To improve treatment outcomes in non–small cell lung cancer (NSCLC), preclinical models that can better predict individual patient response to novel therapies are urgently needed. Using freshly resected tumor tissue, we describe an optimized ex vivo explant culture model that enables concurrent evaluation of NSCLC response to therapy while maintaining the tumor microenvironment. We found that approximately 70% of primary NSCLC specimens were amenable to explant culture with tissue integrity intact for up to 72 hours. Variations in cisplatin sensitivity were noted with approximately 50% of cases responding ex vivo. Notably, explant responses to cisplatin correlated significantly with patient survival (P = 0.006) irrespective of tumor stage. In explant tissue, cisplatin-resistant tumors excluded platinum ions from tumor areas in contrast to cisplatin-sensitive tumors. Intact TP53 did not predict cisplatin sensitivity, but a positive correlation was observed between cisplatin sensitivity and TP53 mutation status (P = 0.003). Treatment of NSCLC explants with the targeted agent TRAIL revealed differential sensitivity with the majority of tumors resistant to single-agent or cisplatin combination therapy. Overall, our results validated a rapid, reproducible, and low-cost platform for assessing drug responses in patient tumors ex vivo, thereby enabling preclinical testing of novel drugs and helping stratify patients using biomarker evaluation. Cancer Res; 77(8); 2029–39. ©2017 AACR.

Non–small cell lung cancer (NSCLC) is a leading cause of cancer death worldwide. Patients with stage I–III tumors are surgically resected and given adjuvant chemotherapy or radiotherapy. Patients with stage IV disease receive palliative chemotherapy only unless they can be stratified for targeted therapy. Most patients receive combination chemotherapy based on clinical parameters of cisplatin or carboplatin with at least one other drug such as vinorelbine, gemcitabine, or paclitaxel. Unfortunately, only approximately 5% of patients receiving adjuvant therapy show 5-year average survival benefit (1, 2). Therefore, more accurate methods for predicting chemotherapeutic benefit are urgently required to improve clinical outcomes.

The era of personalized medicine has heralded the development of targeted therapies for NSCLC, some of which rely on preselection of cancers according to genetic mutation. For example, selective EGFR inhibitors gefitinib and erlotinib provide clinical benefit over standard chemotherapy for NSCLC tumors bearing EGFR mutations (3, 4), whereas the ALK inhibitor crizotinib benefits ALK-mutated cases (5). A global industry is centered on assessing additional mono- or combinatorial treatments in NSCLC clinical trials. Despite this momentum, late-stage failures are a reality and there is less than 11% success in bringing a drug to market (6), attributable in part to nonpredictive preclinical drug platforms (7, 8). The incorporation of patient-derived xenograft (PDX) mouse models (9, 10) into preclinical studies has improved predictive accuracy somewhat (11, 12). However, PDX efficacy studies are expensive, requiring large numbers of mice. Furthermore, not all primary human tumors generate PDXs and, of those that do, serial propagation can select tumors that adapt to grow in an immunocompromised environment.

An alternative approach is to use 3-dimensional ex vivo culture of fresh human tumors. Methods for ex vivo culture of human tumors have been available for many years, and evidence shows that they can reliably reflect tumor growth in vivo (13–19). Here, we have developed and perfected an ex vivo culture method for NSCLC tumor samples that is both simple and reproducible. We have optimized culture conditions and show that tumor and stroma are retained intact and are viable. As proof-of-concept, NSCLC explant response to the standard-of-care chemotherapy drug cisplatin was examined, as well as response to the targeted agent TRAIL. We also illustrate how explants can be used to inform mechanisms of drug action by evaluating biomarkers of drug response. Together, our data show that the explant platform can effectively predict patient response to therapy and can be used for monitoring clinically relevant biomarkers.

Ex vivo explant culture

Fresh NSCLC tumors were collected from consented patients undergoing lung surgery (Ethical approval: LREC: 07/MRE08/07). Patients had no prior exposure to chemotherapy. Viable tumor areas were identified by frozen tissue sectioning and hematoxylin and eosin (H&E) staining. Tissue was placed in Hank balanced salt solution and cut into fragments of 2 to 3 mm3 using 2 skin graft blades on a dental wax surface. These were placed in fresh culture media (DMEM with 4.5 g/L glucose + 0%–5% FCS and 1% pen/strep); 9 fragments were randomly selected and placed on a 0.4-μm culture insert disc (Millipore) floated on 1.5 mL of media in a 6-well dish. Explants were incubated at 37°C and 5% CO2 for 16 to 20 hours. Discs were then transferred to new wells containing 1.5-mL fresh media, and drugs or carrier control were added to each well in a volume of 1.5 μL for 24 hours. Cisplatin (Sigma) was utilized over a dose range of 0 to 50 μmol/L (dissolved in dimethylformamide). TRAIL (20, 21) was utilized at 1 μg/mL, diluted in DMEM media from a stock of 1 mg/mL. After treatment, explants were washed with PBS and transferred to new wells containing 1 mL of 4% (w/v) paraformaldehyde for 20 hours. Explants were transferred onto sponges, pre-soaked in 70% (v/v) ethanol, and placed in histology cassettes. They were embedded into paraffin blocks from which 4-μm sections were generated.

