Genomic and transcriptomic alterations associated with drug vulnerabilities and prognosis in adenocarcinoma at the gastroesophageal junction

Mutational signatures and their association with cancer survival and gene expression in multiple cancer types

Different endogenous and exogenous mutational processes cause specific patterns of somatic mutations and mutational signatures. Although their biological research has been intensive, there are only rare studies assessing the possible prognostic role of mutational signatures. We used data from The Cancer Genome Atlas to study the associations between the activity of the mutational signatures and four survival endpoints in 18 types of malignancies. We further explored the prognostic differences according to, for example, the HPV status in head and neck squamous cell carcinomas and smoking status in lung cancers. The predictive power of the signatures over time was evaluated with a dynamic area under the curve model, and the links between mutational signature activities and differences in gene expression patterns were analyzed. In 12 of 18 studied cancer types, we identified at least one mutational signature whose activity predicted survival outcomes after adjusting for the established prognostic factors. For example, overall survival was associated with the activity of mutational signatures in nine cancer types and disease-specific survival in seven cancer types. The clock-like signatures SBS5 and SBS40 were most commonly associated with survival endpoints. The genes of the myosin binding protein and melanoma antigen families were among the most substantially dysregulated genes between the signatures of low and high activity. The differences in gene expression also revealed various enriched pathways. Based on these data, specific mutational signatures associate with the gene expression and have the potential to serve as strong prognostic factors in several cancer types.

Interferon Gamma Inducible Protein 30: from biological functions to potential therapeutic target in cancers

Interferon Gamma Inducible Protein 30 (IFI30), also known as Gamma-Interferon-Inducible Lysosomal Thiol Reductase (GILT), is predominantly found in lysosomes and the cytoplasm. As the sole enzyme identified to catalyze disulfide bond reduction in the endocytic pathway, IFI30 contributes to both major histocompatibility complex (MHC) class I-restricted antigen cross-presentation and MHC class II-restricted antigen processing by decreasing the disulfide bonds of endocytosed proteins. Remarkably, emerging research has revealed that IFI30 is involved in tumorigenesis, tumor development, and the tumor immune response. Targeting IFI30 may provide new strategies for cancer therapy and improve the prognosis of patients. This review provided a comprehensive overview of the research progress on IFI30 in tumor progression, cellular redox status, autophagy, tumor immune response, and drug sensitivity, with a view to providing the theoretical basis for pharmacological intervention of IFI30 in tumor therapy, particularly in immunotherapy.

m6A modification enhances the stability of CDC25A promotes tumorigenicity of esophagogastric junction adenocarcinoma via cell cycle

N6-Methyladenosine (m6A) modification and its regulators play critical roles in human cancers, but their functions and regulatory mechanisms in adenocarcinoma of the esophagogastric junction (AEG) remain unclear. Here, we identified that IGF2BP3 is the most significantly up-regulated m6A regulator in AEG tumors versus paired normal adjacent tissues from the expression profile of m6A regulators in a large cohort of AEG patients. Silencing IGF2BP3 inhibits AEG progression in vitro and in vivo. By profiling transcriptome-wide targets of IGF2BP3 and the m6A methylome in AEG, we found that IGF2BP3-mediated stabilization and enhanced expression of m6A-modified targets, including targets of the cell cycle pathway, such as CDC25A, CDK4, and E2F1, are critical for AEG progression. Mechanistically, the increased m6A modification of CDC25A accelerates the G1-S transition. Clinically, up-regulated IGF2BP3, METTL3, and CDC25A show a strong positive correlation in TCGA pan-cancer, including AEG. In conclusion, our study highlights the role of post-transcriptional regulation in modulating AEG tumor progression and elucidates the functional importance of the m6A/IGF2BP3/CDC25A axis in AEG cells.

Predictive role of E2F6 in cancer prognosis and responses of immunotherapy

BACKGROUND

E2F6 is a member of the E2F transcription factor family. Numerous studies have demonstrated that E2F6 is critical to cancer development and progression, but its role in cancer immunotherapy remains unclear.

