The Tumor Microenvironment Innately Modulates Cancer Progression

Hinshaw, Dominique C.; Shevde, Lalita A.

doi:10.1158/0008-5472.can-18-3962

Cited by 2,188 publications

(1,854 citation statements)

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“…A large body of literature now provides numerous examples of stromal influence on malignant cell function 25,26 , confirming more than a century of speculation about the critical role of the stroma 1 . However, our knowledge remains largely anecdotal and based mostly on work in animal models rather than human subjects.…”

Section: Discussionmentioning

confidence: 93%

“…During the past two decades numerous studies have revealed interactions between malignant cells and the stroma that promote diverse tumor functions including angiogenesis 4,5 , metastasis 6 , and immunosuppression 7,8 . Stromal cells differ between patients and tumor types [9][10][11][12][13][14][15] and the abundance of certain stromal cell populations are used in the clinic as biomarkers [16][17][18][19] and therapeutic targets [20][21][22][23][24][25] . These studies motivate direct measurements of cell types and the interactions between them in human subjects.…”

Section: Introductionmentioning

confidence: 99%

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Bayesian cell-type deconvolution and gene expression inference reveals tumor-microenvironment interactions

Chu

Danko

2020

Preprint

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Understanding the dynamic interactions between malignant cells and the tumor stroma is a major goal of cancer research. Here we developed a Bayesian model that jointly infers both cellular composition and gene expression in each cell type, including heterogeneous malignant cells, from bulk RNA-seq using scRNA-seq as prior information. We conducted an integrative analysis of 85 single-cell and 1,412 bulk RNA-seq datasets in primary human glioblastoma, head and neck squamous cell carcinoma, and melanoma. We identified cell types correlated with clinical outcomes and explored regional heterogeneity in tumor state and stromal composition. We redefined common molecular subtypes using gene expression in malignant cells, after excluding confounding non-malignant cell types. Finally, we identified genes whose expression in malignant cells correlated with infiltration of macrophages, T-cells, fibroblasts, and endothelial cells across multiple tumor types. Our work provides a new lens that we used to measure cellular composition and expression in a statistically powered cohort of three primary human malignancies. Results Bayesian inference of cell type composition and tumor expressionTED uses a scRNA-seq reference dataset to infer two parameters of interest from bulk RNA-seq data: (i) the proportion of cell types in the bulk population and (ii) the average expression profiles of each cell type. TED describes the proportion and expression profiles of each cell type as latent variables that it infers from the data ( Fig. 1a, Supplementary Fig. 1, Supplementary Note 1). TED makes the key simplifying assumption that each non-malignant cell type shares a common gene expression profile across patients, as observed in the cases analyzed to date 28,30,31 .Critically, each bulk RNA-seq sample is then assumed to have a unique tumor expression profile that we infer from the data.Expression in the reference and bulk RNA-seq data often differ substantially due to batch effects or tumor heterogeneity. To account for uncertainty in the reference cell type expression matrix, TED implements a fully Bayesian inference of tumor composition. First, TED uses Gibbs sampling to estimate the posterior joint distribution of cell type composition, θ0, and gene expression profiles, Z, i.e. P(θ0, Z | φ, X; α) ( Fig. 1a, red, top). Second, to account for tumor cells, or other cell types which cannot be observed in the reference dataset, TED infers a maximum likelihood estimate (MLE) for tumor expression profiles, ψtum (Fig. 1a, red, mid). During this step TED also infers the maximum a posterior estimate (MAP) of the expression profile of non-malignant stromal cells, ψstr, to correct for batch effects between bulk and single cell RNAseq platforms. Last, TED uses the updated expression profile for each patient and cell type to resample the posterior distribution of cell type composition, θ, i.e. P(θ | ψtum , ψstr ,X; α) ( Fig. 1a, red, bottom). Optionally, TED has an additional mode which can be used to learn common patterns of expression heterogeneit...

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Section: Discussionmentioning

confidence: 93%

Section: Introductionmentioning

confidence: 99%

Bayesian cell-type deconvolution and gene expression inference reveals tumor-microenvironment interactions

Chu

Danko

2020

Preprint

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“…The tumor microenvironment (TME) is defined as the totality of normal cells, molecules and blood vessels surrounding and feeding each cancer cell [146]. TME cells are stromal cells, immune-inflammatory cells and vascular endothelial cells.…”