Histologic analysis

H&E staining of formalin-fixed, paraffin-embedded (FFPE) material sections was generated by standard approaches and, for immunohistochemistry (IHC), sections were processed as described (22). The Novolink Polymer Detection System Kit (Leica Microsystems) was used according to the manufacturer's instructions. Primary antibodies were: cleaved PARP [E51]: Abcam 1:6,000, Ki67 Clone MIB-1: DAKO 1:2,000, p53 DO1: gift from David Lane 1:1,000, cytokeratin clone MNF116: DAKO 1:5,000. Antibodies were diluted in blocking solution made with 3% (w/v) BSA, 0.1% (v/v) Triton X-100 (Fisons) in TBS. Staining was visualized under a LEICA DM 2500 microscope and photographed with a LEICA DFC 420 camera.

Quantitation of IHC staining

Images of the tumor explants were taken at 10× magnification and merged using Adobe Photoshop CS5.1, generating a single image of one explant. Tumor area was determined using ImageJ analysis (23), excluding areas of necrosis and stroma. The labeling index was determined using ImmunoRatio (24), and a single value was obtained for all 9 explants derived from one treatment that was expressed as a percentage of the total tumor area.

Laser ablation inductively coupled plasma mass spectrometry

Sections of explants treated with cisplatin were subjected to Laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) to produce elemental maps showing the spatial distribution of platinum in tissue sections (25). The method is described in Supplementary Fig. S1.

Statistical analysis

Significance of proliferation/death indices was determined by Wilcoxon matched pairs test and Jonckheere–Terpstra trend test, respectively. Unpaired data were compared by the Mann–Whitney U test or Kruskal–Wallis one-way ANOVA. Paired data were analyzed by the Page L test (Unistat Statistical Package, version 5.0, Unistat), and interrelationships were investigated by Spearman rank correlation (SPSS, version 22, IBM). The optimal cutoff point to determine the relationship between explant response and patient survival was examined using a plot of sensitivity against 1 − specificity as a receiver operator characteristic (ROC) curve (SPSS). Survival was investigated by Kaplan–Meier analysis (SPSS) of cell indices, which were compared by the log-rank Mantel–Haenszel (Peto) test, and by univariate and multivariate Cox regression (SPSS). P < 0.05 was considered statistically significant.

Histopathology of NSCLC tumors used for explants

Table 1 provides a summary of patient demographics, tumor type, and stage for all 45 samples utilized for this study. The histologic types and stages were broadly consistent with the known distribution of NSCLC cases in the United Kingdom (26). A proportion of NSCLC tumors is known to be necrotic (27), and an important first step was to exclude such tumors from analysis using H&E assessment. This led to the identification of 13 tumors (∼29%) that were excluded from explant generation. Supplementary Fig. S2 indicates the histologic type (Supplementary Fig. S2A) and stage (Supplementary Fig. S2B) of viable and nonviable tumors. The highest proportion of nonviable tumors was within the adenocarcinoma subtype [∼36% compared with ∼25% of squamous cell carcinoma (SCC) cases]. However, there was no correlation between tumor stage and viability.

Table 1.

Summary of patients’ characteristics and tumors used for this study

CharacteristicNumber (%) of patients/tumors
Sex 
 Male 25 (55.6) 
 Female 20 (44.4) 
Age 
 Median 70 
 Range 54–85 
Histology 
 Adenocarcinoma 22 (48.9) 
 SCC 20 (44.4) 
 Large cell carcinoma 0 (0) 
 Atypical carcinoid 3 (6.7) 
Stage 
 IA 7 (15.6) 
 IB 8 (17.8) 
 IIA 8 (17.8) 
 IIB 9 (20) 
 IIIA 11 (24.4) 
 IIIB 1 (2.2) 
 IV 1 (2.2) 
CharacteristicNumber (%) of patients/tumors
Sex 
 Male 25 (55.6) 
 Female 20 (44.4) 
Age 
 Median 70 
 Range 54–85 
Histology 
 Adenocarcinoma 22 (48.9) 
 SCC 20 (44.4) 
 Large cell carcinoma 0 (0) 
 Atypical carcinoid 3 (6.7) 
Stage 
 IA 7 (15.6) 
 IB 8 (17.8) 
 IIA 8 (17.8) 
 IIB 9 (20) 
 IIIA 11 (24.4) 
 IIIB 1 (2.2) 
 IV 1 (2.2) 

NOTE: Tumor samples were collected from consented patients undergoing lung surgery at Glenfield Hospital, Leicester. Clinical data, histology, and stage were provided by official histopathologic reports submitted by consultant pathologists at University Hospitals of Leicester, Leicester, UK.

