Intratumor graph neural network recovers hidden prognostic value of multi-biomarker spatial heterogeneity.
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ABSTRACT:
SUBMITTER: Qiu L
PROVIDER: S-EPMC9307796 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Esophageal squamous cell carcinoma (ESCC) is among the most common malignancies, but little is known about the spatial intratumor heterogeneity (ITH) and the temporal clonal evolutionary processes in this cancer. Interestingly, the epigenetic profiling also showed strong evidence of spatial ITH, and the phyloepigenetic trees were extremely similar with the phylogenetic ones, indicating the interplay and co-dependency of genetic and epigenetic alterations in ESCC. We found that several genes were both mutated and hypermethylated at their promoters, such as ASXL1 and EPHA7. Our integrated investigations of the spatial ITH and the temporal clonal evolution might provide insights into developing biomarkers for early diagnosis of ESCC, as well as personalized therapeutic targets for treating this malignancy. DNA methylation profiles of 12 tumor regions and 2 matched normal esophageal epithelial tissues from three M-WES-examined ESCC cases (ESCC01, ESCC03 and ESCC05) were performed using Illumina Infinium HumanMethylation450K platform (Illumina, San Diego, CA) at the Epigenome Center of University of Southern California.
2016-08-20 | E-GEOD-79366 | biostudies-arrayexpress
Project description:Different aspects of intra-tumor heterogeneity (ITH), which are associated with development of cancer and its response to treatment, have postulated prognostic value. Here we searched for the potential association between phenotypic ITH analyzed by mass spectrometry imaging (MSI) and the prognosis of head and neck cancer. The study involved tissue specimens resected from 77 patients with locally advanced oral squamous cell carcinoma, including 37 patients where matched samples of primary tumor and synchronous lymph node metastases were analyzed. A 3-year follow-up was available for all patients that enabled their separation into two groups: with no evidence of disease (NED, n=41) and with progressive disease (PD, n=36). After the on-tissue trypsin digestion, peptide maps of all cancer regions were segmented using an unsupervised approach to reveal their intrinsic heterogeneity. We found that intra-tumor similarity of spectra was higher in the PD group and diversity of clusters identified during image segmentation was higher in the NED group, which indicated a higher level of ITH in patients with more favorable outcomes. Furthermore, signature of molecular components that correlated with long-term outcomes could be associated with proteins involved in the immune functions. Hence, we proposed that a higher level of ITH revealed by MSI in cancers with a better prognosis could reflect the presence of heterotypic components of tumor microenvironment such as infiltrating immune cells enhancing the response to the treatment. LC-MALDI-MS/MS data deposited in this repository originate from protein lysates obtained from FFPE sections consecutive to sections dedicated to MSI measurements. The hypothetical identity of the MSI components was established by assignment of a component location on the m/z scale for the measured masses of tryptic peptides identified by LC-MALDI-MS/MS allowing ±0.05% mass tolerance.
2022-10-13 | PXD034958 | Pride
Project description:Different aspects of intra-tumor heterogeneity (ITH), which are associated with the development of cancer and its response to treatment, have postulated prognostic value. Here we searched for potential association between phenotypic ITH analyzed by mass spectrometry imaging (MSI) and prognosis of head and neck cancer. The study involved tissue specimens resected from 77 patients with locally advanced oral squamous cell carcinoma, including 37 patients where matched samples of primary tumor and synchronous lymph node metastases were analyzed. A 3-year follow-up was available for all patients which enabled their separation into two groups: with no evidence of disease (NED, n = 41) and with progressive disease (PD, n = 36). After on-tissue trypsin digestion, peptide maps of all cancer regions were segmented using an unsupervised approach to reveal their intrinsic heterogeneity. We found that intra-tumor similarity of spectra was higher in the PD group and diversity of clusters identified during image segmentation was higher in the NED group, which indicated a higher level of ITH in patients with more favorable outcomes. Signature of molecular components that correlated with long-term outcomes could be associated with proteins involved in the immune functions. Furthermore, a positive correlation between ITH and histopathological lymphocytic host response was observed. Hence, we proposed that a higher level of ITH revealed by MSI in cancers with a better prognosis could reflect the presence of heterotypic components of tumor microenvironment such as infiltrating immune cells enhancing the response to the treatment.
