Two distinct phenotypes of immunologically hot gastric cancer subtypes
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ABSTRACT:
SUBMITTER: Saito N
PROVIDER: S-EPMC8579120 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundOvarian cancer (OC) is a highly heterogeneous and malignant gynecological cancer, thereby leading to poor clinical outcomes. The study aims to identify and characterize clinically relevant subtypes in OC and develop a diagnostic model that can precisely stratify OC patients, providing more diagnostic clues for OC patients to access focused therapeutic and preventative strategies.MethodsGene expression datasets of OC were retrieved from TCGA and GEO databases. To evaluate immune cell infiltration, the ESTIMATE algorithm was applied. A univariate Cox analysis and the two-sided log-rank test were used to screen OC risk factors. We adopted the ConsensusClusterPlus algorithm to determine OC subtypes. Enrichment analysis based on KEGG and GO was performed to determine enriched pathways of signature genes for each subtype. The machine learning algorithm, support vector machine (SVM) was used to select the feature gene and develop a diagnostic model. A ROC curve was depicted to evaluate the model performance.ResultsA total of 1,273 survival-related genes (SRGs) were firstly determined and used to clarify OC samples into different subtypes based on their different molecular pattern. SRGs were successfully stratified in OC patients into three robust subtypes, designated S-I (Immunoreactive and DNA Damage repair), S-II (Mixed), and S-III (Proliferative and Invasive). S-I had more favorable OS and DFS, whereas S-III had the worst prognosis and was enriched with OC patients at advanced stages. Meanwhile, comprehensive functional analysis highlighted differences in biological pathways: genes associated with immune function and DNA damage repair including CXCL9, CXCL10, CXCL11, APEX, APEX2, and RBX1 were enriched in S-I; S-II combined multiple gene signatures including genes associated with metabolism and transcription; and the gene signature of S-III was extensively involved in pathways reflecting malignancies, including many core kinases and transcription factors involved in cancer such as CDK6, ERBB2, JAK1, DAPK1, FOXO1, and RXRA. The SVM model showed superior diagnostic performance with AUC values of 0.922 and 0.901, respectively. Furthermore, a new dataset of the independent cohort could be automatically analyzed by this innovative pipeline and yield similar results.ConclusionThis study exploited an innovative approach to construct previously unexplored robust subtypes significantly related to different clinical and molecular features for OC and a diagnostic model using SVM to aid in clinical diagnosis and treatment. This investigation also illustrated the importance of targeting innate immune suppression together with DNA damage in OC, offering novel insights for further experimental exploration and clinical trial.
| S-EPMC10740166 | biostudies-literature
Project description:Background: Iron is an essential nutrient involved in the redox cycle and the formation of free radicals. The reprogramming of iron metabolism is the main link to tumor cell survival. Ferroptosis is an iron-dependent form of regulated cell death associated with cancer; the characteristics of ferroptosis in cancers are still uncertain. This study aimed to explore the application value and gender difference of ferroptosis in prognosis and immune prediction to provide clues for targeted therapy of gastric cancer. Methods: We comprehensively evaluated the ferroptosis levels of 1,404 gastric cancer samples from six independent GC cohorts based on ferroptosis-related specific genes and systematically correlated ferroptosis with immune cell infiltrating and gender characteristics. The ferroptosis score was constructed to quantify the ferroptosis levels of individual tumors using principal component analysis (PCA) algorithms. Results: We identified two distinct ferroptosis subtypes in gastric cancer, namely Subtype-A and Subtype-B. We found that male patients in Subtype-B had the worst prognosis in contrast with the other groups. Three sex hormone receptors (AR, ER, and PR) in Subtype-B tumor patients were higher than in Subtype-A tumor patients in GC, while the HER2 displayed an opposite trend. We developed a risk model termed ferroptosis score to evaluate ferroptosis levels within individual tumors. The low-ferroptosis score group was characterized by activation of immune cells and increased mutation burden, which is also linked to increased neoantigen load and enhanced response to anti-PD-1/L1 immunotherapy. The patients with a low-ferroptosis score showed a high microsatellite instability status (MSI-H) and had a higher response to immunotherapy. Furthermore, the patients with low-ferroptosis scores have a lower estimated IC50 in the several chemotherapy drugs, including paclitaxel, gemcitabine, and methotrexate. Conclusions: We revealed that sex hormone receptors and immune cell infiltration were markedly different between ferroptosis subtypes in GC patients. The results suggested that gender difference may be critical when the ferroptosis-related strategy is applied in GC treatment. Further, ferroptosis levels were identified with an extreme variety of prognosis and tumor immune characteristics, which might benefit GC individualized treatment.