Thirty-two viable tumors were processed for explant culture. Intrinsic levels of cell proliferation and cell death were first assessed in uncultured samples by Ki67 or cleaved PARP (cPARP) immunostaining (Fig. 1A and B). SCC tumors displayed significantly higher levels of proliferation than adenocarcinoma, whereas atypical carcinoid tumors were essentially indolent (Fig. 1A). These observations are consistent with several previous reports (28–30). With regard to cPARP staining, the majority of samples showed less than 20% of staining, indicating low levels of intrinsic cell death (Fig. 1A and B).

Figure 1.

Intrinsic levels of proliferation and apoptosis in the tumors used for explants. A, Proliferation was assessed by quantitating Ki67 IHC staining and cell death by quantitating cPARP staining. Left, percentage of intrinsic proliferation and cell death in tumors. A single dot represents a single tumor sample. For the Ki67 staining, the samples were grouped into 1 of 3 groups: H, high (>40%); M, medium (20%–40%); L, low (0%–20%). The samples all had low intrinsic levels of cPARP staining. Middle and right, percentage of Ki67 and percentage of cPARP staining for tumors with adenocarcinoma (ADC), SCC, and atypical carcinoid (AC) histologies. The SCC samples had significantly higher levels of intrinsic proliferation compared with the adenocarcinoma samples whereas, the atypical carcinoid samples were indolent. Cell death levels were consistent across the histologies. B, Representative images of Ki67 (left) and cPARP (right) IHC staining of high (LT103; top), medium (LT98; middle), and low (LT104; bottom) proliferative tumors. IHC stains were counterstained with hematoxylin. LT103 (high proliferative tumor) and LT98 (medium proliferative tumor) represent SCC samples, whereas LT104 (low proliferative tumor) is an adenocarcinoma. Scale bars, 100 μm.

Figure 1.

Intrinsic levels of proliferation and apoptosis in the tumors used for explants. A, Proliferation was assessed by quantitating Ki67 IHC staining and cell death by quantitating cPARP staining. Left, percentage of intrinsic proliferation and cell death in tumors. A single dot represents a single tumor sample. For the Ki67 staining, the samples were grouped into 1 of 3 groups: H, high (>40%); M, medium (20%–40%); L, low (0%–20%). The samples all had low intrinsic levels of cPARP staining. Middle and right, percentage of Ki67 and percentage of cPARP staining for tumors with adenocarcinoma (ADC), SCC, and atypical carcinoid (AC) histologies. The SCC samples had significantly higher levels of intrinsic proliferation compared with the adenocarcinoma samples whereas, the atypical carcinoid samples were indolent. Cell death levels were consistent across the histologies. B, Representative images of Ki67 (left) and cPARP (right) IHC staining of high (LT103; top), medium (LT98; middle), and low (LT104; bottom) proliferative tumors. IHC stains were counterstained with hematoxylin. LT103 (high proliferative tumor) and LT98 (medium proliferative tumor) represent SCC samples, whereas LT104 (low proliferative tumor) is an adenocarcinoma. Scale bars, 100 μm.

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Optimization of explant culture

Our approach for the NSCLC explant culture system was based on previous experience with breast cancer samples (MacFarlane, unpublished observations; ref. 31;). As a first step in implementing protocols for NSCLC, we first investigated the effects of culture time and FCS concentration.

Explants were routinely allowed to recover for a period of 16 to 20 hours after their initial generation; viability was assessed over a time range of 24 to 72 hours after recovery for 5 tumors. As shown in Fig. 2A, a trend of decreasing cell proliferation and increasing cell death with increasing time of culture was observed, suggesting ex vivo explant cultures are more viable in short-term culture. Varying FCS concentration, from 0% to 5%, at 24 hours of culture after the initial 16 to 20 hours of culture recovery showed no statistically significant difference in levels of proliferation or cell death (Fig. 2B).

Figure 2.

Establishment of optimal explant culture conditions. A, Evaluation of proliferation and cell death levels with increasing time of explant culture. The percentage of Ki67 (left graphs) and the percentage cPARP (right graphs) IHC staining of 5 NSCLC ex vivo explants over time are shown. The staining values were generated from the uncultured tumor in its native state and from explants from the same tumor at 24, 48, and 72 hours of culture after an initial recovery of 16 to 20 hours. The graphs at the top show individual values for each of the 5 tumors and the graphs on the bottom indicate pooled mean values for the 5 samples ±95% confidence interval (CI). Page L nonparametric trend test showed a negative trend for Ki67 staining with increasing culture time (P = 0.01; L statistic = 143) and a positive trend for cPARP staining with increasing culture time (P = 0.05; L statistic = 140). B, Evaluation of percentages of Ki67 and cPARP staining with varying FCS concentration. The percentage of Ki67 (left graphs) and percentage of cPARP (right graphs) IHC staining of 5 NSCLC ex vivo explants over time are shown. The staining values were generated from the uncultured tumor in its native state and from explants from the same tumor cultured in varying FCS concentrations for 24 hours after an initial recovery of 16 to 20 hours. The graphs at the top show individual values for each of the 5 tumors, and the graphs on the bottom indicate pooled mean values for the 5 samples ±95% CI. Page L nonparametric trend test showed no significant difference for Ki67 or cPARP staining with varying FCS concentration. C, Summary of the effect of cultivation. The percentage of Ki67 (left graph) and percentage of cPARP (right graph) staining were determined for 21 explant cultures. The box and whiskers plots show the data for uncultured tumors compared with tumors cultured for 24 hours + 16 to 20 hours of recovery in 1% FCS. The boxes extend from the 25th to 75th percentiles, and the lines in the middle of the boxes represent the median. The whiskers extend from the smallest to the largest values.

