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Combining imaging- and gene-based hypoxia biomarkers in cervical cancer improves prediction of treatment failure independent of intratumor heterogeneity

ABSTRACT: Combining imaging- and gene-based hypoxia biomarkers in cervical cancer improves prediction of treatment failure independent of intratumor heterogeneity

PROVIDER: PRJNA609323 | ENA |

REPOSITORIES: ENA

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Combining imaging- and gene-based hypoxia biomarkers in cervical cancer improves prediction of treatment failure independent of intratumor heterogeneity

Project description:Emerging biomarkers based on medical images and molecular characterization of tumor biopsies open up for combining the two disciplines and exploiting their synergy in treatment planning. We compared pretreatment classification of cervical cancer patients by two previously validated imaging- and gene-based hypoxia biomarkers, evaluated the influence of intratumor heterogeneity, and investigated the benefit of combining them in prediction of treatment failure. The imaging-based biomarker was hypoxic fraction, determined from diagnostic dynamic contrast enhanced (DCE)-MR images. The gene-based biomarker was a hypoxia gene expression signature determined from tumor biopsies. Paired data were available for 118 patients. Intratumor heterogeneity was assessed by variance analysis of MR images and multiple biopsies from the same tumor. The two biomarkers were combined using a dimension-reduction procedure. The biomarkers classified 75% of the tumors with the same hypoxia status. Both intratumor heterogeneity and distribution pattern of hypoxia from imaging were unrelated to inconsistent classification by the two biomarkers, and the hypoxia status of the slice covering the biopsy region was representative of the whole tumor. Hypoxia by genes was independent on tumor cell fraction and showed minor heterogeneity across multiple biopsies in 9 tumors. This suggested that the two biomarkers could contain complementary biological information. Combination of the biomarkers into a composite score led to improved prediction of treatment failure (HR:7.3) compared to imaging (HR:3.8) and genes (HR:3.0) and prognostic impact in multivariate analysis with clinical variables. In conclusion, combining imaging- and gene-based biomarkers enables more precise and informative assessment of hypoxia-related treatment resistance in cervical cancer, independent of intratumor heterogeneity.

2020-06-26 | GSE146114 | GEO

Combining imaging- and gene-based hypoxia biomarkers in cervical cancer improves prediction of chemoradiotherapy failure independent of intratumour heterogeneity.

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Integrating imaging and RNA-seq improves outcome prediction in cervical cancer.

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Transcription profiling of human cervical cancer patient biopsies to explore intratumour heterogeneity reveals that intratumor variation is low for most probe sets tested but that multiple biopsies are recommended for reliable estimates of gene expression

Project description:To explore intratumor heterogeneity in gene expression profiles from patients with cervical cancer. Experimental Design: A total of 33 biopsies were obtained from 11 patients, sampling between two and five different areas for each tumor.The extracted RNA was hybridized onto the Affymetrix U133 Plus 2.0 oligonucleotide chip. The variance of expression within a patient (W), between patients (B) and the total variance (T =W + B) were calculated for each ProbeSet, and the ratio W/T was used as a measure of intratumor heterogeneity. Gene Ontology functional analysis was done to assess the function of genes that had high W/T (top 10%) and low W/T (bottom 10%) values.

2007-11-11 | E-GEOD-5787 | biostudies-arrayexpress

Characterization of spatial heterogeneity in metastasized colorectal cancer by MALDI imaging

Project description:About 50% of colorectal cancer patients develop liver metastases. Patients with metastatic colorectal cancer have 5-year survival rates below 20% despite new therapeutic regimens. Tumor heterogeneity has been linked with poor clinical outcome, but was so far mainly studied via bulk genomic analyses. In this study we performed spatial proteomics via MALDI mass spectrometry imaging on six patient matched CRC primary tumor and liver metastases to characterize interpatient, intertumor and intratumor hetereogeneity. We found several peptide features that were enriched in vital tumor areas of primary tumors and liver metastasis and tentatively derived from tumor cell specific proteins such as annexin A4 and prelamin A/C. Liver metastases of colorectal cancer showed higher heterogeneity between patients than primary tumors while within patients both entities show similar intratumor heterogeneity sometimes organized in zonal pattern. Together our findings give new insights into the spatial proteomic heterogeneity of primary CRC and patient matched liver metastases.

