPIs have been associated with various diseases including cancer. Systems-wide PPI analysis not only sheds light on pathological mechanisms, but also represents a paradigm in identifying potential therapeutic targets. In recent years, cross-linking mass spectrometry (XL-MS) has emerged as a powerful tool for defining endogenous PPIs of cellular networks. While proteome-wide studies have been performed in cell lysates, intact cells and tissues, applications of XL-MS in clinical samples have not been reported. In this study, we adopted a DSBSO-based in vivo XL-MS platform to map interaction landscapes from two breast cancer patient-derived xenograft (PDX) models. As a result, we have generated a PDX interaction network comprising 2,557 human proteins and identified interactions unique to breast cancer subtypes. Interestingly, most of the observed differences in PPIs correlated well with protein abundance changes determined by TMT-based proteome quantitation. Collectively, this work has demonstrated the feasibility of XL-MS analysis in clinical samples, and established an analytical workflow for tissue cross-linking that can be generalized for mapping PPIs from patient samples in the future to dissect disease-relevant cellular networks.

Clinical and pathological predictors of engraftment for patient-derived xenografts in lung adenocarcinoma

Patient-derived xenografts (PDXs) are increasingly utilized in preclinical drug efficacy studies due to their ability to retain the molecular, histological, and drug response characteristics of patient tumors. This study aimed to investigate the factors influencing the successful engraftment of PDXs. Lung adenocarcinoma PDXs were established using freshly resected tumor tissues obtained through surgery. Radiological data of pulmonary nodules from this PDX cohort were analyzed, categorizing them into solid tumors and tumors with ground-glass opacity (GGO) based on preoperative CT images. Gene mutation status was obtained from next generation sequencing data and MassARRAY panel. A total of 254 resected primary lung adenocarcinomas were utilized for PDX establishment, with successful initial engraftment in 58 cases (22.8 %); stable engraftment defined as at least three serial passages was observed in 43 cases (16.9 %). The stable engraftment rates of PDXs from solid tumors and tumors with GGO were 22.1 % (42 of 190 cases) and 1.6 % (1 of 64 cases), respectively (P < 0.001). Adenocarcinomas with advanced stage, poor differentiation, solid histologic subtype, and KRAS or TP53 gene mutations were associated with stable PDX engraftment. Avoiding tumors with GGO features could enhance the cost-effectiveness of establishing PDX models from early-stage resected lung adenocarcinomas.

A comprehensive meta-analysis of tissue resident memory T cells and their roles in shaping immune microenvironment and patient prognosis in non-small cell lung cancer

Tissue-resident memory T cells (TRM) are a specialized subset of long-lived memory T cells that reside in peripheral tissues. However, the impact of TRM-related immunosurveillance on the tumor-immune microenvironment (TIME) and tumor progression across various non-small-cell lung cancer (NSCLC) patient populations is yet to be elucidated. Our comprehensive analysis of multiple independent single-cell and bulk RNA-seq datasets of patient NSCLC samples generated reliable, unique TRM signatures, through which we inferred the abundance of TRM in NSCLC. We discovered that TRM abundance is consistently positively correlated with CD4+ T helper 1 cells, M1 macrophages, and resting dendritic cells in the TIME. In addition, TRM signatures are strongly associated with immune checkpoint and stimulatory genes and the prognosis of NSCLC patients. A TRM-based machine learning model to predict patient survival was validated and an 18-gene risk score was further developed to effectively stratify patients into low-risk and high-risk categories, wherein patients with high-risk scores had significantly lower overall survival than patients with low-risk. The prognostic value of the risk score was independently validated by the Cancer Genome Atlas Program (TCGA) dataset and multiple independent NSCLC patient datasets. Notably, low-risk NSCLC patients with higher TRM infiltration exhibited enhanced T-cell immunity, nature killer cell activation, and other TIME immune responses related pathways, indicating a more active immune profile benefitting from immunotherapy. However, the TRM signature revealed low TRM abundance and a lack of prognostic association among lung squamous cell carcinoma patients in contrast to adenocarcinoma, indicating that the two NSCLC subtypes are driven by distinct TIMEs. Altogether, this study provides valuable insights into the complex interactions between TRM and TIME and their impact on NSCLC patient prognosis. The development of a simplified 18-gene risk score provides a practical prognostic marker for risk stratification.

