Summary and future perspectives 237 7 mm2) tumors. In contrast, PD-1T high tumors showed a higher number of PD-1T TILs both within and outside TLS, potentially explaining the difference in predictive performance. These results suggest that the expansion of PD-1T TILs, both within TLS and within the tumor parenchyma, is essential for an effective response to PD-1 blockade therapy. Digitally quantifying PD-1T TILs in both tumor regions separately and across larger study cohorts is necessary to confirm these results. Additionally, spatial profiling of TLS-associated and intratumoral PD-1T TIL subsets would be valuable to investigate whether TLS actively participate in the anti-tumor immune response during ICB treatment or if they are solely a characteristic of an inflamed TME. Therefore, gaining insight into how TLS shape the state and reactivation of tumor-specific T cells is imperative. This understanding could potentially improve biomarker development and, for instance, by inducing TLS formation, create opportunities for novel therapeutic strategies. Chapter 2; confounding factors on the predictive potential of PD-1T TILs In clinical practice, biopsy sampling for biomarker testing is typically guided by factors such as the size of the lesion, accessibility, and the likelihood of obtaining accurate information. Usually, only one lesion is sampled, even in cases of advanced disease with multiple metastases. In stage IV disease, this commonly involves core needle biopsies or, in cases of oligoprogression, surgical resection of a metastasic lesion. Previous clinical trials of PD-(L)1 blockade monotherapy, which included PD-L1 immunohistochemical (IHC) testing, did not impose specific requirements regarding the type or location of the biopsy samples (i.e. primary versus metastases), resulting in a heterogenous mix of samples. PD-L1 IHC results can be influenced by several factors such as heterogeneity within the same tumor (spatial heterogeneity), sampling time between two different treatments (temporal heterogeneity), as well as differences in sampling between primary and metastatic tumor sites18–21. This leads to an important question: ‘How should clinicians define the optimal sample that is most representative?’ To this end, we examined several potential confounding factors at the sample level for PD‑1T TILs. We observed a trend toward increased predictive accuracy of PD-1T TILs when assessing tumor resections compared to biopsies. This aligns with expectations, as regional differences within the same tumor can be more precisely delineated in resected specimens. To investigate spatial heterogeneity, we quantified PD‑1T TILs in randomly selected small areas of resected specimens. While we did observe a certain degree of variability, the samples were classified as either PD-1T high or PD-1T low. We established this biomarker cut-off as the most predictive for discriminating treatment benefit from disease progression. Our findings indicate that it is possible to detect PD-1T
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