METHODS

Genotype-Tissue Expression (GTEx) and The Cancer Genome Atlas (TCGA) databases were used to obtain RNA-seq data for cancer and normal tissues, and we utilized the cBioPortal to analyze E2F6 genomic alterations in pan-cancer. The protein localization of E2F6 was obtained using the Human Protein Atlas (HPA), and the upregulation of E2F6 expression in clinical glioblastoma multiforme (GBM) tissues was detected by Western blot analysis. The ComPPI website was used to analyze the protein interaction information of E2F6. To evaluate the role of E2F6 in pan-cancer prognosis, we used univariate Cox regression and Kaplan-Meier methods, and gene set enrichment analysis (GSEA) was utilized to identify markers associated with E2F6 expression in tumors. TIMER 2.0 was used to study E2F6-related immune cell infiltration in tumor tissues, and the correlation of E2F6 with immunotherapy biomarkers was investigated using Spearman correlation analysis. The role of E2F6 in the cell cycle was analyzed by flow cytometry, and the Cell Counting Kit-8 (CCK-8) and colony formation assays were utilized to determine the proliferative ability of cells.

RESULTS

In most tumor types, E2F6 was highly expressed and was a good predictor of prognosis. E2F6 was significantly related to markers of immune activation, tumor immune cell infiltration, and immune regulators. Furthermore, E2F6 knockdown significantly attenuated the proliferative ability of glioma cells. Finally, E2F6 effectively predicted anti-programmed cell death 1 (PD1) treatment response.

CONCLUSION

E2F6 is an effective biomarker that predicts the prognosis of cancer patients treated with anti-immune checkpoint therapy.

Glioblastoma vulnerability to neddylation inhibition is dependent on PTEN status, and dysregulation of the cell cycle and DNA replication

Background

Neddylation (NAE) inhibition, affecting posttranslational protein function and turnover, is a promising therapeutic approach to cancer. We report the cytotoxic vulnerability to NAE inhibitors in a subset of glioblastoma (GBM) preclinical models and identify genetic alterations and biological processes underlying differential response.

Methods

GBM DNA sequencing and transcriptomic data were queried for genes associated with response to NAE inhibition; candidates were validated by molecular techniques. Multi-omics and functional assays revealed processes implicated in NAE inhibition response.

Results

Transcriptomics and shotgun proteomics depict PTEN signaling, DNA replication, and DNA repair pathways as significant differentiators between sensitive and resistant models. Vulnerability to MLN4924, a NAE inhibitor, is associated with elevated S-phase populations, DNA re-replication, and DNA damage. In a panel of GBM models, loss of WT PTEN is associated with resistance to different NAE inhibitors. A NAE inhibition response gene set could segregate the GBM cell lines that are most resistant to MLN4924.

Conclusions

Loss of WT PTEN is associated with non-sensitivity to 3 different compounds that inhibit NAE in GBM. A NAE inhibition response gene set largely consisting of DNA replication genes could segregate GBM cell lines most resistant to NAEi and may be the basis for future development of NAE inhibition signatures of vulnerability and clinical trial enrollment within a precision medicine paradigm.

MYB exhibits racially disparate expression, clinicopathologic association, and predictive potential for biochemical recurrence in prostate cancer

MYB acts as a potentiator of aggressiveness and castration resistance in prostate cancer (PCa) through aberrant activation of androgen receptor (AR) signaling. Since Black men experience higher PCa incidence and mortality than White men, we examined if MYB was differentially expressed in prostate tumors from patients of these racial backgrounds. The data reveal that aberrant MYB expression starts early in precancerous high-grade prostate intraepithelial neoplastic lesions and increases progressively in malignant cells. PCa tissues from Black patients exhibit higher MYB expression than White patients in overall and grade-wise comparisons. MYB also exhibits a positive correlation with AR expression and both display higher expression in advanced tumor stages. Notably, we find that MYB is a better predictor of biochemical recurrence than AR, pre-treatment PSA, or Gleason's grades. These findings establish MYB as a promising molecular target in PCa that could be used for improved risk prediction and therapeutic planning.

Genome wide analysis revealed conserved domains involved in the effector discrimination of bacterial type VI secretion system

Type VI secretion systems (T6SSs) deliver effectors into target cells. Besides structural and effector proteins, many other proteins, such as adaptors, co-effectors and accessory proteins, are involved in this process. MIX domains can assist in the delivery of T6SS effectors when encoded as a stand-alone gene or fused at the N-terminal of the effector. However, whether there are other conserved domains exhibiting similar encoding forms to MIX in T6SS remains obscure. Here, we scanned publicly available bacterial genomes and established a database which include 130,825 T6SS vgrG loci from 45,041 bacterial genomes. Based on this database, we revealed six domain families encoded within vgrG loci, which are either fused at the C-terminus of VgrG/N-terminus of T6SS toxin or encoded by an independent gene. Among them, DUF2345 was further validated and shown to be indispensable for the T6SS effector delivery and LysM was confirmed to assist the interaction between VgrG and the corresponding effector. Together, our results implied that these widely distributed domain families with similar genetic configurations may be required for the T6SS effector recruitment process.