Comprehensive multimodal and multiomic profiling reveals epigenetic and transcriptional reprogramming in lung tumors

Epigenomic mechanisms are critically involved in mediation of genetic and environmental factors that underlie cancer development. Histone modifications represent highly informative epigenomic marks that reveal activation and repression of gene activities and dysregulation of transcriptional control due to tumorigenesis. Here, we present a comprehensive epigenomic and transcriptomic mapping of 18 tumor and 20 non-neoplastic tissues from non-small cell lung adenocarcinoma patients. Our profiling covers 5 histone marks including activating (H3K4me3, H3K4me1, and H3K27ac) and repressive (H3K27me3 and H3K9me3) marks and the transcriptome using only 20 mg of tissue per sample, enabled by low-input omic technologies. Using advanced integrative bioinformatic analysis, we uncovered cancer-driving signaling cascade networks, changes in 3D genome modularity, and differential expression and functionalities of transcription factors and noncoding RNAs. Many of these identified genes and regulatory molecules showed no significant change in their expression or a single epigenomic modality, emphasizing the power of integrative multimodal and multiomic analysis using patient samples.

T-plastin contributes to epithelial-mesenchymal transition in human lung cancer cells through FAK/AKT/Slug axis signaling pathway

T-plastin (PLST), a member of the actin-bundling protein family, plays crucial roles in cytoskeletal structure, regulation, and motility. Studies have shown that the plastin family is associated with the malignant characteristics of cancer, such as circulating tumor cells and metastasis, by inducing epithelialmesenchymal transition (EMT) in various cancer cells. However, the role of PLST in the EMT of human lung cancer cells remains unclear. In this study, we observed that PLST overexpression enhanced cell migratory and invasive abilities, whereas its downregulation resulted in their suppression. Moreover, PLST expression levels were associated with the expression patterns of EMT markers, including E-cadherin, vimentin, and Slug. Furthermore, the phosphorylation levels of focal adhesion kinase (FAK) and AKT serine/threonine kinase (AKT) were dependent on PLST expression levels. These findings indicate that PLST induces the migration and invasion of human lung cancer cells by promoting Slug-mediated EMT via the FAK/AKT signaling pathway. [BMB Reports 2024; 57(6): 305-310].

Identification of novel genes associated with atherosclerosis in Bama miniature pig

BACKGROUND

Atherosclerosis is a chronic cardiovascular disease of great concern. However, it is difficult to establish a direct connection between conventional small animal models and clinical practice. The pig's genome, physiology, and anatomy reflect human biology better than other laboratory animals, which is crucial for studying the pathogenesis of atherosclerosis.

METHODS

We used whole-genome sequencing data from nine Bama minipigs to perform a genome-wide linkage analysis, and further used bioinformatic tools to filter and identify underlying candidate genes. Candidate gene function prediction was performed using the online prediction tool STRING 12.0. Immunohistochemistry and immunofluorescence were used to detect the expression of proteins encoded by candidate genes.

RESULTS

We mapped differential single nucleotide polymorphisms (SNPs) to genes and obtained a total of 102 differential genes, then we used GO and KEGG pathway enrichment analysis to identify four candidate genes, including SLA-1, SLA-2, SLA-3, and TAP2. nsSNPs cause changes in the primary and tertiary structures of SLA-I and TAP2 proteins, the primary structures of these two proteins have undergone amino acid changes, and the tertiary structures also show slight changes. In addition, immunohistochemistry and immunofluorescence results showed that the expression changes of TAP2 protein in coronary arteries showed a trend of increasing from the middle layer to the inner layer.

CONCLUSIONS

We have identified SLA-I and TAP2 as potential susceptibility genes of atherosclerosis, highlighting the importance of antigen processing and immune response in atherogenesis.

Representation of genomic intratumor heterogeneity in multi-region non-small cell lung cancer patient-derived xenograft models

Patient-derived xenograft (PDX) models are widely used in cancer research. To investigate the genomic fidelity of non-small cell lung cancer PDX models, we established 48 PDX models from 22 patients enrolled in the TRACERx study. Multi-region tumor sampling increased successful PDX engraftment and most models were histologically similar to their parent tumor. Whole-exome sequencing enabled comparison of tumors and PDX models and we provide an adapted mouse reference genome for improved removal of NOD scid gamma (NSG) mouse-derived reads from sequencing data. PDX model establishment caused a genomic bottleneck, with models often representing a single tumor subclone. While distinct tumor subclones were represented in independent models from the same tumor, individual PDX models did not fully recapitulate intratumor heterogeneity. On-going genomic evolution in mice contributed modestly to the genomic distance between tumors and PDX models. Our study highlights the importance of considering primary tumor heterogeneity when using PDX models and emphasizes the benefit of comprehensive tumor sampling.

