Enhancing Immunotherapy Outcomes: Spatial Multi-Omics Predictive Models for Non-Small Cell Lung Cancer
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ABSTRACT:
PROVIDER: PRJNA1132922 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR29733500_1.fastq.gz | Fastqsanger.gz | |||
| SRR29733500_2.fastq.gz | Fastqsanger.gz | |||
| SRR29733600_1.fastq.gz | Fastqsanger.gz | |||
| SRR29733600_2.fastq.gz | Fastqsanger.gz | |||
| SRR29733700_1.fastq.gz | Fastqsanger.gz |
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Project description:Background: A pressing challenge in treating non-small cell lung cancer (NSCLC) lies in the significant variability of patient responses to immunotherapy. This issue underscores the critical need for innovative predictive models that can navigate beyond conventional biomarkers to enhance patient outcomes, particularly by addressing immunotherapy resistance or responsiveness. Hypothesis: We hypothesize that an integrated multi-omics approach will uncover interactions within the NSCLC tumor immune microenvironment (TIME) and identify novel biomarkers that are predictive of individual immunotherapy responses, thus aiding in the development of a robust personalized treatment planning model. Objective: To develop a predictive model for NSCLC immunotherapy response/resistance by identifying new biomarkers using co-detection by indexing (CODEX) and Digital Spatial Profiling of whole transcriptome atlas (DSP-WTA). Methods: We utilized a multi-omics approach, combining CODEX for spatial mapping of protein expression at the single-cell level and DSP-WTA for comprehensive transcriptomic insights from the cell types identified by CODEX. This methodology facilitated a detailed examination of the TIME in NSCLC samples from patients undergoing first-line immunotherapy. Results: Our analysis identified three cell types, proliferating tumor cells, granulocytes, and vessels, that are associated with resistance to immunotherapy. The high proportion of these cell types demonstrated a hazard ratio (HR) of 3.8 (p = 0.004) in the training cohort (N = 33) and 1.8 (p = 0.05) in the validation cohort (N = 35). In the response cell type model, higher levels of M1 macrophages, M2 macrophages, and CD4 T cells returned a HR of 0.4 (p = 0.019) in the training set and 0.49 (p = 0.036) in the validation set. Gene signatures related to these cell types also predicted outcomes with high accuracy. The resistant gene model, which included 8 genes associated with epithelial-mesenchymal transition (EMT) and cell migration showed a HR of 5.3 (p < 0.001) in the training set and 2.2 (p = 0.036) in the validation set. The response gene model, consisting of 8 genes associated with immunomodulation, had an HR of 0.22 (p = 0.005) in the training set and 0.38 (p = 0.034) in the validation set. Conclusion: This research highlights the potential of a multi-omics strategy in advancing NSCLC treatment toward precision oncology. By offering insights into the TIME and unveiling novel biomarkers, our model seeks to define resistance and to improve prediction of response to treatment.
2024-08-22 | GSE271689 | GEO
Project description:Full title: Predictive Gene Signatures as Strong Prognostic Indicators of the Effectiveness of Bacillus Calmetteâ??Guérin (BCG) Immunotherapy in Primary pT1 Bladder Cancers Intravesical BCG immunotherapy is effective in prevention of recurrence and progression in many cases of non-muscle invasive bladder cancer, but many patients fail to respond. This study identified predictive gene signatures in primary pT1 bladder cancer with BCG immunotherapy. Fourty-Eight patients with primary pT1 bladder cancer treated with BCG immunotherapy were used. Microarray gene expression analysis of the 48 primary bladder cancers was carried out. Predictive gene signatures were individually selected based on the recurrence and progression status. Among 43,148 unique genes, 424 and 287 candidate predictive genes that could predict recurrence and progression, respectively, were selected. Time to recurrence or progression was shorter for patients with poor-predictive gene signatures than good-predictive gene signatures (log-rank test, p <0.001, respectively). Validation of predictive gene signatures with RT-PCR was nearly identical to those of microarray (log-rank test, p <0.05, respectively). In multivariate regression analysis, predictive gene signatures were the only independent predictors of recurrence (HR 3.38, p = 0.048) or progression (HR 10.49, p = 0.048) in validation cohorts. Predictive gene signatures have strong diagnostic value for determining the response to intravesical BCG immunotherapy in primary pT1 bladder cancer. Keywords: Gene expression, Bladder cancer, BCG Total RNA, extracted from the fresh frozen tissues of 48 pT1 bladder cancers, was isolated by TRIzol reagent (Life Technologies, NY, USA), according to the manufacturer's protocol. The quality and integrity of the RNA were confirmed by agarose gel electrophoresis and ethidium bromide staining, followed by visual examination under ultraviolet light. Five-hundred nanograms of total RNA were used for labeling hybridization according to the manufacturerâ??s protocol (Illumina HumanWG-6 BeadChip, version 2, Illumina, Inc., San Diego, CA, USA). Arrays were scanned with an Illumina Bead Array Reader confocal scanner (BeadStation 500GXDW; Illumina, Inc.) according to the manufacturer's instructions. Initial microarray gene expression data were obtained using Bead Studio software with gene expression analysis module (version 3.1.3, Illumina, Inc.).
