An immunohistopathological characterisation of mixed non-seminomatous germ cell tumors

Deep learning for detecting tumour-infiltrating lymphocytes in testicular germ cell tumours

Aims

To evaluate if a deep learning algorithm can be trained to identify tumour-infiltrating lymphocytes (TILs) in tissue samples of testicular germ cell tumours and to assess whether the TIL counts correlate with relapse status of the patient.

Methods

TILs were manually annotated in 259 tumour regions from 28 whole-slide images (WSIs) of H&E-stained tissue samples. A deep learning algorithm was trained on half of the regions and tested on the other half. The algorithm was further applied to larger areas of tumour WSIs from 89 patients and correlated with clinicopathological data.

Results

A correlation coefficient of 0.89 was achieved when comparing the algorithm with the manual TIL count in the test set of images in which TILs were present (n=47). In the WSI regions from the 89 patient samples, the median TIL density was 1009/mm2. In seminomas, none of the relapsed patients belonged to the highest TIL density tertile (>2011/mm2). TIL quantifications performed visually by three pathologists on the same tumours were not significantly associated with outcome. The average interobserver agreement between the pathologists when assigning a patient into TIL tertiles was 0.32 (Kappa test) compared with 0.35 between the algorithm and the experts, respectively. A higher TIL density was associated with a lower clinical tumour stage, seminoma histology and lack of lymphovascular invasion.

Conclusions

Deep learning–based image analysis can be used for detecting TILs in testicular germ cell cancer more objectively and it has potential for use as a prognostic marker for disease relapse.

Immunohistological analysis of tumour infiltrating lymphocytes in seminoma using monoclonal antibodies

Immunological characterization of tumour infiltrating lymphocytes (TIL) by immunohistological techniques was carried out in 20 cases of stage I seminoma. Routine pathological examination of these surgical specimens showed typical seminoma in 20 cases. Eighteen cases showed obvious TIL and immunohistological staining on frozen specimens was performed in 12. TIL in seminomas were predominantly T-cells but B-cells were also identified. T-cells were distributed diffusely with predominance of the CD8+ phenotype judged semiquantitatively. In contrast to the distribution of T-cells, B-cells tended to accumulate and occasionally formed lymphoid follicles. In such follicles the phenotypic pattern of B-cell antigens was comparable with secondary lymphoid follicles in lymphoid organs. There is an immunologically complex response to seminoma by the host with a predominant infiltration of cytotoxic/suppressor T-cells and functional maturation of B-cells.