Identification of key genes and signalling pathways in clear cell renal cell carcinoma: An integrated bioinformatics approach

BACKGROUND

Clear cell Renal Cell Carcinoma (ccRCC) is one of the most prevalent types of kidney cancer. Unravelling the genes responsible for driving cellular changes and the transformation of cells in ccRCC pathogenesis is a complex process.

OBJECTIVE

In this study, twelve microarray ccRCC datasets were chosen from the gene expression omnibus (GEO) database and subjected to integrated analysis.

METHODS

Through GEO2R analysis, 179 common differentially expressed genes (DEGs) were identified among the datasets. The common DEGs were subjected to functional enrichment analysis using ToppFun followed by construction of protein-protein interaction network (PPIN) using Cytoscape. Clusters within the DEGs PPIN were identified using the Molecular Complex Detection (MCODE) Cytoscape plugin. To identify the hub genes, the centrality parameters degree, betweenness, and closeness scores were calculated for each DEGs in the PPIN. Additionally, Gene Expression Profiling Interactive Analysis (GEPIA) was utilized to validate the relative expression levels of hub genes in the normal and ccRCC tissues.

RESULTS

The common DEGs were highly enriched in Hypoxia-inducible factor (HIF) signalling and metabolic reprogramming pathways. VEGFA, CAV1, LOX, CCND1, PLG, EGF, SLC2A1, and ENO2 were identified as hub genes.

CONCLUSION

Among 8 hub genes, only the expression levels of VEGFA, LOX, CCND1, and EGF showed a unique expression pattern exclusively in ccRCC on compared to other type of cancers.

In vitro vascularized immunocompetent patient-derived model to test cancer therapies

This work describes a patient-derived tumoroid model (PDTs) to support precision medicine in lung oncology. The use of human adipose tissue-derived microvasculature and patient-derived peripheral blood mononuclear cells (PBMCs) permits to achieve a physiologically relevant tumor microenvironment. This study involved ten patients at various stages of tumor progression. The vascularized, immune-infiltrated PDT model could be obtained within two weeks, matching the requirements of the therapeutic decision. Histological and transcriptomic analyses confirmed that the main features from the original tumor were reproduced. The 3D tumor model could be used to determine the dynamics of response to antiangiogenic therapy and platinum-based chemotherapy. Antiangiogenic therapy showed a significant decrease in vascular endothelial growth factor (VEGF)-A expression, reflecting its therapeutic effect in the model. In an immune-infiltrated PDT model, chemotherapy showed the ability to decrease the levels of lymphocyte activation gene-3 protein (LAG-3), B and T lymphocyte attenuator (BTLA), and inhibitory receptors of T cells functions.

The differential prognostic implications of PD-L1 expression in the outcomes of Filipinos with EGFR-mutant NSCLC treated with tyrosine kinase inhibitors

Background

The tumor immune microenvironment influences tumor evolution in non-small cell lung cancer (NSCLC). Yet, the prognostic value of programmed death-ligand 1 (PD-L1) in epidermal growth factor receptor (EGFR)-mutant NSCLC remains controversial. Additionally, prognostic studies in Filipinos with EGFR-mutant NSCLC remain unexplored to this day.

Methods

We prospectively studied the outcomes of EGFR-mutant NSCLC in Filipino cohort, and retrospectively verified the survival trend using The Cancer Genome Atlas (TCGA) cohort. Kaplan-Meier method and generalized linear regression were used to assess survival. Expression and DNA methylation of cluster of differentiation 274 (CD274, gene that codes for PD-L1) were examined from TCGA tumor profiles. Pearson's correlation was used to correlate PD-L1 expression with outcomes associated with occurrence of EGFR mutations, tyrosine kinase inhibitor (TKI) types, and programmed cell death protein 1 (PD-1) expression. Proteome network analysis was used to examine the correlation between drug resistance and PD-L1.

