Immunotherapy response modeling by ex-vivo organ culture for lung cancer

Density of tertiary lymphoid structures and their correlation with prognosis in non-small cell lung cancer

Background

Tertiary lymphoid structures (TLS), ordered structure of tumor-infiltrating immune cells in tumor immune microenvironment (TIME), play an important role in the development and anti-tumor immunity of various cancers, including liver, colon, and gastric cancers. Previous studies have demonstrated that the presence of TLS in intra-tumoral (IT), invasive margin (IM), and peri-tumoral (PT) regions of the tumors at various maturity statuses. However, the density of TLS in different regions of non-small cell lung cancer (NSCLC) has not been extensively studied.

Methods

TLS and tumor-infiltrating immune cells were assessed using immunohistochemistry (IHC) staining in 82 NSCLC patients. Tumor samples were divided into three subregions as IT, IM and PT regions, and TLS were identified as early/primary TLS (E-TLS) or secondary/follicular TLS (F-TLS). The distribution of TLS in different maturity statuses, along with their correlation with clinicopathological characteristics and prognostic value, was assessed. Nomograms were used to predict the probability of 1-, 3-, and 5-year overall survival (OS) in patients with NSCLC.

Results

The density of TLS and proportion of F-TLS in the IT region (90.2%, 0.45/mm2, and 61.0%, respectively) were significantly higher than those in the IM region (72.0%, 0.18/mm2, and 39.0%, respectively) and PT region (67.1%, 0.16/mm2, and 40.2%, respectively). A lower density of TLS, especially E-TLS in the IM region, was correlated with better prognosis in NSCLC patients. CD20+ B cells, CD3+ T cells, CD8+ cytotoxic T cells, and CD68+ macrophages were significantly overexpressed in the IM region. CD20+ B cells and CD3+ T cells in the IM region were significantly correlated with the density of E-TLS, while no statistically significant correlation was found with F-TLS. The E-TLS density in the IM region and TNM stage were independent prognostic factors for NSCLC patients. The nomogram showed good prognostic ability.

Conclusions

A higher density of E-TLS in the IM region was associated with a worse prognosis in NSCLC patients, potentially due to the inhibition of TLS maturation caused by the increased density of suppressive immune cells at the tumor invasion front.

Short-term cultured tumor fragments to study immunotherapy combinations based on CD137 (4-1BB) agonism

Biomarkers for cancer immunotherapy are an unmet medical need. The group of Daniela Thommen at the NKI recently reported on novel methodologies based on short-term cultures of patient-derived tumor fragments whose cytokine concentrations in the supernatants and activation markers on infiltrating T cells were associated with clinical response to PD-1 blockade. We set up a similar culture technology with tumor-derived fragments using mouse tumors transplanted into syngeneic immunocompetent mice to test an agonist anti-CD137 mAb and its combinations with anti-PD-1 and/or anti-TGF-β. Increases in IFNγ concentrations in the tissue culture supernatants were detected upon in-culture activation with the anti-CD137 and anti-PD-1 mAb combinations or concanavalin A as a positive control. No other cytokine from a wide array was informative of stimulation with these mAbs. Interestingly, increases in Ki67 and other activation markers were substantiated in lymphocytes from cell suspensions gathered at the end of 72 h cultures. In mice bearing bilateral tumors in which one was excised prior to in vivo anti-CD137 + anti-PD-1 treatment to perform the fragment culture evaluation, no association was found between IFNγ production from the fragments and the in vivo therapeutic outcome in the non-resected contralateral tumors. The experimental system permitted freezing and thawing of the fragments with similar functional outcomes. Using a series of patient-derived tumor fragments from excised solid malignancies, we showed IFNγ production in a fraction of the studied cases, that was conserved in frozen/thawed fragments. The small tumor fragment culture technique seems suitable to preclinically explore immunotherapy combinations.