The role of mesenchymal stem cells derived exosomes as a novel nanobiotechnology target in the diagnosis and treatment of cancer

Mesenchymal stem cells (MSCs), one of the most common types of stem cells, are involved in the modulation of the tumor microenvironment (TME). With the advancement of nanotechnology, exosomes, especially exosomes secreted by MSCs, have been found to play an important role in the initiation and development of tumors. In recent years, nanobiotechnology and bioengineering technology have been gradually developed to detect and identify exosomes for diagnosis and modify exosomes for tumor treatment. Several novel therapeutic strategies bioengineer exosomes to carry drugs, proteins, and RNAs, and further deliver their encapsulated cargoes to cancer cells through the properties of exosomes. The unique properties of exosomes in cancer treatment include targeting, low immunogenicity, flexibility in modification, and high biological barrier permeability. Nevertheless, the current comprehensive understanding of the roles of MSCs and their secreted exosomes in cancer development remain inadequate. It is necessary to better understand/update the mechanism of action of MSCs-secreted exosomes in cancer development, providing insights for better modification of exosomes through bioengineering technology and nanobiotechnology. Therefore, this review focuses on the role of MSCs-secreted exosomes and bioengineered exosomes in the development, progression, diagnosis, and treatment of cancer.

Refined expression quantitative trait locus analysis on adenocarcinoma at the gastroesophageal junction reveals susceptibility and prognostic markers

Objectives: This study aimed to explore cell type level expression quantitative trait loci (eQTL) in adenocarcinoma at the gastroesophageal junction (ACGEJ) and identify susceptibility and prognosis markers. Methods: Whole-genome sequencing (WGS) was performed on 120 paired samples from Chinese ACGEJ patients. Germline mutations were detected by GATK tools. RNA sequencing (RNA-seq) data on ACGEJ samples were taken from our previous studies. Public single-cell RNA sequencing (scRNA-seq) data were used to produce the proportion of epithelial cells. Matrix eQTL and a linear mixed model were used to identify condition-specific cis-eQTLs. The R package coloc was used to perform co-localization analysis with the public data of genome-wide association studies (GWASs). Log-rank and Cox regression tests were used to identify survival-associated eQTL and genes. Functions of candidate risk loci were explored by experimental validation. Results: Refined eQTL analyses of paired ACGEJ samples were performed and 2,036 potential ACGEJ-specific eQTLs with East Asian specificity were identified in total. ACGEJ-gain eQTLs were enriched at promoter regions more than ACGEJ-loss eQTLs. rs658524 was identified as the top eQTL close to the transcription start site of its paired gene (CTSW). rs2240191-RASAL1, rs4236599-FOXP2, rs4947311-PSORS1C1, rs13134812-LOC391674, and rs17508585-CDK13-DT were identified as ACGEJ-specific susceptibility eQTLs. rs309483-LINC01355 was associated with the overall survival of ACGEJ patients. We explored functions of candidate eQTLs such as rs658524, rs309483, rs2240191, and rs4947311 by experimental validation. Conclusion: This study provides new risk loci for ACGEJ susceptibility and effective disease prognosis biomarkers.

Comprehensive Analyses Reveal Effects on Tumor Immune Infiltration and Immunotherapy Response of APOBEC Mutagenesis and Its Molecular Mechanisms in Esophageal Squamous Cell Carcinoma