Results

PD-L1 positivity was associated with significantly longer progression-free survival (PFS; P=0.0096) but had a significantly contrasting influence in the overall survival (OS; P=0.0011). PD-L1 positivity (in both protein and RNA) was associated with longer median OS (mOS) in exon21 L858R, whereas, negativity was associated with longer mOS in exon19 deletion (exon19del). Stratification (high, low, negative) of PD-L1 expression lacked significant prognostic value (all P>0.05). PD-L1/CD274 expression (P<0.05) and DNA methylation (P<0.001) vary significantly among NSCLC subtypes and in different disease stages. Erlotinib treatment produced the longest median progression-free survival (mPFS; 874 days) relative to other EGFR-TKIs (137-311 days). PD-L1 lacked a significant correlation with EGFR-TKIs. Consistent with the immune-regulation activities of PD-1, higher expression leads to relatively shorter mOS. PD-1 correlated positively with PD-L1 expression and occurrence of exon21 L858R.

Conclusions

PD-L1 differentially influenced the outcomes of Filipinos with EGFR-mutant NSCLC. NSCLC subtypes, disease stage, and PD-1 expression may impact the collective outcomes associated with PD-L1 and EGFR-sensitizing mutations.

Proteomic analysis across patient iPSC-based models and human post-mortem hippocampal tissue reveals early cellular dysfunction and progression of Alzheimer's disease pathogenesis

The hippocampus is a primary region affected in Alzheimer's disease (AD). Because AD postmortem brain tissue is not available prior to symptomatic stage, we lack understanding of early cellular pathogenic mechanisms. To address this issue, we examined the cellular origin and progression of AD pathogenesis by comparing patient-based model systems including iPSC-derived brain cells transplanted into the mouse brain hippocampus. Proteomic analysis of the graft enabled the identification of pathways and network dysfunction in AD patient brain cells, associated with increased levels of Aβ-42 and β-sheet structures. Interestingly, the host cells surrounding the AD graft also presented alterations in cellular biological pathways. Furthermore, proteomic analysis across human iPSC-based models and human post-mortem hippocampal tissue projected coherent longitudinal cellular changes indicative of early to end stage AD cellular pathogenesis. Our data showcase patient-based models to study the cell autonomous origin and progression of AD pathogenesis.

Patterns of Carbon-Bound Exogenous Compounds Impact Disease Pathophysiology in Lung Cancer Subtypes in Different Ways

Carbon-bound exogenous compounds, such as polycyclic aromatic hydrocarbons (PAHs), tobacco-specific nitrosamines, aromatic amines, and organohalogens, are known to affect both tumor characteristics and patient outcomes in lung squamous cell carcinoma (LUSC); however, the roles of these compounds in lung adenocarcinoma (LUAD) remain unclear. We analyzed 11 carbon-bound exogenous compounds in LUAD and LUSC samples using in situ high mass-resolution matrix-assisted laser desorption/ionization Fourier-transform ion cyclotron resonance mass spectrometry imaging and performed a cluster analysis to compare the patterns of carbon-bound exogenous compounds between these two lung cancer subtypes. Correlation analyses were conducted to investigate associations among exogenous compounds, endogenous metabolites, and clinical data, including patient survival outcomes and smoking behaviors. Additionally, we examined differences in exogenous compound patterns between normal and tumor tissues. Our analyses revealed that PAHs, aromatic amines, and organohalogens were more abundant in LUAD than in LUSC, whereas the tobacco-specific nitrosamine nicotine-derived nitrosamine ketone was more abundant in LUSC. Patients with LUAD and LUSC could be separated according to carbon-bound exogenous compound patterns detected in the tumor compartment. The same compounds had differential impacts on patient outcomes, depending on the cancer subtype. Correlation and network analyses indicated substantial differences between LUAD and LUSC metabolomes, associated with substantial differences in the patterns of the carbon-bound exogenous compounds. These data suggest that the contributions of these carcinogenic compounds to cancer biology may differ according to the cancer subtypes.

Intratumor microbiome derived glycolysis-lactate signatures depicts immune heterogeneity in lung adenocarcinoma by integration of microbiomic, transcriptomic, proteomic and single-cell data

Introduction

Microbiome plays roles in lung adenocarcinoma (LUAD) development and anti-tumor treatment efficacy. Aberrant glycolysis in tumor might promote lactate production that alter tumor microenvironment, affecting microbiome, cancer cells and immune cells. We aimed to construct intratumor microbiome score to predict prognosis of LUAD patients and thoroughly investigate glycolysis and lactate signature's association with LUAD immune cell infiltration.

