Dataset Information

Microenvironmental Heterogeneity Parallels Breast Cancer Progression: A Histology-Genomic Integration Analysis.

ABSTRACT:

Background

The intra-tumor diversity of cancer cells is under intense investigation; however, little is known about the heterogeneity of the tumor microenvironment that is key to cancer progression and evolution. We aimed to assess the degree of microenvironmental heterogeneity in breast cancer and correlate this with genomic and clinical parameters.

Methods and findings

We developed a quantitative measure of microenvironmental heterogeneity along three spatial dimensions (3-D) in solid tumors, termed the tumor ecosystem diversity index (EDI), using fully automated histology image analysis coupled with statistical measures commonly used in ecology. This measure was compared with disease-specific survival, key mutations, genome-wide copy number, and expression profiling data in a retrospective study of 510 breast cancer patients as a test set and 516 breast cancer patients as an independent validation set. In high-grade (grade 3) breast cancers, we uncovered a striking link between high microenvironmental heterogeneity measured by EDI and a poor prognosis that cannot be explained by tumor size, genomics, or any other data types. However, this association was not observed in low-grade (grade 1 and 2) breast cancers. The prognostic value of EDI was superior to known prognostic factors and was enhanced with the addition of TP53 mutation status (multivariate analysis test set, p = 9 × 10-4, hazard ratio = 1.47, 95% CI 1.17-1.84; validation set, p = 0.0011, hazard ratio = 1.78, 95% CI 1.26-2.52). Integration with genome-wide profiling data identified losses of specific genes on 4p14 and 5q13 that were enriched in grade 3 tumors with high microenvironmental diversity that also substratified patients into poor prognostic groups. Limitations of this study include the number of cell types included in the model, that EDI has prognostic value only in grade 3 tumors, and that our spatial heterogeneity measure was dependent on spatial scale and tumor size.

Conclusions

To our knowledge, this is the first study to couple unbiased measures of microenvironmental heterogeneity with genomic alterations to predict breast cancer clinical outcome. We propose a clinically relevant role of microenvironmental heterogeneity for advanced breast tumors, and highlight that ecological statistics can be translated into medical advances for identifying a new type of biomarker and, furthermore, for understanding the synergistic interplay of microenvironmental heterogeneity with genomic alterations in cancer cells.

SUBMITTER: Natrajan R

PROVIDER: S-EPMC4755617 | biostudies-literature | 2016 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Microenvironmental Heterogeneity Parallels Breast Cancer Progression: A Histology-Genomic Integration Analysis.

Natrajan Rachael R Sailem Heba H Mardakheh Faraz K FK Arias Garcia Mar M Tape Christopher J CJ Dowsett Mitch M Bakal Chris C Yuan Yinyin Y

PLoS medicine 20160216 2

<h4>Background</h4>The intra-tumor diversity of cancer cells is under intense investigation; however, little is known about the heterogeneity of the tumor microenvironment that is key to cancer progression and evolution. We aimed to assess the degree of microenvironmental heterogeneity in breast cancer and correlate this with genomic and clinical parameters.<h4>Methods and findings</h4>We developed a quantitative measure of microenvironmental heterogeneity along three spatial dimensions (3-D) in ...[more]

PMID: 26881778

Similar Datasets

Project description:Multifocal breast cancer (MFBC), defined as multiple synchronous unilateral lesions of invasive breast cancer, is relatively frequent and has been associated with more aggressive features than unifocal cancer. Here, we aimed to investigate the genomic heterogeneity between MFBC lesions sharing similar histopathological parameters. Characterization of different lesions from 36 patients with ductal MFBC involved the identification of non-silent coding mutations in 360 protein-coding genes (171 tumour and 36 matched normal samples). We selected only patients with lesions presenting the same grade, ER, and HER2 status. Mutations were classified as 'oncogenic' in the case of recurrent substitutions reported in COSMIC or truncating mutations affecting tumour suppressor genes. All mutations identified in a given patient were further interrogated in all samples from that patient through deep resequencing using an orthogonal platform. Whole-genome rearrangement screen was further conducted in 8/36 patients. Twenty-four patients (67%) had substitutions/indels shared by all their lesions, of which 11 carried the same mutations in all lesions, and 13 had lesions with both common and private mutations. Three-quarters of those 24 patients shared oncogenic variants. The remaining 12 patients (33%) did not share any substitution/indels, with inter-lesion heterogeneity observed for oncogenic mutation(s) in genes such as PIK3CA, TP53, GATA3, and PTEN. Genomically heterogeneous lesions tended to be further apart in the mammary gland than homogeneous lesions. Genome-wide analyses of a limited number of patients identified a common somatic background in all studied MFBCs, including those with no mutation in common between the lesions. To conclude, as the number of molecular targeted therapies increases and trials driven by genomic screening are ongoing, our findings highlight the presence of genomic inter-lesion heterogeneity in one-third, despite similar pathological features. This implies that deeper molecular characterization of all MFBC lesions is warranted for the adequate management of those cancers.