Tertiary Lymphoid Structure-Associated B Cells Enhance CXCL13+CD103+CD8+ Tissue-Resident Memory T-Cell Response to Programmed Cell Death Protein 1 Blockade in Cancer Immunotherapy

BACKGROUND & AIMS

Although the presence of tertiary lymphoid structures (TLS) correlates with positive responses to immunotherapy in many solid malignancies, the mechanism by which TLS enhances antitumor immunity is not well understood. The present study aimed to investigate the underlying cross talk circuits between B cells and tissue-resident memory T (Trm) cells within the TLS and to understand their role in the context of immunotherapy.

METHODS

Immunostaining and H&E staining of TLS and chemokine (C-X-C motif) ligand 13 (CXCL13)+ cluster of differentiation (CD)103+CD8+ Trm cells were performed on tumor sections from patients with gastric cancer (GC). The mechanism of communication between B cells and CXCL13+CD103+CD8+ Trm cells was determined in vitro and in vivo. The effect of CXCL13+CD103+CD8+ Trm cells in suppressing tumor growth was evaluated through anti-programmed cell death protein (PD)-1 therapy.

RESULTS

The presence of TLS and CXCL13+CD103+CD8+ Trm cells in tumor tissues favored a superior response to anti-PD-1 therapy in patients with GC. Additionally, our research identified that activated B cells enhanced CXCL13 and granzyme B secretion by CD103+CD8+ Trm cells. Mechanistically, B cells facilitated the glycolysis of CD103+CD8+ Trm cells through the lymphotoxin-α/tumor necrosis factor receptor 2 (TNFR2) axis, and the mechanistic target of rapamycin signaling pathway played a critical role in CD103+CD8+ Trm cells glycolysis during this process. Moreover, the presence of TLS and CXCL13+CD103+CD8+ Trm cells correlated with potent responsiveness to anti-PD-1 therapy in a TNFR2-dependent manner.

CONCLUSIONS

This study further reveals a crucial role for cellular communication between TLS-associated B cell and CXCL13+CD103+CD8+ Trm cells in antitumor immunity, providing valuable insights into the potential use of the lymphotoxin-α/TNFR2 axis within CXCL13+CD103+CD8+ Trm cells for advancing immunotherapy strategies in GC.

Current challenges and practical aspects of molecular pathology for non-small cell lung cancers

The continuing evolution of treatment options in thoracic oncology requires the pathologist to regularly update diagnostic algorithms for management of tumor samples. It is essential to decide on the best way to use tissue biopsies, cytological samples, as well as liquid biopsies to identify the different mandatory predictive biomarkers of lung cancers in a short turnaround time. However, biological resources and laboratory member workforce are limited and may be not sufficient for the increased complexity of molecular pathological analyses and for complementary translational research development. In this context, the surgical pathologist is the only one who makes the decisions whether or not to send specimens to immunohistochemical and molecular pathology platforms. Moreover, the pathologist can rapidly contact the oncologist to obtain a new tissue biopsy and/or a liquid biopsy if he/she considers that the biological material is not sufficient in quantity or quality for assessment of predictive biomarkers. Inadequate control of algorithms and sampling workflow may lead to false negative, inconclusive, and incomplete findings, resulting in inappropriate choice of therapeutic strategy and potentially poor outcome for patients. International guidelines for lung cancer treatment are based on the results of the expression of different proteins and on genomic alterations. These guidelines have been established taking into consideration the best practices to be set up in clinical and molecular pathology laboratories. This review addresses the current predictive biomarkers and algorithms for use in thoracic oncology molecular pathology as well as the central role of the pathologist, notably in the molecular tumor board and her/his participation in the treatment decision-making. The perspectives in this setting will be discussed.