Methods

The Cancer Genome Atlas-LUAD (TCGA-LUAD) microbiome data was downloaded from cBioPortal and analyzed to examine its association with overall survival to create a prognostic scoring model. Gene Set Enrichment Analysis (GSEA) was used to find each group's major mechanisms involved. Our study then investigated the glycolysis and lactate pattern in LUAD patients based on 19 genes, which were correlated with the tumor microenvironment (TME) phenotypes and immunotherapy outcomes. We developed a glycolysis-lactate risk score and signature to accurately predict TME phenotypes, prognosis, and response to immunotherapy.

Results

Using the univariate Cox regression analysis, the abundance of 38 genera were identified with prognostic values and a lung-resident microbial score (LMS) was then developed from the TCGA-LUAD-microbiome dataset. Glycolysis hallmark pathway was significantly enriched in high-LMS group and three distinct glycolysis-lactate patterns were generated. Patients in Cluster1 exhibited unfavorable outcomes and might be insensitive to immunotherapy. Glycolysis-lactate score was constructed for predicting prognosis with high accuracy and validated in external cohorts. Gene signature was developed and this signature was elevated in epithelial cells especially in tumor mass on single-cell level. Finally, we found that the glycolysis-lactate signature levels were consistent with the malignancy of histological subtypes.

Discussion

Our study demonstrated that an 18-microbe prognostic score and a 19-gene glycolysis-lactate signature for predicting prognosis of LUAD patients. Our LMS, glycolysis-lactate score and glycolysis-lactate signature have potential roles in precision therapy of LUAD patients.

SPARC: a potential target for functional nanomaterials and drugs

Secreted protein acidic and rich in cysteine (SPARC), also termed osteonectin or BM-40, is a matricellular protein which regulates cell adhesion, extracellular matrix production, growth factor activity, and cell cycle. Although SPARC does not perform a structural function, it, however, modulates interactions between cells and the surrounding extracellular matrix due to its anti-proliferative and anti-adhesion properties. The overexpression of SPARC at sites, including injury, regeneration, obesity, cancer, and inflammation, reveals its application as a prospective target and therapeutic indicator in the treatment and assessment of disease. This article comprehensively summarizes the mechanism of SPARC overexpression in inflammation and tumors as well as the latest research progress of functional nanomaterials in the therapy of rheumatoid arthritis and tumors by manipulating SPARC as a new target. This article provides ideas for using functional nanomaterials to treat inflammatory diseases through the SPARC target. The purpose of this article is to provide a reference for ongoing disease research based on SPARC-targeted therapy.

[Large cell carcinoma of the lung with null immunophenotype: Case report & brief review]

Large cell carcinoma of the lung with null-immunophenotype (LCC-NI) is a diagnostic entity that is especially uncommon now as it does not have any type of cell differentiation or its own molecular alterations. It presents an exceptional diagnostic challenge; indeed, the diagnosis is only possible with complete surgical excision and adequate immunohistochemical and molecular studies. We report the case of a 69-year-old male, with a history of long-term smoking who presented with pleuritic pain. A tumor in the upper lobe of the right lung was detected and removed by lobectomy. Histopathology revealed a neoplasm with large cell morphology without any specific immunophenotype, molecular or genomic rearrangements through next-generation sequencing (NGS) studies, which was diagnosed as LCC-NI.

erarchical tumor artificial intelligence classifier traces tissue of origin and tumor type in primary and metastasized tumors using DNA methylation

Human cancers are heterogenous by their cell composition and origination site. Cancer metastasis generates the conundrum of the unknown origin of migrated tumor cells. Tracing tissue of origin and tumor type in primary and metastasized cancer is vital for clinical significance. DNA methylation alterations play a crucial role in carcinogenesis and mark cell fate differentiation, thus can be used to trace tumor tissue of origin. In this study, we employed a novel tumor-type-specific hierarchical model using genome-scale DNA methylation data to develop a multilayer perceptron model, HiTAIC, to trace tissue of origin and tumor type in 27 cancers from 23 tissue sites in data from 7735 tumors with high resolution, accuracy, and specificity. In tracing primary cancer origin, HiTAIC accuracy was 99% in the test set and 93% in the external validation data set. Metastatic cancers were identified with a 96% accuracy in the external data set. HiTAIC is a user-friendly web-based application through https://sites.dartmouth.edu/salaslabhitaic/. In conclusion, we developed HiTAIC, a DNA methylation-based algorithm, to trace tumor tissue of origin in primary and metastasized cancers. The high accuracy and resolution of tumor tracing using HiTAIC holds promise for clinical assistance in identifying cancer of unknown origin.