Figure 2.

Establishment of optimal explant culture conditions. A, Evaluation of proliferation and cell death levels with increasing time of explant culture. The percentage of Ki67 (left graphs) and the percentage cPARP (right graphs) IHC staining of 5 NSCLC ex vivo explants over time are shown. The staining values were generated from the uncultured tumor in its native state and from explants from the same tumor at 24, 48, and 72 hours of culture after an initial recovery of 16 to 20 hours. The graphs at the top show individual values for each of the 5 tumors and the graphs on the bottom indicate pooled mean values for the 5 samples ±95% confidence interval (CI). Page L nonparametric trend test showed a negative trend for Ki67 staining with increasing culture time (P = 0.01; L statistic = 143) and a positive trend for cPARP staining with increasing culture time (P = 0.05; L statistic = 140). B, Evaluation of percentages of Ki67 and cPARP staining with varying FCS concentration. The percentage of Ki67 (left graphs) and percentage of cPARP (right graphs) IHC staining of 5 NSCLC ex vivo explants over time are shown. The staining values were generated from the uncultured tumor in its native state and from explants from the same tumor cultured in varying FCS concentrations for 24 hours after an initial recovery of 16 to 20 hours. The graphs at the top show individual values for each of the 5 tumors, and the graphs on the bottom indicate pooled mean values for the 5 samples ±95% CI. Page L nonparametric trend test showed no significant difference for Ki67 or cPARP staining with varying FCS concentration. C, Summary of the effect of cultivation. The percentage of Ki67 (left graph) and percentage of cPARP (right graph) staining were determined for 21 explant cultures. The box and whiskers plots show the data for uncultured tumors compared with tumors cultured for 24 hours + 16 to 20 hours of recovery in 1% FCS. The boxes extend from the 25th to 75th percentiles, and the lines in the middle of the boxes represent the median. The whiskers extend from the smallest to the largest values.

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The data from above suggest that the 24-hour time point gives the greatest viability but that FCS concentration is not a significant factor. Subsequent analyses of drug responses were therefore performed for 24 hours, using 1% as the standard FCS concentration. Pooled data for 21 explants under these conditions are shown in Fig. 2C. Overall, there is a small but significant effect of cultivation on explant viability, with there being approximately 10% decrease in proliferation and almost 10% increase in cell death compared with the uncultured but freshly fixed native tumor.

Explant responses to cisplatin

Adjuvant chemotherapy for NSCLC usually consists of cisplatin often in combination with another chemotherapy drug. Clinical trial data have shown that cisplatin is the dominant drug, with the drug given in combination with cisplatin not modifying the effect of chemotherapy on overall survival (1, 32). Given this evidence, we focused on examining explant responses to cisplatin alone.

Twenty-one explants were treated with a dose range of cisplatin (0–50 μmol/L) for 24 hours following the initial recovery of 16 to 20 hours. Data for individual cases are shown in Supplementary Fig. S3. Levels of cell proliferation were only marginally affected by the drug (Supplementary Fig. S3B), and therefore the emphasis was placed on assessing cell death responses (Supplementary Fig. S3A). Cell death response for each tumor was calculated as fold induction relative to the control over the dose range (Fig. 3A). Of 21 tumors, 9 (43%) showed less than 2-fold induction in cell death in response to the drug, whereas the remaining 12 of 21 (57%) showed cell death induction ranging from 2- to 25-fold. The majority of these tumors only showed a response at high levels of cisplatin (50 μmol/L), with only 2 tumors responding at the lower dose of 10 μmol/L.

Figure 3.

