Predicting immunotherapy response, resistance, side effects, and pharmacodynamics has become an important component of clinical trials. Correlative studies are used to investigate these variables by integrating tumor biopsies into the clinical trial design to understand the effect of treatment on the tumor tissue.1 Sequential biopsies are performed at different time points, such as prior to treatment and during treatment to capture pharmacodynamic or biomarker changes.1–3 These research biopsies are intended to be used for sophisticated and expensive analysis, for example, sequencing, multiplex immunofluorescence, and other assays; therefore, quality control (QC) is routinely performed to determine which biopsy specimen is most suitable for a certain analysis. One of the most important parameters during the QC is to determine how much tumor was captured in the biopsy.2 To ensure that the biopsy specimen contains tumor, some clinical trials have a cytopathologist on site during the biopsy procedure who evaluates touch preps of the biopsies. For other trials, tumor assessment is performed on an H&E-stained tissue sample after formalin fixation and paraffin embedding. The biopsy specimen with the most tumor content (TC) is the preferred sample to be used for subsequent molecular analysis.

We investigated whether the TC recorded during the QC process might be of clinical value. To the best of our knowledge, no correlative study has looked at treatment response in correlation with the data obtained during the biopsy QC of rare tumors. Hence, the purpose of this study was to determine whether the assessment of TC at baseline or on-treatment, or the shift in TC from baseline to on-treatment, can be used as a predictor of response. According to the TC assessment in resection specimens after neoadjuvant treatment, we assessed TC on an H&E stain only.4–6 To answer the question of what is the clinical value of TC assessment in biopsies from a target lesion, using a cut-off derived from evaluation of the literature on neoadjuvant treatments in different tumor types, we leveraged our ongoing correlative study for a phase II clinical trial of immune checkpoint inhibitor pembrolizumab in patients with rare tumors.

Our patient cohort (n=57) comprised 57 tumors that were biopsied at baseline and on-treatment. The tumors were represented by 352 biopsy specimens, including 173 baseline and 179 on-treatment biopsy specimens (average: 3 baseline and 3.1 on-treatment biopsy specimens per tumor) from 26 women (46%) and 31 men (54%) who were enrolled in the trial from August 2016 to August 2017 and for whom follow-up data were available. The average age at the time of enrollment was 54 years (range: 24–86 years). The trial had the following patient cohorts defined: carcinoma of unknown primary (n=9), squamous cell carcinoma of the skin (n=9), germ cell tumor/testicular tumor (n=6), adrenocortical carcinoma (n=5), paraganglioma/pheochromocytoma (n=5), small cell malignancies of non-pulmonary origin (n=4), medullary renal cell carcinoma (n=2), penile carcinoma (n=1), vascular sarcoma (n=1), and other rare tumors (n=15). The cohort of other rare tumors consisted of granulosa cell tumor, adult type (n=3), and one case each of the following histology: alveolar rhabdomyosarcoma; alveolar soft part sarcoma; clear cell adenocarcinoma of the cervix uteri; epithelioid hemangioendothelioma; granulosa cell tumor, juvenile type; mesothelioma of the testis; pituitary carcinoma; spindle cell rhabdomyosarcoma; squamous cell carcinoma of the vagina; squamous cell carcinoma of the cervix uteri; uterine inflammatory myofibroblastic tumor; and Wilms tumor. See table 1 for patient characteristics.

Certain carcinomas and other malignancies can respond to immune checkpoint inhibitors, such as renal cell carcinomas,11 small cell lung cancer,12 non-small-cell lung cancer (NSCLC),13 hepatocellular carcinoma,14 metastatic cutaneous squamous cell carcinoma,15 gastric and esophageal cancer,16 head and neck squamous cell carcinoma,17 melanoma,7 18 and others. Among rare tumors, Merkel cell carcinomas showed response to immune checkpoint inhibitors.19 In sarcomas, it seems that immune checkpoint inhibitors only show some efficacy in certain subtypes, such as alveolar soft part sarcoma.20 21

It is well known that chemotherapies can induce morphological changes within tumor tissue, including decreased tumor cellularity.22 Morphological changes also occur after immunotherapy, for example, increased inflammatory/immune cell infiltrates, necrosis, or fibrosis.2 7 13 23 24 The evaluation of TC in resection specimens after therapy represents the residual tumor cells surviving the attacks/pressure of the drug. Microscopic shrinkage of the tumor is regarded as tumor regression, and several scoring systems include the assessment of TC in surgical resection specimens after neoadjuvant therapy to determine prognosis. In several of these tumor-regression scoring systems, a cut-off of <10% residual tumor after therapy is considered significant microscopic tumor shrinkage4–6 8 9 and is reported to be associated with better prognosis in osteosarcoma6 or survival in NSCLC.9 However, whether the assessment of TC assessed in pretreatment and post-treatment biopsy specimens in rare tumors can be used to predict response is unknown. TC is routinely assessed during the QC of research biopsies, and this parameter is generally regarded as only useful for determining whether a certain biopsy can be used for additional analysis. However, we believe that TC obtained during the QC process should be regarded as a valuable parameter that might predict early responsiveness. Such data could be especially valuable when an early on-treatment biopsy is available prior to the first radiological image analysis assessment and especially in trials evaluating immune checkpoint inhibitors, where pseudo-progression has been described as a challenge for radiologists.25