The apolipoprotein B mRNA editing enzyme catalytic polypeptide (APOBEC) mutagenesis is prevalent in esophageal squamous cell carcinoma (ESCC). However, the functional role of APOBEC mutagenesis has yet to be fully delineated. To address this, we collect matched multi-omics data of 169 ESCC patients and evaluate characteristics of immune infiltration using multiple bioinformatic approaches based on bulk and single-cell RNA sequencing (scRNA-seq) data and verified by functional assays. We find that APOBEC mutagenesis prolongs overall survival (OS) of ESCC patients. The reason for this outcome is probably due to high anti-tumor immune infiltration, immune checkpoints expression and immune related pathway enrichment, such as interferon (IFN) signaling, innate and adaptive immune system. The elevated AOBEC3A (A3A) activity paramountly contributes to the footprints of APOBEC mutagenesis and is first discovered to be transactivated by FOSL1. Mechanistically, upregulated A3A exacerbates cytosolic double-stranded DNA (dsDNA) accumulation, thus stimulating cGAS-STING pathway. Simultaneously, A3A is associated with immunotherapy response which is predicted by TIDE algorithm, validated in a clinical cohort and further confirmed in mouse models. These findings systematically elucidate the clinical relevance, immunological characteristics, prognostic value for immunotherapy and underlying mechanisms of APOBEC mutagenesis in ESCC, which demonstrate great potential in clinical utility to facilitate clinical decisions.

Integrative proteomic characterization of adenocarcinoma of esophagogastric junction

The incidence of adenocarcinoma of the esophagogastric junction (AEG) has been rapidly increasing in recent decades, but its molecular alterations and subtypes are still obscure. Here, we conduct proteomics and phosphoproteomics profiling of 103 AEG tumors with paired normal adjacent tissues (NATs), whole exome sequencing of 94 tumor-NAT pairs, and RNA sequencing in 83 tumor-NAT pairs. Our analysis reveals an extensively altered proteome and 252 potential druggable proteins in AEG tumors. We identify three proteomic subtypes with significant clinical and molecular differences. The S-II subtype signature protein, FBXO44, is demonstrated to promote tumor progression and metastasis in vitro and in vivo. Our comparative analyses reveal distinct genomic features in AEG subtypes. We find a specific decrease of fibroblasts in the S-III subtype. Further phosphoproteomic comparisons reveal different kinase-phosphosubstrate regulatory networks among AEG subtypes. Our proteogenomics dataset provides valuable resources for understanding molecular mechanisms and developing precision treatment strategies of AEG.

Characterization of genomic alterations and neoantigens and analysis of immune infiltration identified therapeutic and prognostic biomarkers in adenocarcinoma at the gastroesophageal junction

Objectives

Adenocarcinoma at the gastroesophageal junction (ACGEJ) refers to a malignant tumor that occurs at the esophagogastric junction. Despite some progress in targeted therapies for HER2, FGFR2, EGFR, MET, Claudin 18.2 and immune checkpoints in ACGEJ tumors, the 5-year survival rate of patients remains poor. Thus, it is urgent to explore genomic alterations and neoantigen characteristics of tumors and identify CD8+ T-cell infiltration-associated genes to find potential therapeutic targets and develop a risk model to predict ACGEJ patients’ overall survival (OS).

Methods

Whole-exome sequencing (WES) was performed on 55 paired samples from Chinese ACGEJ patients. Somatic mutations and copy number variations were detected by Strelka2 and FACETS, respectively. SigProfiler and SciClone were employed to decipher the mutation signature and clonal structure of each sample, respectively. Neoantigens were predicted using the MuPeXI pipeline. RNA sequencing (RNA-seq) data of ACGEJ samples from our previous studies and The Cancer Genome Atlas (TCGA) were used to identify genes significantly associated with CD8+ T-cell infiltration by weighted gene coexpression network analysis (WGCNA). To construct a risk model, we conducted LASSO and univariate and multivariate Cox regression analyses.

Results

Recurrent MAP2K7, RNF43 and RHOA mutations were found in ACGEJ tumors. The COSMIC signature SBS17 was associated with ACGEJ progression. CCNE1 and VEGFA were identified as putative CNV driver genes. PI3KCA and TP53 mutations conferred selective advantages to cancer cells. The Chinese ACGEJ patient neoantigen landscape was revealed for the first time, and 58 potential neoantigens common to TSNAdb and IEDB were identified. Compared with Siewert type II samples, Siewert type III samples had significant enrichment of the SBS17 signature, a lower TNFRSF14 copy number, a higher proportion of samples with complex clonal architecture and a higher neoantigen load. We identified 10 important CD8+ T-cell infiltration-related Hub genes (CCL5, CD2, CST7, GVINP1, GZMK, IL2RB, IKZF3, PLA2G2D, P2RY10 and ZAP70) as potential therapeutic targets from the RNA-seq data. Seven CD8+ T-cell infiltration-related genes (ADAM28, ASPH, CAMK2N1, F2R, STAP1, TP53INP2, ZC3H3) were selected to construct a prognostic model. Patients classified as high risk based on this model had significantly worse OS than low-risk patients, which was replicated in the TCGA-ACGEJ cohort.

