Computational Image Analysis Identifies Histopathological Image Features Associated With Somatic Mutations and Patient Survival in Gastric Adenocarcinoma.
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ABSTRACT:
SUBMITTER: Cheng J
PROVIDER: S-EPMC8045755 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundGastric cancer is one of the leading cancer types in incidence and mortality, especially in Asia. In order to improve survival, identification of a catalogue of molecular alterations underlying gastric cancer is a critical step for developing and designing genome-directed therapies.Methodology/principal findingsThe Center for Cancer Genome Discovery (CCGD) at the Dana-Farber Cancer Institute (DFCI) has adapted a high-throughput genotyping platform to determine the mutation status of a large panel of known cancer genes. The mutation detection platform, termed OncoMap v4, interrogates 474 "hotspot" mutations in 41 genes that are relevant for cancer. We performed OncoMap v4 in formalin-fixed paraffin-embedded (FFPE) tissue specimens from 237 gastric adenocarcinomas. Using OncoMap v4, we found that 34 (14.4%) of 237 gastric cancer patients harbored mutations. Among mutations we screened, PIK3CA mutations were the most frequent (5.1%) followed by p53 (4.6%), APC (2.5%), STK11 (2.1%), CTNNB1 (1.7%), and CDKN2A (0.8%). Six samples harbored concomitant somatic mutations. Mutations of CTNNB1 were significantly more frequent in EBV-associated gastric carcinoma (P = 0.046). Our study led to the detection of potentially druggable mutations in gastric cancer which may guide novel therapies in subsets of gastric cancer patients.Conclusions/significanceUsing high throughput mutation screening platform, we identified that PIK3CA mutations were the most frequently observed target for gastric adenocarcinoma.
| S-EPMC3377730 | biostudies-literature
Project description:Peritoneal metastasis occurs in more than half of patients with unresectable or recurrent gastric cancer and is associated with the worst prognosis. The associated genomic events and pathogenesis remain ambiguous. The aim of the present study was to characterize the mutation spectrum of gastric cancer with peritoneal metastasis and provide a basis for the identification of new biomarkers and treatment targets. Matched pairs of normal gastric mucosa and peritoneal tissue and matched pairs of primary tumor and peritoneal metastasis were collected from one patient for whole-exome sequencing (WES); Sanger sequencing was employed to confirm the somatic mutations. G>A and C>T mutations were the two most frequent transversions among the somatic mutations. We confirmed 48somatic mutations in the primary site and 49 in the peritoneal site. Additionally, 25 non-synonymous somatic variations (single-nucleotide variants, SNVs) and 2 somatic insertions/deletions (INDELs) were confirmed in the primary tumor, and 30 SNVs and 5 INDELs were verified in the peritoneal metastasis. Approximately 59% of the somatic mutations were shared between the primary and metastatic site. Five genes (TP53, BAI1, THSD1, ARID2, and KIAA2022) verified in our study were also mutated at a frequency greater than 5%in the COSMIC database. We also identified 9genes (ERBB4, ZNF721, NT5E, PDE10A, CA1, NUMB, NBN, ZFYVE16, and NCAM1) that were only mutated in metastasis and are expected to become treatment targets. In conclusion, we observed that the majority of the somatic mutations in the primary site persisted in metastasis, whereas several single-nucleotide polymorphisms occurred de novo at the second site.
| S-EPMC5190066 | biostudies-other
Project description:BackgroundBoth histopathological image features and genomics data were associated with survival outcome of cancer patients. However, integrating features of histopathological images, genomics and other omics for improving prognosis prediction has not been reported in head and neck squamous cell carcinoma (HNSCC).MethodsA dataset of 216 HNSCC patients was derived from the Cancer Genome Atlas (TCGA) with information of clinical characteristics, genetic mutation, RNA sequencing, protein expression and histopathological images. Patients were randomly assigned into training (n = 108) or validation (n = 108) sets. We extracted 593 quantitative image features, and used random forest algorithm with 10-fold cross-validation to build prognostic models for overall survival (OS) in training set, then compared the area under the time-dependent receiver operating characteristic curve (AUC) in validation set.ResultsIn validation set, histopathological image features had significant predictive value for OS (5-year AUC = 0.784). The histopathology + omics models showed better predictive performance than genomics, transcriptomics or proteomics alone. Moreover, the multi-omics model incorporating image features, genomics, transcriptomics and proteomics reached the maximal 1-, 3-, and 5-year AUC of 0.871, 0.908, and 0.929, with most significant survival difference (HR = 10.66, 95%CI: 5.06-26.8, p < 0.001). Decision curve analysis also revealed a better net benefit of multi-omics model.ConclusionThe histopathological images could provide complementary features to improve prognostic performance for HNSCC patients. The integrative model of histopathological image features and omics data might serve as an effective tool for survival prediction and risk stratification in clinical practice.