We applied the cut-off of <10%, as previously described in resection specimens for different tumor types,4–6 8 9 to dichotomize TC in our biopsy specimens. We observed that a decrease in TC from baseline to on-treatment was significantly (p=0.031) associated with response to pembrolizumab. Additionally, patients with a decrease of TC had a significantly higher overall chance to remain progression-free at 6 months (p=0.0042). Further, patients with low TC in on-treatment biopsies had a longer median TTP of around 3 weeks (0.7 months, p=0.22). However, the results from baseline biopsies showed the opposite with a nearly 2 months of longer median TTP in patients with high TC (p=0.19). These results imply the importance of capturing the tumor dynamic by longitudinal tumor sampling to predict response rather than to look at a static picture at baseline or on-treatment alone using TC as a parameter in rare tumor types. This seems also to be true when using biomarkers2 and underlines the value of both baseline and on-treatment evaluation. However, a recent study by Stein et al,7 assessing 14 histological parameters and generating from these parameters a semiquantitative scale of immune-related pathological response (irPR) ranging from 0 to 3, showed that patients with advanced melanoma and an irPR score of 3 in on-treatment biopsies had better overall survival.7 Hence, the study by Stein et al 7 and our study showed that morphological parameters are important and should not be disregarded. However, comparing TC from baseline and on-treatment biopsies that are available from QC data is very time efficient since these data are already collected, whereas the assessment of several morphological parameters in on-treatment biopsies can be time-consuming but may be valuable in cases where only an on-treatment biopsy is available.

We would argue that the phenomenon of decrease in TC represents a therapy effect. It is known that tumor necrosis can occur after treatment with immune checkpoint inhibitors,7 13 23 24 and we know from the wound-healing process that remodeling of tissue occurs within hours. In myocardial infarction, for example, inflammation occurs within hours; myofibroblasts appear slightly later to construct new collagen; fibrosis can be seen within days; and solid scar formation occurs within weeks.26 We assume that the healing processes after drug-induced tumor necrosis occur quickly as well and that we see this phenomenon in on-treatment biopsies with low TC. Patients with high NC (≥10%) in on-treatment biopsies had a shorter median TTP by around 9 weeks compared with patients with low NC (2.1 months vs 4.2 months, p=n.s.), which is in line with the observation in on-treatment biopsies from melanoma, where necrosis was not associated with response.7 This is an interesting observation since we would think that more necrosis would be associated with better response. It may be that assessment of vital tumor is a better readout of the tumor dynamic under therapy than NC. Patients with no PF in their tumor had a shorter median TTP by around 4 weeks compared with patients with PF (3.2 months vs 4.2 months, p=n .s.). In melanoma, the presence of PF was significantly associated with response.7 Hence, more research is needed to evaluate whether the presence of PF correlates with response to immune checkpoint inhibitors across different tumor types.

We cannot be sure that the low TC we observed in some biopsies was not due to sampling bias, for example, that the same area of tissue was sampled as in the previous baseline biopsy; however, a TC of <10% is a very low tumor content, more likely representing general therapy-induced microscopic tumor shrinkage that was captured in the biopsy rather than a very local healing process due to a prior biopsy. In cases with no tumor content, no clear invasion, or a possible few tumor cells in the biopsy, the lesion could have been missed even though it was an image-guided biopsy and the radiologist assessed the needle as in the lesion. It is known that lesions can be missed even under image guidance.27 28 We included all biopsies/cases in our study since we wanted to assess whether prediction of response is possible using QC data without performing selection of any cases. To include all biopsies and to use a cut-off point for the shift in tumor content can be regarded as a weakness. However, selection of cases could also lead to biases, and using a certain cut-off point can always be challenged. Therefore, more investigations on this topic are needed. We would conclude that biopsies taken during early cycles of treatment are generally suitable for assessing TC to investigate response but also for investigating tumor biology and biomarker dynamics. This might be especially useful in clinical trials to obtain a signal of response even prior to the first radiological assessment. This might give the opportunity to plan an expansion cohort in cases where a response signal can be observed, or to look into prescreening for other possible treatment options for the patient in cases where no signal of response is seen. Whether QC TC can be used for further therapy decision making needs to be evaluated in additional studies across different tumor types. One could argue that sampling of only one tumor site is not representative for the systemic disease process. This might be true, but it was shown that indeed biopsy specimens from one site can capture important tumor biology for the disease.2 Further, TC assessment using an H&E slide can be easily performed by a pathologist.

In summary, to the best of our knowledge, this is the first study looking at TC in biopsy specimens of rare tumors and its utility for predicting clinical outcome using QC data. In the past, such a study would have been difficult to conduct because biopsies were not taken as often, but with the increase of research biopsies being performed during clinical trials, such analyses are now feasible. In clinical trials with longitudinal research biopsies, monitoring TC can be easily performed since TC will be assessed routinely during biopsy QC. Whether the cut-off of <10% and the assessment of the shift in TC from baseline to on-treatment will be suitable to predict response or prognosis to immune checkpoint inhibitors needs to be investigated in future studies. The extent to which TC assessment can be used for therapy decision making, such as switching treatment or changing combination regimens, needs to be determined in large cohorts. Our study had the limitation of a cohort that was too small to answer all of these questions, and sampling bias as mentioned previously could not be excluded. However, we showed that TC assessment is easy and cost-effective and worth investigating further if it can predict treatment outcomes to immune checkpoint inhibitors.