NSCLC explant response to cisplatin. A, Fold cell death relative to control of 21 NSCLC explant cultures treated with a dose range (0–50 μmol/L) of cisplatin. The percentage of cPARP staining of each sample was quantitated within explants from the same tumor cultured in carrier control (DMF) or increasing cisplatin concentrations (1, 10, and 50 μmol/L) for 24 hours after an initial recovery of 16 to 20 hours. The value for each treatment was divided by the carrier control to obtain a fold change. B, Kaplan–Meier patient survival for all cases correlated with sensitivity of explants to cisplatin at 50 μmol/L. Data were evaluated for 26 patients/explants (Supplementary Table S1). The threshold of sensitivity/resistance to the drug was determined using an ROC curve (Supplementary Fig. S4A). The Mantel–Cox log-rank test identified a statistically significant relationship (P = 0.006) between patient survival and cisplatin sensitivity. C, Kaplan–Meier patient survival according to stage correlated with sensitivity of explants to cisplatin at 50 μmol/L. Left graph, stage I/IIA samples (n = 14, P = 0.02). Right graph, stage IIB/III samples (n = 12, P = 0.05). D, Kaplan–Meier patient survival according to adjuvant chemotherapy or lymph node involvement correlated with sensitivity of explants to cisplatin at 50 μmol/L. Left graph, subgroup of patients receiving adjuvant therapy (n = 12), including platinum-based chemotherapy (n = 8), radiotherapy (n = 3), and taxane-based chemotherapy (n = 1). The Mantel–Cox log-rank test identified a statistically significant relationship between survival of patients and response to cisplatin in explants (P = 0.01) Right graph, subgroup of patients with lymph node involvement (n = 10) for which the Mantel–Cox log-rank test did not identify a statistically significant relationship (P = 0.13) between patient survival and cisplatin sensitivity. E, Correlation of response to cisplatin in explant culture with tumor stage (left) and histology (right). The box and whiskers plots show data for difference in percentage of cPARP staining in response to 50 μmol/L cisplatin compared with control treatment for each explant relative to tumor stage/histology. The box extends from the 25th to 75th percentiles, and the lines in the middle of the boxes represent the median. The whiskers extend from the smallest to the largest values. The Jonckheere–Terpstra test for ordered alternatives showed a significant negative trend (P = 0.007) between increasing stage and cisplatin response. Correlation of tumor histology with cisplatin response demonstrated statistically significant differences between SCC samples and adenocarcinoma (ADC) types with a Mann–Whitney test of P = 0.0004.

Figure 3.

NSCLC explant response to cisplatin. A, Fold cell death relative to control of 21 NSCLC explant cultures treated with a dose range (0–50 μmol/L) of cisplatin. The percentage of cPARP staining of each sample was quantitated within explants from the same tumor cultured in carrier control (DMF) or increasing cisplatin concentrations (1, 10, and 50 μmol/L) for 24 hours after an initial recovery of 16 to 20 hours. The value for each treatment was divided by the carrier control to obtain a fold change. B, Kaplan–Meier patient survival for all cases correlated with sensitivity of explants to cisplatin at 50 μmol/L. Data were evaluated for 26 patients/explants (Supplementary Table S1). The threshold of sensitivity/resistance to the drug was determined using an ROC curve (Supplementary Fig. S4A). The Mantel–Cox log-rank test identified a statistically significant relationship (P = 0.006) between patient survival and cisplatin sensitivity. C, Kaplan–Meier patient survival according to stage correlated with sensitivity of explants to cisplatin at 50 μmol/L. Left graph, stage I/IIA samples (n = 14, P = 0.02). Right graph, stage IIB/III samples (n = 12, P = 0.05). D, Kaplan–Meier patient survival according to adjuvant chemotherapy or lymph node involvement correlated with sensitivity of explants to cisplatin at 50 μmol/L. Left graph, subgroup of patients receiving adjuvant therapy (n = 12), including platinum-based chemotherapy (n = 8), radiotherapy (n = 3), and taxane-based chemotherapy (n = 1). The Mantel–Cox log-rank test identified a statistically significant relationship between survival of patients and response to cisplatin in explants (P = 0.01) Right graph, subgroup of patients with lymph node involvement (n = 10) for which the Mantel–Cox log-rank test did not identify a statistically significant relationship (P = 0.13) between patient survival and cisplatin sensitivity. E, Correlation of response to cisplatin in explant culture with tumor stage (left) and histology (right). The box and whiskers plots show data for difference in percentage of cPARP staining in response to 50 μmol/L cisplatin compared with control treatment for each explant relative to tumor stage/histology. The box extends from the 25th to 75th percentiles, and the lines in the middle of the boxes represent the median. The whiskers extend from the smallest to the largest values. The Jonckheere–Terpstra test for ordered alternatives showed a significant negative trend (P = 0.007) between increasing stage and cisplatin response. Correlation of tumor histology with cisplatin response demonstrated statistically significant differences between SCC samples and adenocarcinoma (ADC) types with a Mann–Whitney test of P = 0.0004.

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In addition to the 21 explants treated with a dose range of cisplatin, a further 9 were treated with a single dose of 50 μmol/L cisplatin. We obtained clinical and histopathologic information on all 30 patients and their tumors (Supplementary Table S1). Cell death difference compared with control in response to cisplatin is included alongside this information. One tumor was excluded from the analysis due to complex histopathology and 3 atypical carcinoids were excluded because of their different biologic behavior compared to adenocarcinomas and SCCs. For the remaining 26, a ROC curve was used to determine the threshold for resistance/sensitivity to cisplatin and this analysis gave an area under the curve of 0.6485 ± 0.1122 SE, a likelihood ratio of 3.30 and identified 28.45% as the optimal cutoff (Supplementary Fig. S4A).