Conclusions

This study provides new neoantigen-based immunotherapeutic targets for ACGEJ treatment and effective disease prognosis biomarkers.

Integrative analysis reveals a clinicogenomic landscape associated with liver metastasis and poor prognosis in hepatoid adenocarcinoma of the stomach

Hepatoid adenocarcinoma of the stomach (HAS) is a rare subtype of gastric cancer (GC) that histologically resembles hepatocellular carcinoma (HCC). Despite its low incidence, HAS had a poor 5-year survival rate. Currently, the linkages between clinicopathological and genomic features of HAS and its therapeutic targets remain largely unknown. Herein, we enrolled 90 HAS patients and 270 stage-matched non-HAS patients from our institution for comparing clinicopathological features. We found that HAS had worse overall survival and were more prone to develop liver metastasis than non-HAS in our cohort, which was validated via meta-analysis. By comparing whole-exome sequencing data of HAS (n=30), non-HAS (n=63), and HCC (n=355, The Cancer Genome Atlas), we identified a genomic landscape associated with unfavorable clinical features in HAS, which contained frequent somatic mutations and widespread copy number variations. Notably, signaling pathways regulating pluripotency of stem cells affected by frequent genomic alterations might contribute to liver metastasis and poor prognosis in HAS patients. Furthermore, HAS developed abundant multiclonal architecture associated with liver metastasis. Encouragingly, target analysis suggested that HAS patients might potentially benefit from anti-ERBB2 or anti-PD-1 therapy. Taken together, this study systematically demonstrated a high risk of liver metastasis and poor prognosis in HAS, provided a clinicogenomic landscape underlying these unfavorable clinical features, and identified potential therapeutic targets, laying the foundations for developing precise diagnosis and therapy in this rare but lethal disease.

Resolving mutational signatures in cancer development

In a recent Science study, an advanced mutational signature analysis was performed on an unprecedentedly large set of cancer whole-genome sequences across multiple organs. This work introduces a computational framework to identify common and rare mutational signatures and provides insights into their biological interpretation.

Somatic mutation-associated risk index based on lncRNA expression for predicting prognosis in acute myeloid leukemia

Objectives: Genomic instability has several implications for acute myeloid leukemia (AML) prognosis. This article aims to construct a somatic mutation-associated risk index (SMRI) of genomic instability for AML to predict prognosis and explore the potential determinants of AML prognosis.Methods: We obtained differentially expressed lncRNAs from genomic instability subtypes and selected six lncRNAs to construct the SMRI through multivariate Cox regression analysis. The median SMRI classified patients into high and low SMRI groups. Kaplan-Meier survival analysis was used to clarify the prognostic differences of SMRI subtypes. Receiver operating characteristic curve analysis was performed to elucidate the value of SMRI as a prognostic indicator. Gene set variation analysis, tumor mutation burden (TMB) analysis, immune infiltration, and immune checkpoint expression analysis were performed to investigate possible causes for the differences in prognosis of SMRI subtypes.Results: The high SMRI group exhibited a poor prognosis, which was characterized by elevated levels of TMB, mutation counts (TP53, NPM1, DNMT3A, and FLT3-TKD), CD8⁺ T cell infiltration, and immune checkpoint (PD-1, PD-L2, CTLA4, LAG3) expression. The SMRI was still associated with prognosis, even after adjustment for age, sex, cytogenetic risk, DNMT3A status, FLT3 status, and NPM1 status. Gene set variation analysis showed that AML with FLT3-ITD mutation, CEBPA mutation, and LSCs (leukemia stem cells) were enriched in the high SMRI group.Conclusion: Our research suggests that the SMRI derived from genomic instability subtypes is a useful biomarker for predicting prognosis and may be beneficial for improving the clinical outcome of patients with AML.