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Project description:In Western countries the majority of gastric cancers (GC) are usually diagnosed in advanced stages reporting a 5-year survival rate of only 26%. The Laurén classification of GC was most widely used in clinical practice since it reflects GC morphology, epidemiology, tumor biology, clinical management and outcome. Despite the initial promise of individualizing antitumor treatment, the management of GC still remains relatively broad and general. Apart from clinical staging, molecular profiling enables targeting of the identified underlying alterations, rather than histology. In contrast to breast carcinoma, molecular classification of GC does not yet imply treatment modality. Molecular classifications of GC and their therapeutic implications are therefore extensively studied. The current proposed molecular divisions of GC come from three different parts of the world where different standard treatment modalities for advanced GC are recommended. Wider use of GC molecular subtyping may solve problems, such as susceptibility to novel systemic therapy regimens or selection of patients for aggressive surgery and targeted adjuvant/conversion therapy. In any case, the rapid entry of novel molecular targeted therapies into routine oncology practice clearly underscores the urgent need for clinicians to be aware of these new possibilities.
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Project description:Global investigation of histone marks in acute myeloid leukemia (AML) remains limited. Analyses of 38 AML samples through integrated transcriptional and chromatin mark analysis exposes 2 major subtypes. One subtype is dominated by patients with NPM1 mutations or MLL-fusion genes, shows activation of the regulatory pathways involving HOX-family genes as targets, and displays high self-renewal capacity and stemness. The second subtype is enriched for RUNX1 or spliceosome mutations, suggesting potential interplay between the 2 aberrations, and mainly depends on IRF family regulators. Cellular consequences in prognosis predict a relatively worse outcome for the first subtype. Our integrated profiling establishes a rich resource to probe AML subtypes on the basis of expression and chromatin data.
| S-EPMC6363099 | biostudies-literature
Project description:Gastric cancer is the fifth most common type of human cancer and the third leading cause of cancer-related death. The purpose of this study is to investigate the immune infiltration signatures of gastric cancer and their relation to prognosis. We identified two distinct subtypes of gastric cancer (C1/C2) characterized by different immune infiltration signatures. C1 is featured by immune resting, epithelial-mesenchymal transition, and angiogenesis pathways, while C2 is featured by enrichment of the MYC target, oxidative phosphorylation, and E2F target pathways. The C2 subtype has a better prognosis than the C1 subtype (HR = 0.61, 95% CI: 0.44-0.85; log-rank test, p = 0.0029). The association of C1/C2 with prognosis remained statistically significant (HR = 0.62, 95% CI: 0.44-0.87; p = 0.006) after controlling for age, gender, and stage. The prognosis prediction of C1/C2 was verified in four independent cohorts (including an internal cohort). In summary, our study is helpful for better understanding of the association between immune infiltration and the prognosis of gastric cancer.