2023-02-17 | PXD039409 | Pride

Multiplexed protein and drug imaging by super-resolution ion beam imaging

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Multiplatform molecular profiling reveals epigenomic intratumor heterogeneity in ependymoma, DNA Methylation

Project description:Ependymomas exist within distinct genetic subgroups, but the molecular diversity within individual ependymomas is unknown. We performed multiplatform molecular profiling of 6 spatially-distinct samples from an ependymoma with C11orf95-RELA fusion. DNA methylation and RNA sequencing distinguished clusters of samples according to neuronal development gene expression programs that could also be delineated by differences in magnetic resonance blood perfusion. Exome sequencing and phylogenetic analysis revealed epigenomic intratumor heterogeneity, and suggested that chromosomal structural alterations may precede accumulation of single nucleotide variants during ependymoma tumorigenesis. In sum, these findings shed new light on the oncogenesis and intratumor heterogeneity of ependymoma.

2019-12-20 | GSE142320 | GEO

Spatially Annotated Single Cell Sequencing for Unraveling Intratumor Heterogeneity

Project description:Intratumor heterogeneity is a major obstacle to effective cancer treatment. Current methods to study intratumor heterogeneity using single-cell RNA sequencing (scRNAseq) lack information on the spatial organization of cells. While state-of-the art spatial transcriptomics methods capture the spatial distribution, they either lack single cell resolution or have relatively low transcript counts. Here, we introduce spatially annotated single cell sequencing, based on the previously developed functional single cell sequencing (FUNseq) technique, to spatially profile tumor cells with deep scRNA-seq and single cell resolution. Using our approach, we profiled cells located at different distances from the center of a 2D epithelial cell mass. By profiling the cell patch in concentric bands of varying width, we showed that cells at the outermost edge of the patch responded strongest to their local microenvironment, behaved most invasively, and activated the process of epithelial-to-mesenchymal transition (EMT) to migrate to lowconfluence areas. We inferred cell-cell communication networks and demonstrated that cells in the outermost ~10 cell wide band, which we termed the invasive edge, induced similar phenotypic plasticity in neighboring regions. Applying FUNseq to spatially annotate and profile tumor cells enables deep characterization of tumor subpopulations, thereby unraveling the mechanistic basis for intratumor heterogeneity.

2022-02-10 | GSE196245 | GEO

Combining gene signatures improves prediction of breast cancer survival.

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MR Imaging Distinguishes Tumor Hypoxia Levels of Different Prognostic and Biological Significance in Cervical Cancer

Project description:Tumor hypoxia levels range from mild to severe and have different biological and therapeutical consequences, but are not easily assessable in patients. We present a method based on diagnostic dynamic contrast enhanced (DCE) magnetic resonance imaging (MRI) that visualizes a continuous range of hypoxia levels in tumors of cervical cancer patients. Hypoxia images were generated using an established approach based on pixel-wise combination of the DCE-MRI parameters e and Ktrans, reflecting oxygen consumption and supply, respectively. An algorithm to retrieve hypoxia levels from the images was developed and validated in 28 xenograft tumors, by comparing the MRI-defined levels with hypoxia levels derived from pimonidazole stained histological sections. We further established an indicator of hypoxia levels in patient tumors based on expression of nine hypoxia responsive genes. A strong correlation was found between these indicator values and the MRI-defined hypoxia levels in 63 patients. Chemoradiotherapy outcome of 74 patients was most strongly predicted by moderate hypoxia levels, whereas more severe or milder levels were less predictive. By combining gene expression profiles and MRI-defined hypoxia levels in cancer hallmark analysis, we identified a distribution of levels associated with each hallmark; oxidative phosphorylation and G2/M checkpoint were associated with moderate hypoxia, and epithelial-to-mesenchymal transition and inflammatory responses with significantly more severe levels. At the mildest levels, interferon response hallmarks, together with stabilization of HIF1A protein by immunohistochemistry, appearred significant. Thus, our method visualizes the distribution of hypoxia levels within patient tumors and has potential to distinguish levels of different prognostic and biological significance.

2020-09-01 | GSE147384 | GEO

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