Sperm Autoantigenic Protein 17 Predicts the Prognosis and the Immunotherapy Response of Cancers: A Pan-Cancer Analysis

Background

Sperm autoantigen protein 17 (SPA17) is a highly conserved mammalian protein that participates in the acrosome reaction during fertilization and is a recently reported member of the cancer-testicular antigen (CTA) family. It has been reported that the SPA17 expression is limited in adult somatic tissues and re-expressed in tumor tissues. Recently, studies have found that SPA17 regulates the progression of various cancers, but its role in cancer immunotherapy is not clear.

Methods

The pan-cancer and normal tissue transcriptional data were acquired from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) datasets. We explored the SPA17 pan-cancer genomic alteration analysis in the cBioPortal webtool. The Human Protein Atlas (HPA) and ComPPI websites were used to mine the SPA17 protein information. We performed a western blotting assay to validate the upregulated SPA17 expression in clinical glioblastoma (GBM) samples. The univariate Cox regression and Kaplan-Meier method were used to assess the prognostic role of SPA17 in pan-cancer. Gene Set Enrichment Analysis (GSEA) was used to search the associated cancer hallmarks with SPA17 expression in each cancer type. TIMER2.0 was the main platform to investigate the immune cell infiltrations related to SPA17 in pan-cancer. The associations between SPA17 and immunotherapy biomarkers were performed by Spearman correlation analysis. The drug sensitivity information from the Connectivity Map (CMap) dataset was downloaded to perform SAP17-specific inhibitor sensitivity analysis.

Findings

SPA17 was aberrantly expressed in most cancer types and exhibited prognosis predictive ability in various cancers. In addition, our results also show that SPA17 was significantly correlated with immune-activated hallmarks (including pathways and biological processes), immune cell infiltrations, and immunoregulator expressions. The most exciting finding was that SPA17 could significantly predict anti-PDL1 and anti-PD1 therapy responses in cancer patients. Finally, specific inhibitors, like irinotecan and puromycin, which correlate with SPA17 expression in different cancer types, were also screened using Connectivity Map (CMap).

Conclusions

Our results reveal that SPA17 was abnormally expressed in cancer tissues, and this expression pattern could be associated with immune cell infiltrations in tumor microenvironments. Clinically, SPA17 not only acted as a potent prognostic factor to predict the clinical outcomes of cancer patients but was also a promising immunotherapy predictive biomarker for cancer patients treated with immune-checkpoint inhibitors (ICIs).

High GILT Expression Is Associated with Improved Survival in Metastatic Melanoma Patients Treated with Immune Checkpoint Inhibition

Simple Summary

Skin cancer is the most common type of cancer, with melanoma being among the deadliest of skin cancers due to its propensity to metastasize. Immune checkpoint inhibitors (ICI) generate anti-tumor immune responses resulting in improved outcomes in patients with metastatic melanoma. However, only a subset of melanoma patients responds to these therapies, which are costly and come with a risk of adverse effects. Therefore, there is a need for biomarkers to predict which patients will respond to ICI. We found that ICI-treated metastatic melanoma patients with high GILT mRNA expression in bulk tumor samples had improved survival. Additionally, high GILT protein expression within metastatic melanoma cells was associated with improved survival in patients treated with ICI. This study suggests that GILT may serve as a biomarker to predict which patients will respond to ICI, which could improve patient care, reduce healthcare costs, and facilitate appropriate selection of therapies for patients with metastatic melanoma.

Abstract

Gamma-interferon-inducible lysosomal thiol reductase (GILT) is critical for MHC class II restricted presentation of multiple melanoma antigens. There is variable GILT protein expression in malignant melanocytes in melanoma specimens. High GILT mRNA expression in melanoma specimens is associated with improved overall survival, before the advent of immune checkpoint inhibitors (ICI). However, the association of GILT in metastatic melanoma with survival in patients treated with ICI and the cell type expressing GILT associated with survival have not been determined. Using RNA sequencing datasets, high GILT mRNA expression in metastatic melanoma specimens was associated with improved progression-free and overall survival in patients treated with ICI. A clinical dataset of metastatic melanoma specimens was generated and annotated with clinical information. Positive GILT immunohistochemical staining in antigen presenting cells and melanoma cells was observed in 100% and 65% of metastatic melanoma specimens, respectively. In the subset of patients treated with ICI in the clinical dataset, high GILT protein expression within melanoma cells was associated with improved overall survival. The association of GILT mRNA and protein expression with survival was independent of cancer stage. These studies support that high GILT mRNA expression in bulk tumor samples and high GILT protein expression in melanoma cells is associated with improved survival in ICI-treated patients. These findings support further investigation of GILT as a biomarker to predict the response to ICI.