We then categorized each explant into being either sensitive or resistant to cisplatin (Supplementary Fig. S4B and Supplementary Table S1). Using clinical information on corresponding patients (Supplementary Table S1), the relationship of cisplatin sensitivity/resistance in explant culture to patient survival post-surgery was determined (Fig. 3B). The data show a statistically significant relationship (P = 0.006) with sensitive cases demonstrating a mean survival time (MST) of 28 months and resistant cases an MST of 14 months. To rule out an effect of tumor stage, we separated stage I/IIA and IIB/III cases (Fig. 3C). There is a statistically significant relationship between cisplatin sensitivity and patient survival for both stage I/IIA cases (P = 0.02) and for stage IIB/III cases (P = 0.05), indicating the correlation is independent of stage; importantly, this relationship was also shown to be independent of stage in a multivariate Cox survival analysis. Of the 26 patients, 12 received adjuvant therapy (Supplementary Table S1), 8 received platinum-based chemotherapy, 3 received radiotherapy, and 1 received taxane-based chemotherapy. In those cases receiving any form of adjuvant therapy, there is a significant correlation with survival of patients and response to cisplatin in explants (P = 0.01; Fig. 3D, left). However, there was no relationship between cisplatin sensitivity in explants and survival for patients reported to have lymph node involvement (P = 0.13; Fig. 3D, right). Overall, the data show a strong relationship between patient survival and explant sensitivity to cisplatin, indicating that the explant platform is predictive of disease recurrence and response to adjuvant therapy.

Cisplatin sensitivity in explants was also correlated with tumor stage and histologic type (Fig. 3E). There was a significant negative trend between difference in percentage of cPARP staining compared with control in response to cisplatin and increasing tumor stage (P = 0.007), suggesting that more advanced tumors are more resistant to the drug. There was also a significant correlation between cisplatin sensitivity and tumor type (P = 0.0004), with SCC cases demonstrating greater cisplatin sensitivity than adenocarcinoma subtypes (Fig. 3E).

Cisplatin sensitivity is linked to drug accumulation in tumor areas

A number of mechanisms have been reported to render cells resistant to cisplatin including reduced drug uptake, enhanced export, drug deactivation, increased repair of DNA damage, or alterations in apoptosis (33, 34). To examine drug uptake/export, we investigated Pt ion distribution across explant tissue using LA-ICP-MS (see Supplementary Fig. S1) imaging (Fig. 4 and Supplementary Fig. S5). For resistant cases, Pt ions were depleted from areas corresponding to tumor cells but were present in the stroma (Fig. 4A and Supplementary Fig. S5). In contrast, for sensitive cases, Pt ions were present throughout the tumor and stromal areas of the explant, indicating widespread cisplatin uptake (Fig. 4B and Supplementary Fig. S5). Thus, while cisplatin is available to the resistant explants, there is decreased intracellular drug concentration in tumor cells.

Figure 4.

Pt ion distribution in cisplatin-sensitive and -resistant explants. A and B, Cisplatin-resistant explant (LT31; A) and cisplatin-sensitive explant (LT88; B). Both samples were treated with 10 μmol/L cisplatin. Serial sections of explants stained with H&E staining are shown in the top left, and IHC staining with antibodies for MNF116 (top middle), cPARP (top right), and Ki67 (bottom left) are also shown. LA-ICP-MS samplings to indicate the distribution of Pt ions within each explant are shown in the bottom right. The white lines indicate tumor areas as determined by H&E and MNF116 staining. Scale bars, 100 μm.

Figure 4.

Pt ion distribution in cisplatin-sensitive and -resistant explants. A and B, Cisplatin-resistant explant (LT31; A) and cisplatin-sensitive explant (LT88; B). Both samples were treated with 10 μmol/L cisplatin. Serial sections of explants stained with H&E staining are shown in the top left, and IHC staining with antibodies for MNF116 (top middle), cPARP (top right), and Ki67 (bottom left) are also shown. LA-ICP-MS samplings to indicate the distribution of Pt ions within each explant are shown in the bottom right. The white lines indicate tumor areas as determined by H&E and MNF116 staining. Scale bars, 100 μm.

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TP53 expression in the explants

The TP53 gene is frequently mutated in NSCLC (35). Wild-type TP53 protein is induced by DNA-damaging agents such as cisplatin, whereas mutated TP53 is either not expressed or is constitutively expressed. We utilized IHC to gain an indication of TP53 function in the 30 tumors, identifying 3 categories: (i) WTTP53 tumors (12 tumors), (ii) MUTTP53 tumors with constitutively high TP53 levels (16 tumors), and (iii) MUTTP53 tumors expressing undetectable TP53 (2 tumors). IHC TP53 staining of positive and negative tumors is shown in Fig. 5A, whereas Fig. 5B indicates induction of TP53 following treatment of a WTTP53 tumor with a dose range of cisplatin and quantitation of the staining. Overall, 40% of tumors were WTTP53 and 60% MUTTP53 based on IHC criteria (Supplementary Table S1). This is approximately consistent with the known mutation rate of TP53 in human NSCLC (34).

Figure 5.