| S-EPMC9458238 | biostudies-literature
Project description:PurposeIntratumor metabolic heterogeneity parameters on 18F-2-fluoro-2-deoxy-D-glucose (18F-FDG) positron emission tomography-computed tomography (PET-CT) have been proven to be predictors of the clinical prognosis of cancer patients. The study aimed to examine the correlation between 18F-FDG PET-CT-defined heterogeneity parameters and the prognostic significance in patients with colorectal cancer.MethodsThe study included 188 patients with colorectal cancer who received surgery and 18F-FDG PET/CT examinations. Preoperative 18F-FDG PET/CT conventional and metabolic heterogeneity parameters were collected, including maximum, peak, and mean standardized uptake value (SUVmax, SUVpeak, and SUVmean), metabolic tumor volume (MTV), total lesion glycolysis (TLG), heterogeneity index-1 (HI-1) and heterogeneity index-2 (HI-2), and clinicopathological information. Correlations between these parameters and patient survival outcomes were inferred.ResultsThe associations between 18F-FDG PET/CT parameters and clinical outcomes were analyzed. Tumor thrombus (P < 0.001), tumor stage (P=0.001), MTV (P=0.003), HI-1 (P=0.032), and HI-2 (P=0.001) differed between the two groups with and without recurrence. Multivariate analysis showed that, in the radical surgery group, HI-2 (HR = 1.10, 95% CI: 1.04-1.17, P=0.001), tumor stage (HR = 20.65, 95% CI: 4.81-88.62, P < 0.001), and regional lymph nodes status (HR = 0.16, 95% CI: 0.04-0.57, P=0.005) were independent variables significantly correlated with progression-free survival (PFS) and HI-2 (HR = 1.16, 95% CI: 1.07-1.26, P < 0.001) was an independent variable affecting overall survival (OS). In the palliative surgery group, HI-2 (HR = 1.03, 95% CI: 1.01-1.06, P=0.020) was an independent variable affecting PFS, and all the parameters were not statistically significant for OS.ConclusionHI-2, tumor stage, and regional lymph nodes status might predict the outcomes of colorectal cancer more effectively than other 18F-FDG PET/CT defined parameters.
| S-EPMC8818395 | biostudies-literature
Project description:Tumor genetic heterogeneity may underlie poor clinical outcomes because diverse subclones could be comprised of metastatic and drug resistant cells. Targeted deep sequencing has been used widely as a diagnostic tool to identify actionable mutations in cancer patients. In this study, we evaluated the clinical utility of estimating tumor heterogeneity using targeted panel sequencing data. We investigated the prognostic impact of a tumor heterogeneity (TH) index on clinical outcomes, using mutational profiles from targeted deep sequencing data acquired from 1,352 patients across 8 cancer types. The TH index tended to be increased in high pathological stage disease in several cancer types, indicating clonal expansion of cancer cells as tumor progression proceeds. In colorectal cancer patients, TH index values also correlated significantly with clinical prognosis. Integration of the TH index with genomic and clinical features could improve the power of risk prediction for clinical outcomes. In conclusion, deep sequencing to determine the TH index could serve as a promising prognostic indicator in cancer patients.
| S-EPMC6418103 | biostudies-literature
Project description:BackgroundThe prognosis of adrenocortical carcinoma (ACC) is heterogeneous. Genomic studies have identified ACC subgroups characterized by specific molecular alterations, including features measured at DNA level (somatic mutations, chromosome alterations, DNA methylation), which are closely associated with outcome. The aim of this study was to evaluate intratumor heterogeneity of prognostic molecular markers at the DNA level.MethodsTwo different tissue samples (primary tumor, local recurrence or metastasis) were analyzed in 26 patients who underwent surgery for primary or recurrent ACC. DNA-related biomarkers with prognostic role were investigated in frozen and paraffin-embedded samples. Somatic mutations of p53/Rb and Wnt/β-catenin pathways were assessed using next-generation sequencing (n = 26), chromosome alteration profiles were determined using SNP arrays (n = 14) and methylation profiles were determined using four-gene bisulfite pyrosequencing (n = 12).ResultsSomatic mutations for ZNRF3, TP53, CTNN1B and CDKN2A were found in 7, 6, 6 and 4 patients, respectively, with intratumor heterogeneity in 8/26 patients (31%). Chromosome alteration profiles were 'Noisy' (numerous and anarchic alterations) in 8/14 and 'Chromosomal' (extended patterns of loss of heterozygosity) in 5/14 of the study samples. For these profiles, no intratumor heterogeneity was observed. Methylation profiles were hypermethylated in 5/12 and non-hypermethylated in 7/12 of the study samples. Intratumor heterogeneity of methylation profiles was observed in 2/12 patients (17%).ConclusionsIntratumor heterogeneity impacts DNA-related molecular markers. While somatic mutation can differ, prognostic DNA methylation and chromosome alteration profile seem rather stable and might be more robust for the prognostic assessment.