Project description:BACKGROUND:Endocrine FGF21 and FGF19 target adipocytes and hepatocytes through betaKlotho (KLB) and FGFR tyrosine kinases effecting glucose, lipid and energy metabolism. Both factors alleviate obesity and metabolic abnormalities which are contributing factors to breast tumor progression. Genomic manipulation of hepatic FGFR4 has uncovered roles of endocrine FGF signaling in both metabolic and cellular homeostasis. Here we determined whether systemic and microenvironmental metabolic alterations caused by the FGFR4 deficiency affect tumorigenesis in breast where FGFR4 is negligible. Breast tumors were induced in the bigenic mice with ablation of FGFR4 and overexpression of TGF? that activates Her2 in the ductal and lobular epithelium surrounded by adipocytes. Mammary tumorigenesis and alterations in systemic and breast microenvironmental metabolic parameters and regulatory pathways were analyzed. RESULTS:Ablation of FGFR4 had no effect on cellular homeostasis and Her2 activity of normal breast tissue. However, the absence of FGFR4 reduced TGF?-driven breast tumor incidence and progression and improved host survival. Notable increases in hepatic and serum FGF21, ileal FGF15/19, adiponectin and adipsin, and decreases in systemic Fetuin A, IGF-1, IGFBP-1, RBP4 and TIMP1 were observed. The ablation affected adipogenesis and secretory function of adipocytes as well as lipogenesis, glycolysis and energy homeostasis associated with the functions of mitochondria, ER and peroxisomes in the breast and tumor foci. Treatment with a chemical inhibitor of NAMPT involved in the pathways inhibited the growth and survival of breast tumor cells and tumor-initiating cell-containing spheres. The FGFR4 ablation also caused elevation of inflammatory factors in the breast. CONCLUSIONS:Although the primary role of FGFR4 in metabolism occurs in hepatocytes, its ablation results in a net inhibitory effect on mammary tumor progression. We suggest that the tumor-delaying effect of FGFR4 deficiency may be in large part due to elevated anti-obesogenic FGF21 that triggers tumor-suppressing signals from both peripheral and breast adipocytes. The predominant changes in metabolic pathways suggested roles of metabolic effects from both peripheral and breast adipocytes on metabolic reprogramming in breast epithelial cells that contribute to the suppression of tumor progression. These results provide new insights into the contribution of systemic and microenvironmental metabolic effects controlled by endocrine FGF signaling to breast carcinogenesis.

Project description:PurposeEarly detection of pancreatic ductal adenocarcinoma (PDAC) remains elusive. Precursor lesions of PDAC, specifically intraductal papillary mucinous neoplasms (IPMNs), represent a bona fide pathway to invasive neoplasia, although the molecular correlates of progression remain to be fully elucidated. Single-cell transcriptomics provides a unique avenue for dissecting both the epithelial and microenvironmental heterogeneities that accompany multistep progression from noninvasive IPMNs to PDAC.Experimental designSingle-cell RNA sequencing was performed through droplet-based sequencing on 5,403 cells from 2 low-grade IPMNs (LGD-IPMNs), 2 high-grade IPMNs (HGD-IPMN), and 2 PDACs (all surgically resected).ResultsAnalysis of single-cell transcriptomes revealed heterogeneous alterations within the epithelium and the tumor microenvironment during the progression of noninvasive dysplasia to invasive cancer. Although HGD-IPMNs expressed many core signaling pathways described in PDAC, LGD-IPMNs harbored subsets of single cells with a transcriptomic profile that overlapped with invasive cancer. Notably, a proinflammatory immune component was readily seen in low-grade IPMNs, composed of cytotoxic T cells, activated T-helper cells, and dendritic cells, which was progressively depleted during neoplastic progression, accompanied by infiltration of myeloid-derived suppressor cells. Finally, stromal myofibroblast populations were heterogeneous and acquired a previously described tumor-promoting and immune-evading phenotype during invasive carcinogenesis.ConclusionsThis study demonstrates the ability to perform high-resolution profiling of the transcriptomic changes that occur during multistep progression of cystic PDAC precursors to cancer. Notably, single-cell analysis provides an unparalleled insight into both the epithelial and microenvironmental heterogeneities that accompany early cancer pathogenesis and might be a useful substrate to identify targets for cancer interception.See related commentary by Hernandez-Barco et al., p. 2027.

Dataset Information

Microenvironmental Heterogeneity Parallels Breast Cancer Progression: A Histology-Genomic Integration Analysis.

Background

Methods and findings

Conclusions

Publications

Microenvironmental Heterogeneity Parallels Breast Cancer Progression: A Histology-Genomic Integration Analysis.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets