The success rate in establishing primary cervical xenograft models in the orthotopic site from patient cervix biopsy tissue was 48%, with 16 of 33 implanted tumors growing in the animals and maintained for up to 5 generations. Failure of engraftment was defined at 12 months post implantation. Details of the tumors giving rise to xenografts are outlined in Supplementary Table 1 showing the number of tumor in each passage. On average it took 3–4 months for the first palpable xenograft to arise following orthotopic transplant. The majority of the patients were FIGO stage II–IIIA/B with squamous cell histology. Analysis of association with outcome was non-informative due to both small patient numbers and lack of sufficient follow-up for some patients to assess clinical outcomes.

No associations were found between the xenograft take rate and the clinical characteristics of the patients, specifically histology, nodal status and tumor size, although the number of patients was small (n = 34) (Table 1). Similarly, there was no apparent association between IFP, level of hypoxia (HP5) or HPV status of the primary tumor and xenografting success rate. Associations with clinical outcome were not assessed because of the small number of patients and the limited time of follow-up since completing treatment.

Supplementary Table 1 illustrates our strategy for analysis of the various microenvironmental parameters of the xenografts. We opted to analyze four of the xenografts (OCICX 1, 3, 8, 16) at each of the first five passages and all of the xenografts at passage three for comparison with the initial biopsies from which the xenografts were established. The numbers in the highlighted regions of the body of the table represent the numbers of tumors that contributed to this analysis. Most of the patients had measurements of both IFP and hypoxia in their tumors hence initially we examined these parameters in the xenograft models. The analysis indicated similar but higher IFP values in most of the original patient tumors than in the passage three xenografts (Spearman correlation coefficient = 0.17) (Figure 1A). IFP increased slightly with the number of passages in the four xenograft models examined across five passages (p value for linear trend 0.0037). Unfortunately the value for one of the primary tumors was not available but it may be noted that for the other three values in the xenografts were generally lower than measured in the primary tumor (Figure 1B).

Measurements of hypoxia in the patients were made using an Eppendorf polarographic oxygen electrode (to determine the percent of pO₂ values <5 mmHg = HP5) but this probe was not available for measurements in the xenografts. Consequently we used EF5 uptake in the xenografts and CA-9 staining in both the patient biopsies and the xenografts as surrogate parameters for tissue hypoxia (Figure 2). Both, EF5 and CA-9, were assessed separately in the stromal and tumor components of the tumor. EF5 had a moderate correlation with CA-9 expression in the xenografts (r = 0.51 in tumor and r = 0.52 in stroma), but the correlation between CA-9 and HP5 in the patients was poor. This poor correlation likely relates to the inherent heterogeneity of these different techniques in the assessment of tumoral hypoxia. We have reported previously that HP5 values made directly in the patient tumor do not correlate well with CA-9 measurements made in individual biopsies from the patient’s tumors [48]. (Figure 2).

The epithelial and stromal components of the original biopsies and xenograft models were scored and assessed using two independent methods—qualitatively by two pathologists (BC and JS) on high power fields and quantitatively using a semi-automated pattern recognition software program (Aperio’s Genie) on whole tissue sections. Scoring was done on the H&E slides on both the patient biopsy and xenograft sections for each OCICx model. Figure 3 shows a good accuracy of epithelial-stromal discrimination between these two approaches with a linear correlation for passage 3 xenografts and patient biopsies. The Genie Spectrum IHC analysis for the patient biopsy and matching (passage 3) xenograft is illustrated in Figure 4 for the tumor and stromal components of two of the models (OCICx 23 and 3). The panels illustrate the masks of tumor and stroma in the tumor sections with the corresponding H&E staining for comparison. The percent tumor at passage 3 for all the OCICx models and for the patient biopsy are shown in Figure 5. There is heterogeneity of tumor proportion between the two that probably reflects the fact that only a single (small) biopsy specimen was available, whereas values for the xenografts are averaged over a number of tumors (as indicated in Supplementary Table 1).

Using Genie analysis we quantified the stromal content of four xenografts models (OCICx 1,3,8, 16) throughout the five passages for comparison to the original biopsy (Figure 6A). The stromal components of the various passages relative to the biopsy from which they were derived shows heterogeneity (as seen in Figure 5). Interestingly, in all four models the level of stroma tended to increase at early passages and then decreased at later passages with a low value after five passages for all models (<10%). The decrease in stromal content in the later passages paralleled an increase in the growth rate of the tumors, as assessed by the mean time between passages (Figure 6B). This increase in growth rate was also seen in the remaining models (Supplementary Figure 1). Analysis of the para-aortic lymphnodes indicated that the metastatic potential of the xenografts also increased significantly (p < 0.01) with passage number (Figure 6C).