| S-EPMC7424337 | biostudies-literature
Project description:The interpatient variability of tumor proteomes has been investigated on a large scale but many tumors display also intratumoral heterogeneity regarding morphological and genetic features. It remains largely unknown to what extent the local proteome of tumors intrinsically differs. Here, we used hepatocellular carcinoma as a model system to quantify both inter- and intratumor heterogeneity across human patient specimens with spatial resolution. We defined proteomic features that distinguish neoplastic from the directly adjacent nonneoplastic tissue, such as decreased abundance of NADH dehydrogenase complex I. We then demonstrated the existence of intratumoral variations in protein abundance that re-occur across different patient samples, and affect clinically relevant proteins, even in the absence of obvious morphological differences or genetic alterations. Our work demonstrates the suitability and the benefits of using mass spectrometry-based proteomics to analyze diagnostic tumor specimens with spatial resolution. Data are available via ProteomeXchange with identifier PXD007052.
| S-EPMC5880102 | biostudies-literature
Project description:As tumors accumulate genetic alterations, an evolutionary process occurs in which genetically distinct subclonal populations of cells co-exist, resulting in intratumor genetic heterogeneity (ITH). The clinical implications of ITH remain poorly defined. Data are limited with respect to whether ITH is an independent determinant of patient survival outcomes, across different cancer types. Here, we report the results of a pan-cancer analysis of over 3300 tumors, showing a varied landscape of ITH across 9 cancer types. While some gene mutations are subclonal, the majority of driver gene mutations are clonal events, present in nearly all cancer cells. Strikingly, high levels of ITH are associated with poorer survival across diverse types of cancer. The adverse impact of high ITH is independent of other clinical, pathologic and molecular factors. High ITH tends to be associated with lower levels of tumor-infiltrating immune cells, but this association is not able to explain the observed survival differences. Together, these data show that ITH is a prognostic marker in multiple cancers. These results illuminate the natural history of cancer evolution, indicating that tumor heterogeneity represents a significant obstacle to cancer control.
| S-EPMC4891103 | biostudies-other
Project description:PurposeProbe-based dynamic (4-D) imaging modalities capture breast intratumor heterogeneity both spatially and kinetically. Characterizing heterogeneity through tumor sub-populations with distinct functional behavior may elucidate tumor biology to improve targeted therapy specificity and enable precision clinical decision making.MethodsWe propose an unsupervised clustering algorithm for 4-D imaging that integrates Markov-Random Field (MRF) image segmentation with time-series analysis to characterize kinetic intratumor heterogeneity. We applied this to dynamic FDG PET scans by identifying distinct time-activity curve (TAC) profiles with spatial proximity constraints. We first evaluated algorithm performance using simulated dynamic data. We then applied our algorithm to a dataset of 50 women with locally advanced breast cancer imaged by dynamic FDG PET prior to treatment and followed to monitor for disease recurrence. A functional tumor heterogeneity (FTH) signature was then extracted from functionally distinct sub-regions within each tumor. Cross-validated time-to-event analysis was performed to assess the prognostic value of FTH signatures compared to established histopathological and kinetic prognostic markers.ResultsAdding FTH signatures to a baseline model of known predictors of disease recurrence and established FDG PET uptake and kinetic markers improved the concordance statistic (C-statistic) from 0.59 to 0.74 (p = 0.005). Unsupervised hierarchical clustering of the FTH signatures identified two significant (p < 0.001) phenotypes of tumor heterogeneity corresponding to high and low FTH. Distributions of FDG flux, or Ki, were significantly different (p = 0.04) across the two phenotypes.ConclusionsOur findings suggest that imaging markers of FTH add independent value beyond standard PET imaging metrics in predicting recurrence-free survival in breast cancer and thus merit further study.
| S-EPMC8421450 | biostudies-literature
Project description:Spatially resolved transcriptomics performs high-throughput measurement of transcriptomes while preserving spatial information about the cellular organizations. However, many spatially resolved transcriptomic technologies can only distinguish spots consisting of a mixture of cells instead of working at single-cell resolution. Here, we present STdGCN, a graph neural network model designed for cell type deconvolution of spatial transcriptomic (ST) data that can leverage abundant single-cell RNA sequencing (scRNA-seq) data as reference. STdGCN is the first model incorporating the expression profiles from single cell data as well as the spatial localization information from the ST data for cell type deconvolution. Extensive benchmarking experiments on multiple ST datasets showed that STdGCN outperformed 14 published state-of-the-art models. Applied to a human breast cancer Visium dataset, STdGCN discerned spatial distributions between stroma, lymphocytes and cancer cells for tumor microenvironment dissection. In a human heart ST dataset, STdGCN detected the changes of potential endothelial-cardiomyocyte communications during tissue development.
| S-EPMC10274700 | biostudies-literature