Biomarkers and experimental models for cancer immunology investigation

The rapid advancement of tumor immunotherapies poses challenges for the tools used in cancer immunology research, highlighting the need for highly effective biomarkers and reproducible experimental models. Current immunotherapy biomarkers encompass surface protein markers such as PD-L1, genetic features such as microsatellite instability, tumor-infiltrating lymphocytes, and biomarkers in liquid biopsy such as circulating tumor DNAs. Experimental models, ranging from 3D in vitro cultures (spheroids, submerged models, air-liquid interface models, organ-on-a-chips) to advanced 3D bioprinting techniques, have emerged as valuable platforms for cancer immunology investigations and immunotherapy biomarker research. By preserving native immune components or coculturing with exogenous immune cells, these models replicate the tumor microenvironment in vitro. Animal models like syngeneic models, genetically engineered models, and patient-derived xenografts provide opportunities to study in vivo tumor-immune interactions. Humanized animal models further enable the simulation of the human-specific tumor microenvironment. Here, we provide a comprehensive overview of the advantages, limitations, and prospects of different biomarkers and experimental models, specifically focusing on the role of biomarkers in predicting immunotherapy outcomes and the ability of experimental models to replicate the tumor microenvironment. By integrating cutting-edge biomarkers and experimental models, this review serves as a valuable resource for accessing the forefront of cancer immunology investigation.

Combination of Genomic Landsscape and 3D Culture Functional Assays Bridges Sarcoma Phenotype to Target and Immunotherapy

Genomic-based precision medicine has not only improved tumour therapy but has also shown its weaknesses. Genomic profiling and mutation analysis have identified alterations that play a major role in sarcoma pathogenesis and evolution. However, they have not been sufficient in predicting tumour vulnerability and advancing treatment. The relative rarity of sarcomas and the genetic heterogeneity between subtypes also stand in the way of gaining statistically significant results from clinical trials. Personalized three-dimensional tumour models that reflect the specific histologic subtype are emerging as functional assays to test anticancer drugs, complementing genomic screening. Here, we provide an overview of current target therapy for sarcomas and discuss functional assays based on 3D models that, by recapitulating the molecular pathways and tumour microenvironment, may predict patient response to treatments. This approach opens new avenues to improve precision medicine when genomic and pathway alterations are not sufficient to guide the choice of the most promising treatment. Furthermore, we discuss the aspects of the 3D culture assays that need to be improved, such as the standardisation of growth conditions and the definition of in vitro responses that can be used as a cut-off for clinical implementation.

Functional precision oncology using patient-derived assays: bridging genotype and phenotype

Genomics-based precision medicine has revolutionized oncology but also has inherent limitations. Functional precision oncology is emerging as a complementary approach that aims to bridge the gap between genotype and phenotype by modelling individual tumours in vitro. These patient-derived ex vivo models largely preserve several tumour characteristics that are not captured by genomics approaches and enable the functional dissection of tumour vulnerabilities in a personalized manner. In this Review, we discuss several examples of personalized functional assays involving tumour organoids, spheroids and explants and their potential to predict treatment responses and drug-induced toxicities in individual patients. These developments have opened exciting new avenues for precision oncology, with the potential for successful clinical applications in contexts in which genomic data alone are not informative. To implement these assays into clinical practice, we outline four key barriers that need to be overcome: assay success rates, turnaround times, the need for standardized conditions and the definition of in vitro responders. Furthermore, we discuss novel technological advances such as microfluidics that might reduce sample requirements, assay times and labour intensity and thereby enable functional precision oncology to be implemented in routine clinical practice.

Lung Cancer Organoids: The Rough Path to Personalized Medicine

Simple Summary

Lung cancer is very difficult to cure, especially when it has spread to other parts of the body. One of the main reasons that delay the identification of effective therapies is the complexity of lung cancer cells, which can be very different among individual patients. Organoids are small aggregates of tumor cells that are generated from lung tumors and used in cancer research laboratories to study the features of tumor cells. Organoids have unique properties, as they reproduce many characteristics of the tumor derived from each specific patient. Due to their capacity to reproduce individual tumor features in the laboratory setting, organoids are an excellent system to study lung cancer and to identify functional therapies. This review summarizes the challenges encountered by researchers in the field of lung cancer organoids and describes how the advances in organoid technology may allow the future development of individualized therapies for lung cancer patients.