2010-04-07 | E-GEOD-19423 | biostudies-arrayexpress
Project description:Full title: Predictive Gene Signatures as Strong Prognostic Indicators of the Effectiveness of Bacillus Calmette–Guérin (BCG) Immunotherapy in Primary pT1 Bladder Cancers Intravesical BCG immunotherapy is effective in prevention of recurrence and progression in many cases of non-muscle invasive bladder cancer, but many patients fail to respond. This study identified predictive gene signatures in primary pT1 bladder cancer with BCG immunotherapy. Fourty-Eight patients with primary pT1 bladder cancer treated with BCG immunotherapy were used. Microarray gene expression analysis of the 48 primary bladder cancers was carried out. Predictive gene signatures were individually selected based on the recurrence and progression status. Among 43,148 unique genes, 424 and 287 candidate predictive genes that could predict recurrence and progression, respectively, were selected. Time to recurrence or progression was shorter for patients with poor-predictive gene signatures than good-predictive gene signatures (log-rank test, p <0.001, respectively). Validation of predictive gene signatures with RT-PCR was nearly identical to those of microarray (log-rank test, p <0.05, respectively). In multivariate regression analysis, predictive gene signatures were the only independent predictors of recurrence (HR 3.38, p = 0.048) or progression (HR 10.49, p = 0.048) in validation cohorts. Predictive gene signatures have strong diagnostic value for determining the response to intravesical BCG immunotherapy in primary pT1 bladder cancer. Keywords: Gene expression, Bladder cancer, BCG
2010-03-26 | GSE19423 | GEO
Project description:ICLIC-MS for Enhancing Outcomes Research and Clinical Care in Multiple Sclerosis
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Project description:Lack of reliable predictive biomarkers is a major limitation of combination therapy with chemotherapy and anti-PD-1 therapy (chemo-immunotherapy). The increase of peripheral blood (PB) CD8+ T cells expressing CX3CR1, a marker of differentiation, correlates with response to anti-PD-1 therapy; however, the predictive and prognostic value of T-cell CX3CR1 expression during chemo-immunotherapy remains elusive. Here, we evaluated the utility of PB CX3CR1+CD8+ T cells as a predictive correlate of response to chemo-immunotherapy in non-small cell lung cancer (NSCLC) patients. At least 10% increase of the CX3CR1+ subset in circulating CD8+ T cells from baseline (CX3CR1 score) was associated with response to chemo-immunotherapy at 6 weeks (p = 0.0382) and 9 weeks (p = 0.0045). Sensitivity, specificity, positive and negative predictive value of at least 10% increase of the CX3CR1 score was 83.3%, 88.2%, 83.3% and 88.2%, respectively with 86.2% overall accuracy of predicting response at 9 weeks. Furthermore, at least 10% increase of the CX3CR1 score correlated with improved overall (p = 0.0105) and progression-free survival (p = 0.0265). Combined T-cell receptor (TCR) sequencing of tumor tissue and single-cell RNA/TCR sequencing of longitudinal PB samples from a patient who received a long-term benefit from chemo-immunotherapy demonstrated that circulating clonally expanded CD8+ T cells were terminal effector T cells expressing high levels of CX3CR1, and contained frequent tumor-infiltrating T-cell colonotypes early-on post treatment. Collectively, these findings suggest the potential utility of T-cell CX3CR1 expression as a dynamic blood-based biomarker during the course of chemo-immunotherapy and a marker to identify frequent tumor-infiltrating lymphocyte repertoires.