| S-EPMC8802764 | biostudies-literature
Project description:Homologous recombination repair deficiency (HRD) is observed in 10% of patients with castrate-resistant prostate cancer (PCa). Preliminary data suggest that HRD-PCa might be more responsive to immune checkpoint inhibitors (ICIs). In this study, we compare the tumor immune landscape and peripheral T cell receptor (TCR) repertoire of patients with and without HRD-PCa to gain further insight into the immunogenicity of HRD-PCa. Immunohistochemistry was performed on tumor tissue of 81 patients, including 15 patients with HRD-PCa. Peripheral TCR sequencing was performed in a partially overlapping cohort of 48 patients, including 16 patients with HRD-PCa. HRD patients more frequently had intratumoral CD3+, CD3+CD8-FoxP3- or Foxp3+ TILs above median compared to patients without DNA damage repair alterations (DDRwt; CD3+ and Foxp3+: 77% vs 35%, p = .013; CD3+CD8-FoxP3-: 80% vs 44%, p = .031). No significant difference in CD8+ TILs or PD-L1 expression was observed. In peripheral blood, HRD patients displayed a more diverse TCR repertoire compared to DDRwt patients (p = .014). Additionally, HRD patients shared TCR clusters with low generation probability, suggesting patient-overlapping T cell responses. A pooled analysis of clinical data from 227 patients with molecularly characterized PCa suggested increased efficacy of ICIs in HRD-PCa. In conclusion, patients with HRD-PCa display increased TIL density and an altered peripheral TCR repertoire. Further research into the efficacy of ICIs and the presence of shared neoantigens in HRD-PCa is warranted.
| S-EPMC9255222 | biostudies-literature
Project description:Purpose: To identify novel breast cancer subtypes by extracting quantitative imaging phenotypes of the tumor and surrounding parenchyma and to elucidate the underlying biologic underpinnings and evaluate the prognostic capacity for predicting recurrence-free survival (RFS).Experimental Design: We retrospectively analyzed dynamic contrast-enhanced MRI data of patients from a single-center discovery cohort (n = 60) and an independent multicenter validation cohort (n = 96). Quantitative image features were extracted to characterize tumor morphology, intratumor heterogeneity of contrast agent wash-in/wash-out patterns, and tumor-surrounding parenchyma enhancement. On the basis of these image features, we used unsupervised consensus clustering to identify robust imaging subtypes and evaluated their clinical and biologic relevance. We built a gene expression-based classifier of imaging subtypes and tested their prognostic significance in five additional cohorts with publically available gene expression data but without imaging data (n = 1,160).Results: Three distinct imaging subtypes, that is, homogeneous intratumoral enhancing, minimal parenchymal enhancing, and prominent parenchymal enhancing, were identified and validated. In the discovery cohort, imaging subtypes stratified patients with significantly different 5-year RFS rates of 79.6%, 65.2%, 52.5% (log-rank P = 0.025) and remained as an independent predictor after adjusting for clinicopathologic factors (HR, 2.79; P = 0.016). The prognostic value of imaging subtypes was further validated in five independent gene expression cohorts, with average 5-year RFS rates of 88.1%, 74.0%, 59.5% (log-rank P from <0.0001 to 0.008). Each imaging subtype was associated with specific dysregulated molecular pathways that can be therapeutically targeted.Conclusions: Imaging subtypes provide complimentary value to established histopathologic or molecular subtypes and may help stratify patients with breast cancer. Clin Cancer Res; 23(13); 3334-42. ©2017 AACR.
| S-EPMC5496801 | biostudies-literature
Project description:BackgroundDeregulated gene expression is a hallmark of cancer; however, most studies to date have analyzed short-read RNA sequencing data with inherent limitations. Here, we combine PacBio long-read isoform sequencing (Iso-Seq) and Illumina paired-end short-read RNA sequencing to comprehensively survey the transcriptome of gastric cancer (GC), a leading cause of global cancer mortality.ResultsWe performed full-length transcriptome analysis across 10 GC cell lines covering four major GC molecular subtypes (chromosomal unstable, Epstein-Barr positive, genome stable and microsatellite unstable). We identify 60,239 non-redundant full-length transcripts, of which > 66% are novel compared to current transcriptome databases. Novel isoforms are more likely to be cell line and subtype specific, expressed at lower levels with larger number of exons, with longer isoform/coding sequence lengths. Most novel isoforms utilize an alternate first exon, and compared to other alternative splicing categories, are expressed at higher levels and exhibit higher variability. Collectively, we observe alternate promoter usage in 25% of detected genes, with the majority (84.2%) of known/novel promoter pairs exhibiting potential changes in their coding sequences. Mapping these alternate promoters to TCGA GC samples, we identify several cancer-associated isoforms, including novel variants of oncogenes. Tumor-specific transcript isoforms tend to alter protein coding sequences to a larger extent than other isoforms. Analysis of outcome data suggests that novel isoforms may impart additional prognostic information.ConclusionsOur results provide a rich resource of full-length transcriptome data for deeper studies of GC and other gastrointestinal malignancies.