Abstract

Lung cancer is the leading cause of cancer death worldwide. Despite significant advances in research and therapy, a dismal 5-year survival rate of only 10–20% urges the development of reliable preclinical models and effective therapeutic tools. Lung cancer is characterized by a high degree of heterogeneity in its histology, a genomic landscape, and response to therapies that has been traditionally difficult to reproduce in preclinical models. However, the advent of three-dimensional culture technologies has opened new perspectives to recapitulate in vitro individualized tumor features and to anticipate treatment efficacy. The generation of lung cancer organoids (LCOs) has encountered greater challenges as compared to organoids derived from other tumors. In the last two years, many efforts have been dedicated to optimizing LCO-based platforms, resulting in improved rates of LCO production, purity, culture timing, and long-term expansion. However, due to the complexity of lung cancer, further advances are required in order to meet clinical needs. Here, we discuss the evolution of LCO technology and the use of LCOs in basic and translational lung cancer research. Although the field of LCOs is still in its infancy, its prospective development will likely lead to new strategies for drug testing and biomarker identification, thus allowing a more personalized therapeutic approach for lung cancer patients.

Multimodal predictors for precision immunotherapy

Immune checkpoint blockade (ICB) unleashes immune cells to attack tumors, thereby inducing durable clinical responses in many cancer types. The number of patients responding to ICB is modest, however, and combination treatments are likely needed to overcome the multifaceted suppressive pathways active in the tumor microenvironment (TME). The development of precision immuno-oncology (IO) strategies allowing to identify the optimal treatment of each patient upfront is therefore a pivotal question in the field of cancer immunotherapy. Although single-parameter biomarkers can enrich for response to ICB, their predictive capacity is far from perfect and their clinical utility is complicated by their continuous nature and the difficulty to determine cut-offs that reliably distinguish responding patients from those without clinical benefit. The antitumor immune response that is induced or reinvigorated by immunotherapy is a complex cascade of events requiring the interplay of multiple cell types. To move towards precision IO, it is therefore essential to understand for each individual patient at which level(s) the antitumor immune response failed and how it can be therapeutically restored. Holistic approaches to profile human tumor microenvironments and treatment-induced responses may help to identify critical rate-limiting factors of antitumor immunity. These factors need to be translated into clinically applicable multimodal predictors that allow for the selection of the best IO treatment. This review discusses strategies to (i) create such holistic views of antitumor immunity, (ii) identify measurable parameters capturing the complexity of a patient's immune status, and (iii) facilitate the incorporation of precision IO research in the clinic.

Biomedical Applications of Non-Small Cell Lung Cancer Spheroids

Lung malignancies accounted for 11% of cancers worldwide in 2020 and remained the leading cause of cancer deaths. About 80% of lung cancers belong to non-small cell lung cancer (NSCLC), which is characterized by extremely high clonal and morphological heterogeneity of tumors and development of multidrug resistance. The improvement of current therapeutic strategies includes several directions. First, increasing knowledge in cancer biology results in better understanding of the mechanisms underlying malignant transformation, alterations in signal transduction, and crosstalk between cancer cells and the tumor microenvironment, including immune cells. In turn, it leads to the discovery of important molecular targets in cancer development, which might be affected pharmaceutically. The second direction focuses on the screening of novel drug candidates, synthetic or from natural sources. Finally, "personalization" of a therapeutic strategy enables maximal damage to the tumor of a patient. The personalization of treatment can be based on the drug screening performed using patient-derived tumor xenografts or in vitro patient-derived cell models. 3D multicellular cancer spheroids, generated from cancer cell lines or tumor-isolated cells, seem to be a helpful tool for the improvement of current NSCLC therapies. Spheroids are used as a tumor-mimicking in vitro model for screening of novel drugs, analysis of intercellular interactions, and oncogenic cell signaling. Moreover, several studies with tumor-derived spheroids suggest this model for the choice of "personalized" therapy. Here we aim to give an overview of the different applications of NSCLC spheroids and discuss the potential contribution of the spheroid model to the development of anticancer strategies.