Identification of Candidate Partner Cells in Tumor–Stromal Interactions by Histology-Based Spatial Analysis for Prognostic Stratification After Neoadjuvant Chemotherapy
- 1Department of Pathology, Yamagata University, Faculty of Medicine, 2-2-2 Iida-Nishi, Yamagata 990-9585, Japan
- 2Department of Surgery 1, Yamagata University, Faculty of Medicine, Yamagata 990-9585, Japan
Abstract
Despite advances in multidisciplinary treatment, recurrence remains a major clinical challenge in refractory cancers. Many patients have residual tumor after neoadjuvant chemotherapy (NAC), and clinical outcomes among patients without a pathological complete response (non-pCR) are heterogeneous. The spatial relationships between residual tumor cells and surrounding stromal cells may provide information for further prognostic stratification. In this review, we discuss histology-based spatial analysis (HSA) of surgical specimens, with particular attention to pancreatic ductal adenocarcinoma. We describe four steps that connect existing biological, histological, and clinical findings. First, intercellular distances and local cell numbers are compared to identify candidate partner cells. Second, functional and molecular studies examine their interactions with tumor cells, including effects on survival and drug resistance. Third, HSA of immunostained patient specimens measures the number, size, and localization of foci containing cell relationships supported by these studies. Fourth, these measurements are evaluated in relation to recurrence and survival, alongside established clinicopathological factors. This approach uses archival surgical specimens to connect biological findings with patient outcomes. Its value for prognostic stratification after NAC requires validation in large clinical cohorts.
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BibTeX
@article{aung2026identification,
title = {{Identification of Candidate Partner Cells in Tumor–Stromal Interactions by Histology-Based Spatial Analysis for Prognostic Stratification After Neoadjuvant Chemotherapy}},
author = {Naing Ye Aung and Takanobu Kabasawa and Yuki Hamada and Fuyuhiko Motoi and Mitsuru Futakuchi},
journal = {Cancers},
year = {2026},
month = oct,
doi = {10.3390/cancers18213450},
url = {https://www.mdpi.com/2072-6694/18/21/3450},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Identification of Candidate Partner Cells in Tumor–Stromal Interactions by Histology-Based Spatial Analysis for Prognostic Stratification After Neoadjuvant Chemotherapy
AU - Naing Ye Aung
AU - Takanobu Kabasawa
AU - Yuki Hamada
AU - Fuyuhiko Motoi
AU - Mitsuru Futakuchi
PY - 2026
DA - 2026/10/26
JO - Cancers
DO - 10.3390/cancers18213450
UR - https://www.mdpi.com/2072-6694/18/21/3450
AB - Despite advances in multidisciplinary treatment, recurrence remains a major clinical challenge in refractory cancers. Many patients have residual tumor after neoadjuvant chemotherapy (NAC), and clinical outcomes among patients without a pathological complete response (non-pCR) are heterogeneous. The spatial relationships between residual tumor cells and surrounding stromal cells may provide information for further prognostic stratification. In this review, we discuss histology-based spatial analysis (HSA) of surgical specimens, with particular attention to pancreatic ductal adenocarcinoma. We describe four steps that connect existing biological, histological, and clinical findings. First, intercellular distances and local cell numbers are compared to identify candidate partner cells. Second, functional and molecular studies examine their interactions with tumor cells, including effects on survival and drug resistance. Third, HSA of immunostained patient specimens measures the number, size, and localization of foci containing cell relationships supported by these studies. Fourth, these measurements are evaluated in relation to recurrence and survival, alongside established clinicopathological factors. This approach uses archival surgical specimens to connect biological findings with patient outcomes. Its value for prognostic stratification after NAC requires validation in large clinical cohorts.
SN - 2072-6694
ER -