2023-04-05 | GSE213902 | GEO
Project description:TREM2 blockade modifies the tumor myeloid landscape enhancing anti-PD-1 immunotherapy
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Project description:Predictive Biomarkers for the Responsiveness of Recurrent Glioblastomas to Activated Killer Cell Immunotherapy
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Project description:Purpose: The efficacy of immunomodulators in improving pregnancy outcomes in infertile patients is controversial, with some reports finding improvements in pregnancy outcomes and some studies finding lack of efficacy in unselected patient populations. Therefore, the aim of this study was to identify people who could benefit from immunotherapy. Methods: 29 patients who had at least one previous embryo transfer failure and planned to undergo another frozen-thawed embryo transfer (FET) cycle were included. Peripheral blood of the patients was collected for detection of serum cytokines, T cell subsets at D3-D9 days of menstrual cycle before FET, mRNA was extracted from endometrial tissues during the window of implantation (WOI) for analysis. All patients began treatment with immunomodulators, including prednisone, hydroxychloroquine, cyclosporine, on the first day of the FET cycle. They were divided into pregnant group and non-pregnant group according to clinical pregnancy. Results: There were no differences in cytokines and T cell subsets between the two groups. Functional annotation of endometrial mRNA revealed functional enrichment in leucocyte mediated immunity, innate immune response, regulation of T cell receptor (TCR) signaling, T cell activation and positive T cell selection. Conclusion: The cytokines and immune cell subsets of peripheral blood cannot accurately predict the outcome of pregnancy after immunotherapy, and endometrial biopsy on the WOI may be a target to identify people who benefit from immunotherapy.
2024-09-09 | GSE272778 | GEO
Project description:Purpose: To evaluate the presence of a gene expression signature present before treatment as predictive of response to treatment with MAGEâA3 immunotherapeutic in metastatic melanoma patients and to validate its predictivity in adjuvant therapy of early-stage lung cancer. Patients were participants in two Phase II studies of the recombinant MAGEâA3 antigen combined with immunological adjuvants. mRNA from tumor samples (biopsies) collected before MAGE-A3 immunotherapy was analyzed by microarray hybridization and by quantitative polymerase chain reaction (qRT-PCR). The melanoma microarray dataset was used to discover and crossvalidate a gene expression signature and classifier discriminative of Responders (R) versus Non-Responders (NR) patients; the gene signature and classifier were then applied to an adjuvant lung cancer study. Patients that were not included for analysis are denoted as NE (Non-evaluable). GSK Biologicals
2013-05-30 | E-GEOD-35640 | biostudies-arrayexpress
Project description:Immune checkpoint inhibitors (ICI) produce durable responses in some melanoma patients, but many patients derive no clinical benefit, and the molecular underpinnings of such resistance remain elusive. Here, we leveraged single-cell RNA-seq (scRNA-seq) from 31 melanoma tumors and novel computational methods to interrogate malignant cell states that promote immune evasion. We identified a resistance program expressed by malignant cells that is associated with T cell exclusion and immune evasion. The program is present prior to immunotherapy, characterizes cold niches, and predicts clinical responses to anti-PD-1 therapy in an independent cohort of 112 melanoma patients. CDK4/6-inhibition represses this program in individual malignant cells, induces senescence, and reduces melanoma tumor outgrowth in a mouse model when given in combination with immunotherapy. Our study provides a high-resolution landscape of ICI resistant cell states, identifies clinically predictive signatures, and forms a basis for the development of novel therapeutic strategies that could overcome immunotherapy resistance.
2018-11-01 | GSE115978 | GEO