TP53 expression. A, IHC staining of explants treated with cisplatin demonstrating tumors with constitutively high levels of nuclear TP53 in tumor cells (LT18, LT27, and LT23) or low levels of TP53 (LT116). Scale bars, 100 μm. B, IHC staining and quantitation of nuclear p53 staining in a TP53WT explant sample demonstrating dose-dependent TP53 expression following cisplatin treatment. The graph shows the percentage of mean labeling index of TP53 ±SD following treatment of the tumor sample with increasing doses of cisplatin (P = 0.0001). Scale bars, 100 μm. C, Correlation of intrinsic proliferation index with TP53 IHC staining. The graph shows the percentage of Ki67 staining of tumors classified according to TP53 IHC staining. Each circle represents one sample. D, Induction of cell death, as assessed by cPARP staining (left graph), and reduction of proliferation (right graph), as assessed by Ki67 staining, upon 50 μmol/L cisplatin treatment of 30 NSCLC ex vivo explants stratified according to their ability to induce TP53 expression upon treatment with the drug. The data show that TP53-inducible tumors have a significantly reduced (P = 0.003) ability to undergo cell death in response to cisplatin compared with TP53-noninducible tumors. The majority of these tumors are of the SCC subtype.

Figure 5.

TP53 expression. A, IHC staining of explants treated with cisplatin demonstrating tumors with constitutively high levels of nuclear TP53 in tumor cells (LT18, LT27, and LT23) or low levels of TP53 (LT116). Scale bars, 100 μm. B, IHC staining and quantitation of nuclear p53 staining in a TP53WT explant sample demonstrating dose-dependent TP53 expression following cisplatin treatment. The graph shows the percentage of mean labeling index of TP53 ±SD following treatment of the tumor sample with increasing doses of cisplatin (P = 0.0001). Scale bars, 100 μm. C, Correlation of intrinsic proliferation index with TP53 IHC staining. The graph shows the percentage of Ki67 staining of tumors classified according to TP53 IHC staining. Each circle represents one sample. D, Induction of cell death, as assessed by cPARP staining (left graph), and reduction of proliferation (right graph), as assessed by Ki67 staining, upon 50 μmol/L cisplatin treatment of 30 NSCLC ex vivo explants stratified according to their ability to induce TP53 expression upon treatment with the drug. The data show that TP53-inducible tumors have a significantly reduced (P = 0.003) ability to undergo cell death in response to cisplatin compared with TP53-noninducible tumors. The majority of these tumors are of the SCC subtype.

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As expected, TP53MUT tumors had significantly higher intrinsic levels of proliferation compared with TP53WT tumors (Fig. 5C), and the majority of TP53MUT cancers were of the SCC subtype (Fig. 5D). In terms of response to cisplatin, TP53MUT samples had significantly higher levels of cell death induction compared with TP53WT samples (Fig. 5D, left) and significantly higher levels of suppression of cell proliferation (Fig. 5D, right). These data counteract the view that TP53MUT tumors are defective in their apoptotic response to DNA damage induced by cisplatin.

Explant responses to TRAIL

TRAIL is a death receptor ligand that has been developed for therapy, although clinical trials have been disappointing (36). It is thought that preclinical in vitro studies using cell lines have not faithfully represented the clinical situation. This is supported by data demonstrating that the majority of primary human tumor cells are resistant to TRAIL receptor agonists (36–38). To investigate TRAIL sensitivity in NSCLC, 12 explants were treated with TRAIL either as a single agent or in combination with cisplatin (Fig. 6A). TRAIL alone did not elicit a strong response, except for one case (LT22) that demonstrated approximately 4-fold induction of cell death. Similarly, TRAIL did not enhance the effects of cisplatin in the majority of cases, except for one tumor (LT83) for which slightly greater cell death induction (6-fold) than cisplatin alone (4-fold) was detected (Fig. 6A and B).

Figure 6.

Response to TRAIL. A, Fold cell death induction in response to 1 μg/mL of TRAIL, 50 μmol/L cisplatin, or a combination of the two relative to the carrier control is shown. The percentage of cell death of 12 ex vivo explant cultures as determined by cPARP staining was determined after each treatment for 24 hours after an initial recovery of 16 to 20 hours. These values were divided by the value for each carrier control to calculate the fold difference. B, Representative images of cPARP staining of LT83, LT18, and LT22 treated with 1 μg/mL of TRAIL, 50 μmol/L cisplatin, or a combination of the two. Scale bars, 100 μm.

Figure 6.

Response to TRAIL. A, Fold cell death induction in response to 1 μg/mL of TRAIL, 50 μmol/L cisplatin, or a combination of the two relative to the carrier control is shown. The percentage of cell death of 12 ex vivo explant cultures as determined by cPARP staining was determined after each treatment for 24 hours after an initial recovery of 16 to 20 hours. These values were divided by the value for each carrier control to calculate the fold difference. B, Representative images of cPARP staining of LT83, LT18, and LT22 treated with 1 μg/mL of TRAIL, 50 μmol/L cisplatin, or a combination of the two. Scale bars, 100 μm.

