Targeting tumoral hypoxia: finding opportunity in complexity

Quantification of Tumor Hypoxia through Unsupervised Modelling of Consumption and Supply Hypoxia MR Imaging in Breast Cancer

Simple Summary

Hypoxia in solid tumors is common in most solid cancers and is associated with treatment resistance to both chemo- and radiation-therapy. There is also reason to believe that hypoxia is an important determinant of metastic disease. Identifying hypoxia in solid tumors is important in treatment planning and decision making. In 2018 Hompland et al. proposed a method, based on quantifying consumption and supply of oxygen from diffusion weighted magnetic resonance imaging, to estimate the hypoxic fraction of a solid tumor. The method was based on training model parameters on a known hypoxia state in prostate cancer. In the present study we verified the validity of the consumption and supply concept in breast cancer. Furthermore, we developed and validated a new approach to the concept that does not require a ground truth to train the parameters.

Abstract

The purpose of the present study is to investigate if consumption and supply hypoxia (CSH) MR-imaging can depict breast cancer hypoxia, using the CSH-method initially developed for prostate cancer. Furthermore, to develop a generalized pan-cancer application of the CSH-method that doesn’t require a hypoxia reference standard for training the CSH-parameters. In a cohort of 69 breast cancer patients, we generated, based on the principles of intravoxel incoherent motion modelling, images reflecting cellular density (apparent diffusion coefficient; ADC) and vascular density (perfusion fraction; fp). Combinations of the information in these images were compared to a molecular hypoxia score made from gene expression data, aiming to identify a way to apply the CSH-methodology in breast cancer. Attempts to adapt previously proposed models for prostate cancer included direct transfers and model parameter rescaling. A novel approach, based on rescaling ADC and fp data to give more nuanced response in the relevant physiologic range, was also introduced. The new CSH-method was validated in a prostate cancer cohort with known hypoxia status. The proposed CSH-method gave estimates of hypoxia that was strongly correlated to the molecular hypoxia score in breast cancer, and hypoxia as measured in pathology slices stained with pimonidazole in prostate cancer. The generalized approach to CSH-imaging depicted hypoxia in both breast and prostate cancers and requires no model training. It is easy to implement using readily available technology and encourages further investigation of CSH-imaging in other cancer entities and in other settings, with the goal being to overcome hypoxia-induced resistance to treatment.

Intratumoral heterogeneity and hypoxia gene expression signatures: Is a single biopsy adequate?

•

A single biopsy may not accurately reflect the global hypoxia status of a tumor due to intratumoral heterogeneity.

•

Compared with individual genes, hypoxia gene expression signatures are generally more consistent across multiple biopsies from different regions of a tumor and may give a more reliable estimate of global hypoxia status.

•

Wherever possible, the use of multiple biopsies provides greater assurance in correctly classifying a tumor as more or less hypoxic.

Background and Purpose

Gene expression signatures are often used to identify hypoxic tumors. However, intratumoral heterogeneity raises concern that multiple biopsies may be necessary to assess global hypoxia status. The objective of this study was to compare the impact of heterogeneity on the discriminative capacity of several previously described hypoxia gene signatures and determine if a single biopsy is sufficient to obtain a reliable estimate of hypoxia in cervical cancer.

Materials and Methods

Multiple biopsies (33) were obtained from 11 locally advanced (FIGO IB to IVB) cervical cancers prior to treatment. Ten hypoxia gene signatures were analyzed. Variance component analysis was used to determine the ratio of within-tumor variability to total-tumor variability when one to five biopsies are available for analysis (W/T_1–5). The mean standardized error in the signature scores was estimated by comparing the score using one biopsy randomly selected from each tumor to the ‘global’ score using all available biopsies.

Results

The ten hypoxia signatures were comprised of 6–99 genes each. The W/T₁ ratios for individual genes commonly found in the signatures ranged from 0.17 to 0.73. W/T₁ ratios for the signatures were generally lower (0.21–0.45), implying greater capacity to discriminate among tumors. With additional biopsies, the signature W/T ratios (ie W/T_2-5) decreased further. The mean error in the signature scores varied from 0.27 to 0.40 of one standard deviation, suggesting high capacity to discriminate among tumors with different global hypoxia scores.

Conclusions

Compared with individual probes, hypoxia gene expression signatures are generally more consistent across multiple biopsies from different regions of a tumor and more tolerant of intratumoral heterogeneity.

Generation of multiparametric MRI maps by using Gd-labelled- RBCs reveals phenotypes and stages of murine prostate cancer

Prostate Cancer (PCa) is the second most common and fifth cause of cancer-related mortality in males in Western Countries. The development of innovative tools for an early, more precise and noninvasive diagnosis is a medical need. Vascular volume (Vv) and hypoxia are two of the most important tumor hallmarks. Herein, they have been assessed in TRAMP mice by using MRI. Their quantification has been carried out by injecting autologous Red Blood Cells (RBCs), ex vivo labelled with Gd-HPDO3A or Gd-DOTP complexes, respectively. Gd-labelled-RBCs are stably confined in the intravascular space, also in presence of a very leaky tumor endothelium, thus representing efficient probes for vascular space analysis. Vv enhancement and hypoxia onset have been demonstrated to be present at early stages of PCa and their expression largely increases with tumor development. Moreover, also Diffusion weighted MRI and Amide Proton Transfer MRI have been herein applied to characterize PCa. The herein applied multiparametric MRI (mpMRI) analysis allows a detailed in vivo characterization of PCa, in which each histotype and cancer stage displays a specific MRI pattern. This provides an unprecedented opportunity to feature prostate tumor, making possible a non-invasive, precise and early diagnosis, which could direct treatments towards a more personalized medicine.

The clinical significance of hypoxia in human cancers

Hypoxia is present to some extent in most solid malignant human cancers because of an imbalance between the limited oxygen delivery capacity of the abnormal vasculature and the high oxygen consumption of tumor cells. This drives a complex and dynamic compensatory response to enable continued cell survival, including genomic changes leading to selection of hypoxia-adapted cells with a propensity to invade locally, metastasize, and recur following surgery or radiotherapy. There is indisputable clinical evidence from numerous observational and therapeutic studies across a range of tumor types to implicate hypoxia as a key determinant of cancer behavior and treatment outcome. Despite this, hypoxia-targeted treatment has failed to influence clinical practice. This is explained, in part, by emerging findings to indicate that hypoxia is not equally important in all patients even when present to the same extent. The impact of hypoxia on patient outcome and the benefit of hypoxia-targeted treatments are greatest in situations where hypoxia is a primary biological driver of disease behavior-patients with tumors having a "hypoxic driver" phenotype. The challenge for the clinical and scientific communities moving forward is to develop robust precision cancer medicine strategies for identifying these patients in the setting of other etiologic, genomic, and host-tumor factors, considering not only the state of the tumor at diagnosis but also changing patient and tumor characteristics over time.