Cancer-Associated Lymphoid Aggregates in Histology Images: Manual and Deep Learning-Based Quantification Approaches.

Quantification of lymphoid aggregates including tertiary lymphoid structures (TLS) with germinal centers in histology images of cancer is a promising approach for developing prognostic and predictive tissue biomarkers. In this article, we provide recommendations for identifying lymphoid aggregates in tissue sections from routine pathology workflows such as hematoxylin and eosin staining. To overcome the intrinsic variability associated with manual image analysis (such as subjective decision-making, attention span), we recently developed a deep learning-based algorithm called HookNet-TLS to detect lymphoid aggregates and germinal centers in various tissues.

Sustained innate interferon is an essential inducer of tertiary lymphoid structures.

Tertiary lymphoid structures (TLS) resemble follicles of secondary lymphoid organs and develop in nonlymphoid tissues during inflammation and cancer. Which cell types and signals drive the development of TLS is largely unknown. To investigate early events of TLS development in the lungs, we repeatedly instilled p(I:C) plus ovalbumin (Ova) intranasally.

Multi-resolution deep learning characterizes tertiary lymphoid structures and their prognostic relevance in solid tumors.

Background: Tertiary lymphoid structures (TLSs) are dense accumulations of lymphocytes in inflamed peripheral tissues, including cancer, and are associated with improved survival and response to immunotherapy in various solid tumors. Histological TLS quantification has been proposed as a novel predictive and prognostic biomarker, but lack of standardized methods of TLS characterization hampers assessment of TLS densities across different patients, diseases, and clinical centers.

Methods: We introduce an approach based on HookNet-TLS, a multi-resolution deep learning model, for automated and unbiased TLS quantification and identification of germinal centers in routine hematoxylin and eosin stained digital pathology slides.

B cell-rich niches support stem-like CD8 T cells in cancer microenvironment.

Cytotoxic T cells are indispensable for the body's fight against most cancers. In the current issue of Cancer Cell, Gaglia et al. reveal how changes in the tumor tissue architecture creating niches of T cell-B cell interactions may support anti-tumor T cell responses.

The roles of tertiary lymphoid structures in chronic diseases.

Tertiary lymphoid structures (TLSs) are ectopic lymphoid tissues that drive antigen-specific immune responses at sites of chronic inflammation. Unlike secondary lymphoid organs such as lymph nodes, TLSs lack capsules and have their own unique characteristics and functions. The presumed influence of TLSs on the disease course has led to widespread interest in obtaining a better understanding of their biology and function.