Stereotactic body radiation therapy in unresectable stage III non-small cell lung cancer: A systematic review

In unresectable stage III non-small cell lung cancer (NSCLC), the standard of care for most fit patients is concurrent chemotherapy with normofractionated radiotherapy (NFRT), followed by durvalumab consolidation. Nevertheless, almost half of patients will present locoregional or metastatic intrathoracic relapse. Improving locoregional control thus remains an important objective. For this purpose, stereotactic body radiotherapy (SBRT) may be a relevant treatment modality. We performed a systematic review of the literature that evaluate the efficacy and safety of SBRT in this situation, either instead of or in addition to NFRT. Among 1788 unique reports, 18 met the inclusion criteria. They included 447 patients and were mainly prospective (n = 10, including 5 phase 2 trials). In none, maintenance durvalumab was administered. Most reported SBRT boost after NFRT (n = 8), or definitive tumor and nodal SBRT (n = 7). Median OS varied from 10 to 52 months, due to the heterogeneity of the included populations and according to treatment regimen. The rate of severe side effects was low, with <5 % grade 5 toxicity, and mainly observed when mediastinal SBRT was performed without dose constraints to the proximal bronchovascular tree. It was suggested that a biologically effective dose higher than 112.3 Gy may increase locoregional control. SBRT for selected stage III NSCLC bears potential to improve loco-regional tumor control, but at present, this should only be done in prospective clinical trials.

Patient-derived xenograft models in cancer therapy: technologies and applications

Patient-derived xenograft (PDX) models, in which tumor tissues from patients are implanted into immunocompromised or humanized mice, have shown superiority in recapitulating the characteristics of cancer, such as the spatial structure of cancer and the intratumor heterogeneity of cancer. Moreover, PDX models retain the genomic features of patients across different stages, subtypes, and diversified treatment backgrounds. Optimized PDX engraftment procedures and modern technologies such as multi-omics and deep learning have enabled a more comprehensive depiction of the PDX molecular landscape and boosted the utilization of PDX models. These irreplaceable advantages make PDX models an ideal choice in cancer treatment studies, such as preclinical trials of novel drugs, validating novel drug combinations, screening drug-sensitive patients, and exploring drug resistance mechanisms. In this review, we gave an overview of the history of PDX models and the process of PDX model establishment. Subsequently, the review presents the strengths and weaknesses of PDX models and highlights the integration of novel technologies in PDX model research. Finally, we delineated the broad application of PDX models in chemotherapy, targeted therapy, immunotherapy, and other novel therapies.

The NRF2 antagonist ML385 inhibits PI3K-mTOR signaling and growth of lung squamous cell carcinoma cells

BACKGROUND

Lung squamous cell carcinoma (LUSC) currently has limited therapeutic options because of the relatively few validated targets and the lack of clinical drugs for some of these targets. Although NRF2/NFE2L2 pathway activation commonly occurs in LUSC, NRF2 has predominantly been studied in other cancer models. Here, we investigated the function of NRF2 in LUSC, including in organoid models, and we explored the activity of a small molecule NRF2 inhibitor ML385, which has not previously been investigated in LUSC.

METHODS

We first explored the role of NRF2 signaling in LUSC cancer cell line and organoid proliferation through NRF2 knockdown or ML385 treatment, both in vivo and in vitro. Next, we performed Western blot and immunofluorescence assays to determine the effect of NRF2 inhibition on PI3K-mTOR signaling. Finally, we used cell viability and clonogenic assays to explore whether ML385 could sensitize LUSC cancer cells to PI3K inhibitors.

RESULTS

We find that downregulation of NRF2 signaling inhibited proliferation of LUSC cancer cell lines and organoids, both in vivo and in vitro. We also demonstrate that inhibition of NRF2 reduces PI3K-mTOR signaling, with two potential mechanisms being involved. Although NRF2 promotes AKT phosphorylation, it also acts downstream of AKT to increase RagD protein expression and recruitment of mTOR to lysosomes after amino acid stimulation. We also find that ML385 potentiates LUSC growth inhibition by a pan-PI3K inhibitor, which correlates with stronger inhibition of PI3K-mTOR signaling.