To gain better insight into the stromal and tumor epithelial components of the cervix xenografts and the associated cervix biopsy, SMA, collagen IV and cytokeratin staining were examined (Supplementary Figure 2). The distinct staining of SMA in the stromal components showed well-differentiated fibroblasts/myofibroblasts. Collagen IV staining was also very specific for the stroma. The cytokeratin IHC stain in both the biopsy and xenograft differentiates (positive) epithelial components from (negative) stroma. Proliferation (Ki-67 staining), hypoxia (EF5 and CA-9 staining), and blood vessels (CD31 staining) and lymph vessels (LYVE1 staining) were also assessed in these biopsies and xenografts as shown in Figure 2.

To alleviate issues associated with heterogeneity in the tumor to stromal content of the biopsies and xenografts, quantitation of the staining for the various markers was assessed separately in the tumor and stromal components as shown in Figure 7A,B. For CA-9 and EF5 (hypoxia) in the epithelial components of the tumor there was a significant (p < 0.001) increase with passage number. In parallel there was a significant increase in vascular staining (CD31) (p < 0.001) in the stromal component. On average there was also a significant increase in Ki67 staining in the epithelial component of the tumor and LYVE1 in both components, however this is variable from one model to another. CD31 and LYVE1 levels were much lower in the epithelial than in the stromal component consistent with the finding that CA-9 and EF5 change to a larger extent in the epithelial than the stromal component. Ki-67 levels are much lower in the stromal than epithelial component. Correlations between these markers were in general weak (r < 0.6).

To make an overall comparison of the concordance of the measurements in the biopsies and xenografts, we plotted all the data measured in the xenografts against that measured in the original biopsy for each of the 11 xenograft models (up to OCICx23), as shown in Figure 8A. The actual values are presented in Supplementary Table 3. To assess the reproducibility of the patient measurements in the relevant xenografts the Intraclass Correlation Coefficient (ICC) was calculated and the data are plotted in the order of the ICC. Notably in the Figure 8A the collagen IV staining levels (in stroma) generally show a poor correlation, consequently we also plotted the data excluding the collagen IV data (Figure 8B), again ordered according to the ICC values. The majority of models (10 of 11) show good concordance (ICC ≥ 0.83) with OCICx 11, 16, 22 and 1 as the first 4 models with strong positive correlations for all markers. One of the xenograft model (OCICx 8) associated poorly, regardless of whether the collagen IV measurements are included or not (ICC = 0.62 excluding Collagen IV and ICC = 0.6 for the entire data set, respectively).

The aim of this present study was to characterize the tumor microenvironment of primary cervix xenografts, established and propagated directly from patient tumors. Our goal was to develop well-characterized and representative models of human tumors that recapitulate the microenvironmental complexity of clinical cervical cancer. To our knowledge there have been no other studies of this nature demonstrating the differences in the tumor microenvironment between early xenograft passages. We report the establishment of a unique set of serially transplantable, orthotopic, patient-derived cervical cancer xenograft models that, at least within the range of passage numbers examined, show a relatively stable retention of the original tumor characteristics, but demonstrate a range of features faithfully reflecting the tumor heterogeneity encountered in patients. This is essential for the validity of the xenograft model and the results which will be obtained from them using novel therapeutics [49]. Direct orthotopic implantation of the tumors may preserve the ability of cells to interact with supporting cells such as the stroma within the microenvironment; features that are lost in the in vitro setting. However, one drawback of any tumor grafting model based on core biopsies is that small acquired samples may not always be representative of an entire patient tumor [50].

There are a limited number of studies reporting on the development of patient-derived xenograft models through serial orthotopic implantation. The latency for tumor “take” is variable among tumour histology, location of implantation, and recipient strain [51]. Studies in patient-derived xenografts of pancreatic, lung, ovarian and prostate carcinomas demonstrate engraftment rates ranging between 40–95% with serial passages resembling the original biopsy histologically [52,53]. See Supplementary Table 2 for summary. Recently DeRose et al. [54] reported on the establishment of serially transplantable, orthotopic, breast tumor grafts that retain the characteristics of the original tumor (based on histology and genetic profiling). The tumor architecture was maintained through several passages in mice including its supportive stroma. Furthermore, Jin et al. [55] showed that early passage of the patient-derived tumor tissue of primary colon carcinoma, lymphatic and hepatic metastases revealed a high level of similarity with the original clinical samples with respect to histology, immunohistochemistry and gene expression. Thus it is clear that patient derived xenograft models histopathological features and molecular signatures that are similar to the original tumors in various contexts. There are limited studies investigating orthotopic vs. subcutaneous xenografts comparisons originating from patient tissue samples. However Pocard et al. [56] does in fact show, in colorectal carcinomas, that orthotopic xenografts resemble the original tissue sample better then subcutaneous tumors.

However, there has been limited detailed analyses about the stromal and microenvironmental components of these primary xenograft models particularly in regards to changes during passaging. In our primary cervix xenograft model an engraftment rate of approximately 48% was found. This rate was not correlated to HPV status or patient clinico-pathological features nor to the measurements of hypoxia (HP5) or IFP in the primary (patient) tumor, although it should be recognized that this may reflect the small sample size of the biopsy population. Despite the lack of correlation with clinic-pathologic features we did observe the development of lymphatic metastases in many of the models and observed that the number of metastases increased with passage number in the four models analysed for passage number changes. Consistent with other studies, as noted above, we observed that the OCICx xenografts generally track with the patient biopsy in terms of tumor morphology and stromal elements. The strong positive correlation between the pathologist scoring of the tumor sections for epithelial and stromal components and the automated Genie system (Figure 3) confirms the value of the automated approach to allow quantitative analysis of specific markers across whole tumor sections.