| S-EPMC7658095 | biostudies-literature
Project description:BackgroundGastric and gastro-esophageal junction cancers (GCs) frequently recur after resection, but markers to predict recurrence risk are missing. T-cell infiltrates have been validated as prognostic markers in other cancer types, but not in GC because of methodological limitations of past studies. We aimed to define and validate the prognostic role of major T-cell subtypes in GC by objective computational quantification.MethodsSurgically resected chemotherapy-naïve GCs were split into discovery (n = 327) and validation (n = 147) cohorts. CD8 (cytotoxic), CD45RO (memory), and FOXP3 (regulatory) T-cell densities were measured through multicolor immunofluorescence and computational image analysis. Cancer-specific survival (CSS) was assessed. All statistical tests were two-sided.ResultsCD45RO-cell and FOXP3-cell densities statistically significantly predicted CSS in both cohorts. Stage, CD45RO-cell, and FOXP3-cell densities were independent predictors of CSS in multivariable analysis; mismatch repair (MMR) and Epstein-Barr virus (EBV) status were not statistically significant. Combining CD45RO-cell and FOXP3-cell densities into the Stomach Cancer Immune Score showed highly statistically significant (all P ≤ .002) CSS differences (0.9 years median CSS to not reached). T-cell infiltrates were highest in EBV-positive GCs and similar in MMR-deficient and MMR-proficient GCs.ConclusionThe validation of CD45RO-cell and FOXP3-cell densities as prognostic markers in GC may guide personalized follow-up or (neo)adjuvant treatment strategies. Only those 20% of GCs with the highest T-cell infiltrates showed particularly good CSS, suggesting that a small subgroup of GCs is highly immunogenic. The potential for T-cell densities to predict immunotherapy responses should be assessed. The association of high FOXP3-cell densities with longer CSS warrants studies into the biology of regulatory T cells in GC.
| S-EPMC7781469 | biostudies-literature
Project description:BackgroundActivation of the phosphatidylinositol 3-kinase (PI3K) through mutational inactivation of PTEN tumour suppressor gene is common in diverse cancer types, but rarely reported in gastric cancer. Recently, mutations in PIK3CA, which encodes the p110alpha catalytic subunit of PI3K, have been identified in various human cancers, including 3 of 12 gastric cancers. Eighty percent of these reported mutations clustered within 2 regions involving the helical and kinase domains. In vitro study on one of the "hot-spot" mutants has demonstrated it as an activating mutation.MethodsBased on these data, we initiated PIK3CA mutation screening in 94 human gastric cancers by direct sequencing of the gene regions in which 80% of all the known PIK3CA mutations were found. We also examined PIK3CA expression level by extracting data from the previous large-scale gene expression profiling study. Using Significance Analysis of Microarrays (SAM), we further searched for genes that show correlating expression with PIK3CA.ResultsWe have identified PIK3CA mutations in 4 cases (4.3%), all involving the previously reported hotspots. Among these 4 cases, 3 tumours demonstrated microsatellite instability and 2 tumours harboured concurrent KRAS mutation. Data extracted from microarray studies showed an increased expression of PIK3CA in gastric cancers when compared with the non-neoplastic gastric mucosae (p < 0.001). SAM further identified 2910 genes whose expression levels were positively associated with that of PIK3CA.ConclusionOur data suggested that activation of the PI3K signalling pathway in gastric cancer may be achieved through up-regulation or mutation of PIK3CA, in which the latter may be a consequence of mismatch repair deficiency.