Clinicopathological Characteristics and Survival Predictions for Adenocarcinoma of the Esophagogastric Junction: A SEER Population-Based Retrospective Study

Objective

Adenocarcinoma of the esophagogastric junction (AEJ) is a relatively rare malignancy in Western countries whose specific clinicopathological characteristics and associated prognosis have not been comprehensively described.

Methods

Data on patients with AEJ between 2005 and 2015 in the Surveillance, Epidemiology, and End Results (SEER) database were extracted, evaluated, and compared with patients with gastric cancer (GC) in general. Overall survival (OS) was evaluated using the Kaplan–Meier method. Univariate and multivariate analyses were performed using the Cox proportional hazards regression model to identify risk factors predictive for OS, and the results were used to construct a nomogram to predict 1-, 3-, and 5-year OS among patients with AEJ.

Results

A total of 8013 patients diagnosed with AEJ were identified from the records of 30,179 patients with GC. The mean age was 65.4 (SD = 12.0) years, 79.5% were men, 87.2% were Caucasian, 91.5% were moderately-to-poorly differentiated, 34.4% had AJCC stage I AEJ, and 28.8% had stage IV. The median OS was 18 months, and the 5-year OS was 25.8% (95% CI: 24.8–26.8%). Fewer patients with AEJ had undergone surgical resection, fewer had T+ and N+ (N2~N3) disease (P < 0.001), and fewer had distant metastases compared to the patients with GC (P < 0.05). In the univariate and multivariate analyses, age, race, summary stage, N stage, M stage, and surgery were identified as independent risk factors. The nomogram had a calibration index of 0.726.

Conclusion

AEJ was found to have distinct clinicopathological characteristics. Age, race, summary stage, N stage, M stage, and surgery were independently associated with OS. The nomogram accurately predicted 1-, 3-, and 5-year OS rates.

Exosomes: A New Pathway for Cancer Drug Resistance

Exosomes are extracellular vesicles (EVs) that are secreted into body fluids by multiple cell types and are enriched in bioactive molecules, although their exact contents depend on the cells of origin. Studies have shown that exosomes in the tumor microenvironment affect tumor growth, metastasis and drug resistance by mediating intercellular communication and the transport of specific molecules, although their exact mechanisms of action need to be investigated further. In this review, we have summarized current knowledge on the relationship between tumor drug resistance and exosomes, and have discussed the potential applications of exosomes as diagnostic biomarkers and therapeutic targets.

Non-Coding Variants in Cancer: Mechanistic Insights and Clinical Potential for Personalized Medicine

The cancer genome is characterized by extensive variability, in the form of Single Nucleotide Polymorphisms (SNPs) or structural variations such as Copy Number Alterations (CNAs) across wider genomic areas. At the molecular level, most SNPs and/or CNAs reside in non-coding sequences, ultimately affecting the regulation of oncogenes and/or tumor-suppressors in a cancer-specific manner. Notably, inherited non-coding variants can predispose for cancer decades prior to disease onset. Furthermore, accumulation of additional non-coding driver mutations during progression of the disease, gives rise to genomic instability, acting as the driving force of neoplastic development and malignant evolution. Therefore, detection and characterization of such mutations can improve risk assessment for healthy carriers and expand the diagnostic and therapeutic toolbox for the patient. This review focuses on functional variants that reside in transcribed or not transcribed non-coding regions of the cancer genome and presents a collection of appropriate state-of-the-art methodologies to study them.

Immune Infiltration Subtypes Characterization and Identification of Prognosis-Related lncRNAs in Adenocarcinoma of the Esophagogastric Junction

