Spatial immunoprofiling of the intratumoral and peritumoral tissue of renal cell carcinoma patients.
Oscar BrückMoon Hee LeeRiku TurkkiIlona UskiPatrick PenttiläLassi PaavolainenPanu KovanenPetrus JärvinenPetri BonoTeijo PellinenMohamed El MissiryAnna KreutzmanPublished in: Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc (2021)
While the abundance and phenotype of tumor-infiltrating lymphocytes are linked with clinical survival, their spatial coordination and its clinical significance remain unclear. Here, we investigated the immune profile of intratumoral and peritumoral tissue of clear cell renal cell carcinoma patients (n = 64). We trained a cell classifier to detect lymphocytes from hematoxylin and eosin stained tissue slides. Using unsupervised classification, patients were further classified into immune cold, hot and excluded topographies reflecting lymphocyte abundance and localization. The immune topography distribution was further validated with The Cancer Genome Atlas digital image dataset. We showed association between PBRM1 mutation and immune cold topography, STAG1 mutation and immune hot topography and BAP1 mutation and immune excluded topography. With quantitative multiplex immunohistochemistry we analyzed the expression of 23 lymphocyte markers in intratumoral and peritumoral tissue regions. To study spatial interactions, we developed an algorithm quantifying the proportion of adjacent immune cell pairs and their immunophenotypes. Immune excluded tumors were associated with superior overall survival (HR 0.19, p = 0.02) and less extensive metastasis. Intratumoral T cells were characterized with pronounced expression of immunological activation and exhaustion markers such as granzyme B, PD1, and LAG3. Immune cell interaction occurred most frequently in the intratumoral region and correlated with CD45RO expression. Moreover, high proportion of peritumoral CD45RO+ T cells predicted poor overall survival. In summary, intratumoral and peritumoral tissue regions represent distinct immunospatial profiles and are associated with clinicopathologic characteristics.
Keyphrases
- end stage renal disease
- newly diagnosed
- chronic kidney disease
- ejection fraction
- poor prognosis
- machine learning
- peritoneal dialysis
- deep learning
- squamous cell carcinoma
- single cell
- renal cell carcinoma
- binding protein
- patient reported outcomes
- mass spectrometry
- long non coding rna
- papillary thyroid
- body composition
- dna methylation
- high resolution
- atomic force microscopy
- high speed
- cell therapy