| S-EPMC7821541 | biostudies-literature
Project description:Modulators in ubiquitin-proteasome system (UPS) has been implicated in regulating cancer-related genes, immune responses, and oncogenesis. However, the global UPS expression pattern and its role in gastric cancer (GC) pathology remain elusive. Herein, we integrated the modulators in UPS and dissected their associations with tumor microenvironment (TME), therapeutic response and prognosis in GC. Ten eligible GC cohorts (n = 2161) were collected in this comprehensive analysis. Unsupervised clustering based on expression profile of ubiquitination regulators was performed to identify distinct expression pattern. Then, pathway activation, and TME characteristics and prognosis were explored for patients in each pattern. Finally, a UPS scoring system in GC, termed UPSGC, is developed for individualized quantification of UPS expression pattern. Two prognosis-distinctive UPS expression patterns were identified and validated. Multiple interdependent characteristics were found in each pattern. Patients in the pattern with poor prognosis were found with activation of EMT, TNFα/NF-κB and IL6/JAK/STAT3 signaling, and more infiltration of immunosuppressive M2 macrophages and Th2 cells in TME. And another pattern was characterized by upregulation of angiogenesis, Notch and Wnt-β/catenin signaling, as well as enrichment of microvessels in TME. Based on the UPSGC system, two pattern-related clinical subtypes were identified. Finally, the UPSGC subtypes were validated as robust biomarker to predict patient's therapeutic responses and survival outcomes. In conclusion, this study proposes two previously unexplored UPS expression patterns in GC, in which patients have distinct survival outcomes and molecular characteristics. The findings provide new evidences to support the clinical relevance of ubiquitination with personalized therapy.
| S-EPMC10074993 | biostudies-literature
Project description:Despite continual efforts to develop prognostic and predictive models of colorectal cancer by using clinicopathological and genetic parameters, a clinical test that can discriminate between patients with good or poor outcome after treatment has not been established. Thus, the authors aim to uncover subtypes of colorectal cancer that have distinct biological characteristics associated with prognosis and identify potential biomarkers that best reflect the biological and clinical characteristics of subtypes.Unsupervised hierarchical clustering analysis was applied to gene expression data from 177 patients with colorectal cancer to determine a prognostic gene expression signature. Validation of the signature was sought in two independent patient groups. The association between the signature and prognosis of patients was assessed by Kaplan-Meier plots, log-rank tests and the Cox model.The authors identified a gene signature that was associated with overall survival and disease-free survival in 177 patients and validated in two independent cohorts of 213 patients. In multivariate analysis, the signature was an independent risk factor (HR 3.08; 95% CI 1.33 to 7.14; p=0.008 for overall survival). Subset analysis of patients with AJCC (American Joint Committee on Cancer) stage III cancer revealed that the signature can also identify the patients who have better outcome with adjuvant chemotherapy (CTX). Adjuvant chemotherapy significantly affected disease-free survival in patients in subtype B (3-year rate, 71.2% (CTX) vs 41.9% (no CTX); p=0.004). However, such benefit of adjuvant chemotherapy was not significant for patients in subtype A.The gene signature is an independent predictor of response to chemotherapy and clinical outcome in patients with colorectal cancer.
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