The analysis of differences in the various measurements and markers during the passaging of the xenografts suggests that hypoxia levels increase with passage number (generation) in the tumors. In parallel with the increase in EF5 and CA-9, particularly in the epithelial component, there is an increase in the proliferation marker, Ki-67, in the (oxic) epithelial component, which may increase oxygen demand. The increased levels of CD-31 staining (endothelial cells) in the epithelial and stromal components are consistent with such an increased demand but the increased level of hypoxia suggests that this does not result in a sufficient increase in supply of oxygen. Presumably the levels of hypoxia in the xenografts must plateau and stabilize at later passages. A recent study assessing levels of hypoxia in pancreatic cancer xenografts (at later passages than used here) using EF5 staining and analysis of the whole tumor with flow cytometry, reported that, for xenografts from different primaries, there were consistently lower or higher values of hypoxia [57]. This study also observed higher Ki-67 levels in tumors with greater levels of hypoxia.

It can be noted that the EF-5 staining levels in both the epithelial and stromal compartments tend to be lower than those for CA-9. Although this may reflect factors other than hypoxia than can modulate CA-9 expression it is also consistent with findings that lower levels of oxygen are required to activate EF-5 binding than are required to stabilize HIF-1 and stimulate CA-9 production [58]. This highlights an often unappreciated difference between these hypoxia markers. Also the levels of hypoxia and Ki-67 staining are higher and increase faster in the epithelial component than the stromal component, whilst the opposite is true for the CD-31 expression, consistent with most of the vasculature remaining within the stromal compartment and limited invasion of vessels into the tumor component. LYVE-1 staining (primarily reflecting lymphatics) shows a similar pattern to the CD-31 staining. It is particularly low in the epithelial component consistent with low levels of lymphatics in tumors. Similarly, Ki-67 levels are much lower in the stromal than the epithelial components. However, measurements within a specific tumor are subject to heterogeneity inherent within that model (i.e., in tumors from different animals but from the same model) (Figure 7). Mean values from sections derived from multiple individual tumors were felt to provide a better global perspective of a particular xenograft model (derived from a specific patient). Unfortunately this does not translate to the comparison with the primary patient biopsy, which being a core biopsy only represents one region of the primary tumor and cannot encompass the heterogeneity inherent in that patient’s cancer.

The small amount of tissue available for analysis of the biopsies likely explains why the individual markers showed limited correlation between the biopsy and their respective xenografts. Nevertheless when all of the markers were combined the intraclass correlation coefficient analysis (Figure 8) showed that overall there was good correlation between the patient biopsy and the measurements of the markers in all the xenografts at passage three with the exception of collagen IV. Reasons why collagen IV is an outlier in most of the OCICx models are unclear but we note that different antibodies were used for the xenografts and the biopsies, so in the case of the xenografts any residual human stromal collagen IV would not have been detected. For all the other IHC markers the other antibodies recognised both the human and murine markers. Excluding collagen IV from the ICC analysis showed a good correlation for other markers for all but one of the eleven xenograft models analysed. While it is possible that heterogeneity explains the failure of this model to show a good correlation the data raises a caution that not all xenografts may necessarily be good models of the tumour from which they are derived, even at very early passage. Genetic analysis of the xenograft models is currently planned and it will be of interest to determine if the degree of correlation between the biopsy and xenograft models parallels that observed with the current markers. Based on the available data in the literature [51] for such comparisons we anticipate that all the models will show a high correlation.

Currently we are further exploring the tumor microenvironment factors such as stromal components and hypoxia in these xenografts through a multimodality imaging study (manuscript in preparation). These imaging studies will help to address some of the issues associated with heterogeneity both within the xenografts and between xenograft and primary, which, as noted above, is a concern because the primary tumor is represented in the current study by a single biopsy. Inevitably imaging measurements are at a much lower resolution than is possible with tissue sections.

Overall our results demonstrate that early passage xenografts established from clinical cervix cancer biopsies, capture and reflect the general histopathological features of the primary tumor not only in terms of epithelial vs. stromal elements but other tumor microenvironmental elements (hypoxia, IFP, vasculature). However, detailed IHC analyses suggest significant increases in hypoxia and proliferation in the epithelial component during serial passaging. This was associated with an increase in the number of lymphatic metastases with passage number suggesting a possible increase in malignancy. An important caveat is that the interpretation of our studies must be cautious because of the known issues of heterogeneity within the tumor but the data has significant implications for the choice of suitable xenograft models for therapeutic testing of drugs. Understanding the importance of the stroma with the tumor microenvironment in our model of the primary cervix xenografts remains a work-in-progress and further analysis is warranted.