CONCLUSIONS

Our data provide additional support for NRF2 promoting LUSC growth through PI3K-mTOR activation and support development of NRF2 inhibitors for the treatment of LUSC.

Valsartan prevents gefitinib-induced lung inflammation, oxidative stress, and alteration of plasma metabolites in rats

Gefitinib (GEF) is an inhibitor of the epidermal growth factor receptor, linked to higher risk of severe/fatal interstitial lung disease (ILD). This study was performed to determine the protective roles of an angiotensin-II type-1 receptor (AT1R) "valsartan (VAL)" in prevention of lung inflammation, oxidative stress and metabolites alteration induced by GEF. Four groups of male Wistar albino rats were received vehicle, VAL (30 mg/kg), GEF (30 mg/kg), or both for four weeks. Blood samples and lungs were harvested for plasma metabolites and histological analysis, respectively, and evaluation of inflammation and oxidative stress. GEF monotherapy showed a dense inflammation in lungs, and significantly increased tumor necrosis factor-α (P = 0.0349), interleukin-6 (P < 0.0001), chemokine ligand-3 (P = 0.0420), and interleukin-1β (P = 0.0377). GEF increased oxidative stress markers including glutathione, malondialdehyde, and catalase levels. Also, several plasma metabolites including butanoic acid, N-methylphenylethanolamine, oxalic acid, l-alanine, phosphoric acid, l-theorinine, pyroglutamic acid, and 2-bromosebacic acid were changed by GEF. The combination of VAL plus GEF reduced the inflammation and oxidative stress mediated by GEF monotherapy. In addition, the combination treatment returned plasma metabolites to the normal levels compared to GEF monotherapy. These findings revealed that VAL has a possible pulmonary protective role against pulmonary toxicity of GEF, which may lead to novel approaches for management of GEF-induced ILD.

Mitochondrial Aconitase ACO2 Links Iron Homeostasis with Tumorigenicity in Non-Small Cell Lung Cancer

The ability of a patient tumor to engraft an immunodeficient mouse is the strongest known independent indicator of poor prognosis in early-stage non-small cell lung cancer (NSCLC). Analysis of primary NSCLC proteomes revealed low-level expression of mitochondrial aconitase (ACO2) in the more aggressive, engrafting tumors. Knockdown of ACO2 protein expression transformed immortalized lung epithelial cells, whereas upregulation of ACO2 in transformed NSCLC cells inhibited cell proliferation in vitro and tumor growth in vivo. High level ACO2 increased iron response element binding protein 1 (IRP1) and the intracellular labile iron pool. Impaired cellular proliferation associated with high level ACO2 was reversed by treatment of cells with an iron chelator, whereas increased cell proliferation associated with low level ACO2 was suppressed by treatment of cells with iron. Expression of CDGSH iron-sulfur (FeS) domain-containing protein 1 [CISD1; also known as mitoNEET (mNT)] was modulated by ACO2 expression level and inhibition of mNT by RNA interference or by treatment of cells with pioglitazone also increased iron and cell death. Hence, ACO2 is identified as a regulator of iron homeostasis and mNT is implicated as a target in aggressive NSCLC.

IMPLICATIONS

FeS cluster-associated proteins including ACO2, mNT (encoded by CISD1), and IRP1 (encoded by ACO1) are part of an "ACO2-Iron Axis" that regulates iron homeostasis and is a determinant of a particularly aggressive subset of NSCLC.

Machine Learning for Lung Cancer Diagnosis, Treatment, and Prognosis

The recent development of imaging and sequencing technologies enables systematic advances in the clinical study of lung cancer. Meanwhile, the human mind is limited in effectively handling and fully utilizing the accumulation of such enormous amounts of data. Machine learning-based approaches play a critical role in integrating and analyzing these large and complex datasets, which have extensively characterized lung cancer through the use of different perspectives from these accrued data. In this review, we provide an overview of machine learning-based approaches that strengthen the varying aspects of lung cancer diagnosis and therapy, including early detection, auxiliary diagnosis, prognosis prediction, and immunotherapy practice. Moreover, we highlight the challenges and opportunities for future applications of machine learning in lung cancer.