Close modal

Predicting drug response in patients with cancer is a major challenge in the clinic. Cell line xenograft mouse models have been extensively used for preclinical drug testing, but while these models can provide an initial indication of in vivo drug efficacy, data are often not predictive of patient outcome (7, 39). Although the advent of mouse PDX models has opened up the possibility of tailoring drugs to a tumor with a specific genetic lesion (11, 40), in practice, these models are expensive and lose the characteristics of the original human tumor microenvironment over time. Here, we have perfected a rapid and low-cost platform that relies on the in situ assessment of drug responses within real human tumors. We validate this platform by showing that explant response to the standard-of-care chemotherapy drug cisplatin is related to survival of patients (P = 0.006), indicating that explant response to cisplatin is predictive of disease progression. Responses to the targeted agent TRAIL are also more consistent with clinical outcomes than standard cell line model systems (36–38). We demonstrate how the explant platform can be used to inform mechanisms of drug action by biomarker monitoring.

A number of organotypic culture systems have been previously developed for human tumors (13–18). In most of these previous systems, viability of tumors has been demonstrated for up to 7 days (13–19). Here, we identified a mild effect of cultivation after 24 hours of culture (Fig. 2C), but tissue architecture was maintained intact for up to 72 hours. Our preference is to examine drug responses immediately after cultivation to minimize any effects of culture. Correlation of organotypic culture data with patient outcomes has been previously reported for the Histoculture Drug Response Assay system (15–17). However, a disadvantage of this technique is that the endpoint requires enzymatic digestion of tissue, thus preventing assessment of the specific cell type affected by the drug. This disadvantage can be overcome by using our in situ FFPE/IHC approach.

Our data show that the majority of the cisplatin-resistant tumors are of a higher stage (Fig. 3 and Supplementary Table S1), but the ability to induce cell death in response to cisplatin does not correlate with intact TP53 (Fig. 5). In fact, we have found that TP53-mutated NSCLC cases are more sensitive to cisplatin in explants thanWTTP53 cases (Fig. 5D). Previous studies have investigated whether TP53 mutations are of prognostic value in predicting response to chemotherapy in NSCLC; the results are controversial (41). In a 35-patient study, the presence of mutant TP53 was highly indicative of resistance to cisplatin (P = 0.002) (42), while in a study involving 253 patients, TP53-positive patients had a significantly greater survival benefit from adjuvant chemotherapy compared with TP53-negative patients (43). Another report in the International Adjuvant Lung Cancer Trial (IALT), a randomized trial of adjuvant cisplatin-based chemotherapy, found no correlation between TP53 mutation and outcome in 524 patients (44). Overall, it will be important to extend analysis to a greater number of explants/patients to robustly determine the prognostic value of TP53 mutation. Lack of response to cisplatin does, however, correlate with exclusion of the drug from tumor areas (Fig. 4). Cisplatin import is mediated by the copper transporter CTR1, whereas the copper transporters ATP7A and ATP7B regulate the efflux of cisplatin (45). Resistance to cisplatin has been associated with alterations in the expression status of these transporters (46) and so it will also be important to evaluate these transporters in the explant system used here.

In summary, the explant platform provides a patient-relevant model system for the preclinical evaluation of novel anticancer agents. When combined with tumor stratification approaches, the platform has the potential for personalizing drug treatment. The technology is low-cost, rapid, and achievable within an integrated cancer translational research setting. An important next step will be to conduct a clinical study aimed at determining which patients would best respond to chemotherapy prospectively; such a study is currently being developed within our center.

No potential conflicts of interest were disclosed.

Conception and design: B. Sharp, C. Pritchard, M. MacFarlane, J.H. Pringle

Development of methodology: E. Karekla, B. Sharp, J. Le Quesne, C. Pritchard, M. MacFarlane, J.H. Pringle

Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): E. Karekla, W.-J. Liao, J. Pugh, M. MacFarlane

Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): E. Karekla, B. Sharp, J. Pugh, H. Reid, J. Le Quesne, D. Moore, C. Pritchard, M. MacFarlane, J.H. Pringle

Writing, review, and/or revision of the manuscript: E. Karekla, B. Sharp, J. Pugh, H. Reid, C. Pritchard, M. MacFarlane, J.H. Pringle

Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): E. Karekla, H. Reid, J.H. Pringle

Study supervision: C. Pritchard, M. MacFarlane, J.H. Pringle

Other (histopathologicinterpretation): J. Le Quesne

We thank Andrew Wardlaw for providing the ethical framework for this project; Hilary Marshall and Will Monteiro for support in tissue collection; thoracic surgeons at Glenfield Hospital, Leicester, for providing clinical samples; and Chris Baines for providing clinical data. We also thank Angie Gillies for assistance with histology.

This work was supported by a Medical Research Council (MRC) Doctoral Training Grant to E. Karekla, the MRC Toxicology Unit (MC A/600), and the Leicester Experimental Cancer Medicine Centre (C325/A15575 Cancer Research UK/UK Department of Health). C. Pritchard was supported by a Royal Society-Wolfson merit award.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

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