The incidence of adenocarcinoma of the esophagogastric junction (AEG) has markedly increased worldwide. However, the precise etiology of AEG is still unclear, and the therapeutic options thus remain limited. Growing evidence has implicated long non-coding RNAs (lncRNAs) in cancer immunomodulation. This study aimed to examine the tumor immune infiltration status and assess the prognostic value of immune-related lncRNAs in AEG. Using the ESTIMATE method and single-sample GSEA, we first evaluated the infiltration level of 28 immune cell types in AEG samples obtained from the TCGA dataset (N=201). Patients were assigned into high- and low-immune infiltration subtypes based on the immune cell infiltration’s enrichment score. GSEA and mutation pattern analysis revealed that these two immune infiltration subtypes had distinct phenotypes. We identified 1470 differentially expressed lncRNAs in two immune infiltration subtypes. From these differentially expressed lncRNAs, six prognosis-related lncRNAs were selected using the Cox regression analysis. Subsequently, an immune risk signature was constructed based on combining the values of the six prognosis-associated lncRNAs expression levels and multiple regression coefficients. To determine the risk model’s prognostic capability, we performed a series of survival analyses with Kaplan–Meier methods, Cox proportional hazards regression models, and the area under receiver operating characteristic (ROC) curve. The results indicated that the immune-related risk signature could be an independent prognostic factor with a significant predictive value in patients with AEG. Furthermore, the immune-related risk signature can effectively predict the response to immunotherapy and chemotherapy in AEG patients. In conclusion, the proposed immune-related lncRNA prognostic signature is reliable and has high survival predictive value for patients with AEG and is a promising potential biomarker for immunotherapy.

Genomic Heterogeneity and Clonal Evolution in Gastroesophageal Junction Cancer Revealed by Single Cell DNA Sequencing

Gastroesophageal junction (GEJ) cancer is a tumor that occurs at the junction of stomach and esophagus anatomically. GEJ cancer frequently metastasizes to lymph nodes, however the heterogeneity and clonal evolution process are unclear. This study is the first of this kind to use single cell DNA sequencing to determine genomic variations and clonal evolution related to lymph node metastasis. Multiple Annealing and Looping Based Amplification Cycles (MALBAC) and bulk exome sequencing were performed to detect single cell copy number variations (CNVs) and single nucleotide variations (SNVs) respectively. Four GEJ cancer patients were enrolled with two (Pt.3, Pt.4) having metastatic lymph nodes. The most common mutation we found happened in the TTN gene, which was reported to be related with the tumor mutation burden in cancers. Significant intra-patient heterogeneity in SNVs and CNVs were found. We identified the SNV subclonal architecture in each tumor. To study the heterogeneity of CNVs, the single cells were sequenced. The number of subclones in the primary tumor was larger than that in lymph nodes, indicating the heterogeneity of primary site was higher. We observed two patterns of multi-station lymph node metastasis: one was skip metastasis and the other was to follow the lymphatic drainage. Taken together, our single cell genomic analysis has revealed the heterogeneity and clonal evolution in GEJ cancer.

A novel genomic classification system of gastric cancer via integrating multidimensional genomic characteristics

BACKGROUND

Gastric cancer (GC) is one of the leading causes of cancer deaths with high heterogeneity. There is currently a paucity of clinically applicable molecular classification system to guide precise medicine.

METHODS

A total of 70 Chinese patients with GC were included in this study and whole-exome sequencing was performed. Unsupervised clustering was undertaken to identify genomic subgroups, based on mutational signature, copy number variation, neoantigen, clonality, and essential genomic alterations. Subgroups were characterized by clinicopathological factors, molecular features, and prognosis.

RESULTS

We identified 32 significantly mutated genes (SMGs), including TP53, ARID1A, PIK3CA, CDH1, and RHOA. Of these, PREX2, PIEZO1, and FSIP2 have not been previously reported in GC. Using a novel genome-based classification method that integrated multidimensional genomic features, we categorized GC into four subtypes with distinct clinical phenotypes and prognosis. Subtype 1, which was predominantly Lauren intestinal type, harbored recurrent TP53 mutation and ERBB2 amplification, high tumor mutation burden (TMB)/tumor neoantigen burden (TNB), and intratumoral heterogeneity, with a liver metastasis tendency. Subtype 2 tended to occur at an elder age, accompanying with frequent TP53 and SYNE1 mutations, high TMB/TNB, and was associated with poor prognosis. Subtype 3 and subtype 4 included patients with mainly diffuse/mixed type tumors, high frequency of peritoneal metastasis, and genomical stability, whereas subtype 4 was associated with a favorable prognosis.

CONCLUSIONS

By integrating multidimensional genomic characteristics, we proposed a novel genomic classification system of GC associated with clinical phenotypes and provided a new insight to facilitate genome-guided risk stratification and disease management.