| S-EPMC1079799 | biostudies-literature
Project description:Determining the genetic basis of cancer requires comprehensive analyses of large collections of histopathologically well-classified primary tumours. Here we report the results of a collaborative study to discover somatic mutations in 188 human lung adenocarcinomas. DNA sequencing of 623 genes with known or potential relationships to cancer revealed more than 1,000 somatic mutations across the samples. Our analysis identified 26 genes that are mutated at significantly high frequencies and thus are probably involved in carcinogenesis. The frequently mutated genes include tyrosine kinases, among them the EGFR homologue ERBB4; multiple ephrin receptor genes, notably EPHA3; vascular endothelial growth factor receptor KDR; and NTRK genes. These data provide evidence of somatic mutations in primary lung adenocarcinoma for several tumour suppressor genes involved in other cancers--including NF1, APC, RB1 and ATM--and for sequence changes in PTPRD as well as the frequently deleted gene LRP1B. The observed mutational profiles correlate with clinical features, smoking status and DNA repair defects. These results are reinforced by data integration including single nucleotide polymorphism array and gene expression array. Our findings shed further light on several important signalling pathways involved in lung adenocarcinoma, and suggest new molecular targets for treatment.
| S-EPMC2694412 | biostudies-literature
Project description:We characterized the mutational landscape of melanoma, the form of skin cancer with the highest mortality rate, by sequencing the exomes of 147 melanomas. Sun-exposed melanomas had markedly more ultraviolet (UV)-like C>T somatic mutations compared to sun-shielded acral, mucosal and uveal melanomas. Among the newly identified cancer genes was PPP6C, encoding a serine/threonine phosphatase, which harbored mutations that clustered in the active site in 12% of sun-exposed melanomas, exclusively in tumors with mutations in BRAF or NRAS. Notably, we identified a recurrent UV-signature, an activating mutation in RAC1 in 9.2% of sun-exposed melanomas. This activating mutation, the third most frequent in our cohort of sun-exposed melanoma after those of BRAF and NRAS, changes Pro29 to serine (RAC1(P29S)) in the highly conserved switch I domain. Crystal structures, and biochemical and functional studies of RAC1(P29S) showed that the alteration releases the conformational restraint conferred by the conserved proline, causes an increased binding of the protein to downstream effectors, and promotes melanocyte proliferation and migration. These findings raise the possibility that pharmacological inhibition of downstream effectors of RAC1 signaling could be of therapeutic benefit.
| S-EPMC3432702 | biostudies-literature
Project description:BackgroundLung adenocarcinoma (LUAD) is the most common histologic subtype of lung cancer and has a high risk of distant metastasis at every disease stage. We aimed to characterize the genomic landscape of LUAD and identify mutation signatures associated with tumor progression.Methods and findingsWe performed an integrative genomic analysis, incorporating whole exome sequencing (WES), determination of DNA copy number and DNA methylation, and transcriptome sequencing for 101 LUAD samples from the Environment And Genetics in Lung cancer Etiology (EAGLE) study. We detected driver genes by testing whether the nonsynonymous mutation rate was significantly higher than the background mutation rate and replicated our findings in public datasets with 724 samples. We performed subclonality analysis for mutations based on mutant allele data and copy number alteration data. We also tested the association between mutation signatures and clinical outcomes, including distant metastasis, survival, and tumor grade. We identified and replicated two novel candidate driver genes, POU class 4 homeobox 2 (POU4F2) (mutated in 9 [8.9%] samples) and ZKSCAN1 (mutated in 6 [5.9%] samples), and characterized their major deleterious mutations. ZKSCAN1 was part of a mutually exclusive gene set that included the RTK/RAS/RAF pathway genes BRAF, EGFR, KRAS, MET, and NF1, indicating an important driver role for this gene. Moreover, we observed strong associations between methylation in specific genomic regions and somatic mutation patterns. In the tumor evolution analysis, four driver genes had a significantly lower fraction of subclonal mutations (FSM), including TP53 (p = 0.007), KEAP1 (p = 0.012), STK11 (p = 0.0076), and EGFR (p = 0.0078), suggesting a tumor initiation role for these genes. Subclonal mutations were significantly enriched in APOBEC-related signatures (p < 2.5×10-50). The total number of somatic mutations (p = 0.0039) and the fraction of transitions (p = 5.5×10-4) were associated with increased risk of distant metastasis. Our study's limitations include a small number of LUAD patients for subgroup analyses and a single-sample design for investigation of subclonality.ConclusionsThese data provide a genomic characterization of LUAD pathogenesis and progression. The distinct clonal and subclonal mutation signatures suggest possible diverse carcinogenesis pathways for endogenous and exogenous exposures, and may serve as a foundation for more effective treatments for this lethal disease. LUAD's high heterogeneity emphasizes the need to further study this tumor type and to associate genomic findings with clinical outcomes.