Section: Resveratrol and Cancer Evidencementioning

confidence: 99%

Resveratrol in Cancer Patients: From Bench to Bedside

Berretta

Bignucolo

Francia

et al. 2020

IJMS

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Resveratrol (3,5, is a natural phytoalexin that accumulates in several vegetables and fruits like nuts, grapes, apples, red fruits, black olives, capers, red rice as well as red wines. Being both an extremely reactive molecule and capable to interact with cytoplasmic and nuclear proteins in human cells, resveratrol has been studied over the years as complementary and alternative medicine (CAM) for the therapy of cancer, metabolic and cardiovascular diseases like myocardial ischemia, myocarditis, cardiac hypertrophy and heart failure. This review will describe the main biological targets, cardiovascular outcomes, physico-chemical and pharmacokinetic properties of resveratrol in preclinical and clinical models implementing its potential use in cancer patients.properties of resveratrol are, however, marked by a pharmacokinetic profile and by an unfavorable oral bioavailability, which requires a thorough analysis. To date, to the best of our knowledge, scientific papers and reviews summarizing multiple characteristics of resveratrol, its pharmacokinetic, pharmacodynamic profiles and potential drug interaction in oncology are lacking in literature. Therefore, this review aimed to describe the potential use of resveratrol in cancer management presenting the main biochemical pathways involved, issues and potential uses in cancer patients. Moreover, the involvement of resveratrol in cardioncology, its potential use for risk reduction of myocardial ischemia, myocarditis, cardiac hypertrophy as well as heart failure are also discussed. To endorse this review, we made a comprehensive search on PubMed, Web of Science and SciFinder. The search terms were "resveratrol" combined with "cardioncology" or "cancer" or "drug-food" or "cardiology" or "pharmacokinetic" or "pharmacodynamic". Physico-Chemical and Pharmacokinetic Properties of ResveratrolResveratrol is a low molecular weight phyto-polyphenol of 228 Da that appears as an off-white powder with lipophilic properties (octanol/water partition coefficient, log Kow = 3.1). Its melting point is between 253 and 255 • C, and its solubility in water is very low (3 mg/100 mL) [8]. The ethylene bridge due to a limited degree of freedom generates two geometric isomers: cis-resveratrol and trans-resveratrol ( Figure 1) [5]. These isoforms co-exist in resveratrol extracts even if a greater biological activity and stability are attributed to trans-resveratrol. Comparing to the geometric isomers, the nearly planar structure of trans-resveratrol is less flexible than the non-planar structure of cis-resveratrol, but it possesses a lower repulsive energy that ensures it, albeit small, higher stability. Isomerization of trans-resveratrol to cis-resveratrol occurs via molecule breakdown when trans-resveratrol is exposed to UV radiation at a wavelength of 254 or 366 nm, to high pH conditions or in plants during fermentation processes [5,9]. In analyzing some physical-chemical aspects of resveratrol, Zupancic et al. showed how trans-resveratrol is rapidly degradable in high-pH solutions. In par...

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“…However, the tumor microenvironment is formed from more than just tumor cells, and also includes stromal cells and infiltrating cells of the innate and adaptive immune system, which are likely to also be affected by PARP inhibition. These cells communicate with each other through direct contact and/or indirect signals that can alter the functionality of immune cells so that they either favor or limit tumor growth [10,11]. Emerging evidence supporting the immunomodulatory roles of PARP-1 and PARP-2 has raised the prospect of harnessing PARP inhibition to not only target the cancer itself, but also therapeutically modify its microenvironment.…”

Section: Introductionmentioning

confidence: 99%

Immunomodulatory Roles of PARP-1 and PARP-2: Impact on PARP-Centered Cancer Therapies

Yélamos

Moreno-Lama

Jimeno

et al. 2020

Cancers

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Poly(ADP-ribose) polymerase-1 (PARP-1) and PARP-2 are enzymes which posttranslationally modify proteins through poly(ADP-ribosyl)ation (PARylation)-the transfer of ADP-ribose chains onto amino acid residues-with a resultant modulation of protein function. Many targets of PARP-1/2-dependent PARylation are involved in the DNA damage response and hence, the loss of these proteins disrupts a wide range of biological processes, from DNA repair and epigenetics to telomere and centromere regulation. The central role of these PARPs in DNA metabolism in cancer cells has led to the development of PARP inhibitors as new cancer therapeutics, both as adjuvant treatment potentiating chemo-, radio-, and immuno-therapies and as monotherapy exploiting cancer-specific defects in DNA repair. However, a cancer is not just made up of cancer cells and the tumor microenvironment also includes multiple other cell types, particularly stromal and immune cells. Interactions between these cells-cancerous and non-cancerous-are known to either favor or limit tumorigenesis. In recent years, an important role of PARP-1 and PARP-2 has been demonstrated in different aspects of the immune response, modulating both the innate and adaptive immune system. It is now emerging that PARP-1 and PARP-2 may not only impact cancer cell biology, but also modulate the anti-tumor immune response. Understanding the immunomodulatory roles of PARP-1 and PARP-2 may provide invaluable clues to the rational development of more selective PARP-centered therapies which target both the cancer and its microenvironment.

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The Tumor Microenvironment Innately Modulates Cancer Progression

Cited by 2,188 publications

References 100 publications

Bayesian cell-type deconvolution and gene expression inference reveals tumor-microenvironment interactions

Bayesian cell-type deconvolution and gene expression inference reveals tumor-microenvironment interactions

Resveratrol in Cancer Patients: From Bench to Bedside

Immunomodulatory Roles of PARP-1 and PARP-2: Impact on PARP-Centered Cancer Therapies

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