| S-EPMC5140047 | biostudies-literature
Project description:Perioperative chemotherapy enhances the survival rates for patients with esophageal and gastric (EG) adenocarcinoma, but not all patients benefit from this additional treatment. Chemotherapeutic agents have been demonstrated to alter the immune cell (IC) composition in the tumor microenvironment. Hence, there is a rationale to investigate the influence of neoadjuvant chemotherapy (NAC) on different IC subsets, to better understand and compare their utility as complementary prognostic or predictive biomarkers in a clinically relevant context. The density of T cells (CD8+ and FoxP3+), B cells (CD20+) and the expression of PD-L1 on ICs and tumor cells (TC) was assessed by immunohistochemistry on paired biopsies from primary tumors (PT) pre-NAC, and resected PT and lymph node metastases post-NAC. The cohort encompasses 148 patients with resectable EG adenocarcinoma, all of whom received NAC. The density of CD8+ cells was decreased and the density of FoxP3+ cells and CD20+ cells was increased in PT post-NAC. PD-L1 expression was not altered following NAC. In pre-NAC specimens, high FoxP3+ density and high PD-L1 expression on ICs were favorable prognostic factors, whereas high CD8+ density was an unfavorable prognostic factor. In post-NAC specimens, however, high FoxP3+ density was an unfavorable prognostic factor, and high PD-L1 expression on TC was associated with a shorter survival. There were no significant associations between IC density or PD-L1 expression in PT pre-NAC and histopathological regression. These findings propose that NAC might alter the density and prognostic impact of some IC subsets in EG adenocarcinoma.
| S-EPMC8158033 | biostudies-literature
Project description:IntroductionMR imaging can noninvasively visualize tumor phenotype characteristics at the macroscopic level. Here, we investigated whether somatic mutations are associated with and can be predicted by MRI-derived tumor imaging features of glioblastoma (GBM).MethodsSeventy-six GBM patients were identified from The Cancer Imaging Archive for whom preoperative T1-contrast (T1C) and T2-FLAIR MR images were available. For each tumor, a set of volumetric imaging features and their ratios were measured, including necrosis, contrast enhancing, and edema volumes. Imaging genomics analysis assessed the association of these features with mutation status of nine genes frequently altered in adult GBM. Finally, area under the curve (AUC) analysis was conducted to evaluate the predictive performance of imaging features for mutational status.ResultsOur results demonstrate that MR imaging features are strongly associated with mutation status. For example, TP53-mutated tumors had significantly smaller contrast enhancing and necrosis volumes (p = 0.012 and 0.017, respectively) and RB1-mutated tumors had significantly smaller edema volumes (p = 0.015) compared to wild-type tumors. MRI volumetric features were also found to significantly predict mutational status. For example, AUC analysis results indicated that TP53, RB1, NF1, EGFR, and PDGFRA mutations could each be significantly predicted by at least one imaging feature.ConclusionMRI-derived volumetric features are significantly associated with and predictive of several cancer-relevant, drug-targetable DNA mutations in glioblastoma. These results may shed insight into unique growth characteristics of individual tumors at the macroscopic level resulting from molecular events as well as increase the use of noninvasive imaging in personalized medicine.
| S-EPMC4648958 | biostudies-literature