Intratumoral plasma cells predict outcomes to PD-L1 blockade in non-small cell lung cancer

Tertiary lymphoid structures as potential biomarkers for cancer prediction and prognosis

Tertiary lymphoid structures (TLSs) are ectopic lymphocyte aggregates formed in non-lymphoid tissues, including cancers, and are loci for the generation of in situ anti-tumor immune responses, which play a crucial role in cancer control. The state of TLS presence in cancer and its composition can significantly impact the treatment response and prognosis of patients. TLSs have the potential to serve as predictive and prognostic biomarkers for cancer. However, the mechanisms underlying TLS formation in cancer and how the essential components of TLSs affect cancer are not fully understood. In this review, we summarized TLS formation in cancer, the value of the TLS in different states of existence, and its key constituents for cancer prediction and prognosis. Finally, we discussed the impact of cancer treatment on TLSs.

Melanoma Brain Metastasis: Biology and Therapeutic Advances

Metastasis to the brain is a frequent complication of advanced melanoma. Historically, patients with melanoma brain metastasis (MBM) have had dismal outcomes, but outcomes have improved with the development of more effective treatments, including stereotactic radiosurgery and effective immune and targeted therapies. Despite these advances, MBM remains a leading cause of death from this disease, and many therapies show decreased efficacy against these tumors compared with extracranial metastases. This differential efficacy may be because of recently revealed unique molecular and immune features of MBMs-which may also provide rational new therapeutic strategies.

Spatial multi-omics reveal intratumoral humoral immunity niches associated with tertiary lymphoid structures in pancreatic cancer immunotherapy pathologic responders

Pancreatic adenocarcinoma (PDAC) is a rapidly progressing cancer that responds poorly to immunotherapies. Intratumoral tertiary lymphoid structures (TLS) have been associated with rare long-term PDAC survivors, but the role of TLS in PDAC and their spatial relationships within the context of the broader tumor microenvironment remain unknown. We generated a spatial multi-omics atlas encompassing 26 PDAC tumors from patients treated with combination immunotherapies. Using machine learning-enabled H&E image classification models and unsupervised gene expression matrix factorization methods for spatial transcriptomics, we characterized cellular states within TLS niches spanning across distinct morphologies and immunotherapies. Unsupervised learning generated a TLS-specific spatial gene expression signature that significantly associates with improved survival in PDAC patients. These analyses demonstrate TLS-associated intratumoral B cell maturation in pathological responders, confirmed with spatial proteomics and BCR profiling. Our study also identifies spatial features of pathologic immune responses, revealing TLS maturation colocalizing with IgG/IgA distribution and extracellular matrix remodeling.

GRAPHICAL ABSTRACT

HIGHLIGHTS

Integrated multi-modal spatial profiling of human PDAC tumors from neoadjuvant immunotherapy clinical trials reveal diverse spatial niches enriched in TLS.TLS maturity is influenced by tumor location and the cellular neighborhoods in which TLS immune cells are recruited.Unsupervised machine learning of genome-wide signatures on spatial transcriptomics data characterizes the TLS-enriched TME and associates TLS transcriptomes with survival outcomes in PDAC.Interactions of spatially variable gene expression patterns showed TLS maturation is coupled with immunoglobulin distribution and ECM remodeling in pathologic responders.Intratumoral plasma cell and immunoglobin gene expression spatial dynamics demonstrate trafficking of TLS-driven humoral immunity in the PDAC TME.

Significance

We report a spatial multi-omics atlas of PDAC tumors from a series of immunotherapy neoadjuvant clinical trials. Intratumorally, pathologic responders exhibit mature TLS that propagate plasma cells into malignant niches. Our findings offer insights on the role of TLS-associated humoral immunity and stromal remodeling during immunotherapy treatment.

Dissecting transcriptome signals of anti-PD-1 response in lung adenocarcinoma

Immune checkpoint blockades are actively adopted in diverse cancer types including metastatic melanoma and lung cancer. Despite of durable response in 20-30% of patients, we still lack molecular markers that could predict the patient responses reliably before treatment. Here we present a composite model for predicting anti-PD-1 response based on tumor mutation burden (TMB) and transcriptome sequencing data of 85 lung adenocarcinoma (LUAD) patients who received anti-PD-(L)1 treatment. We found that TMB was a good predictor (AUC = 0.81) for PD-L1 negative patients (n = 20). For PD-L1 positive patients (n = 65), we built an ensemble model of 100 XGBoost learning machines where gene expression, gene set activities and cell type composition were used as input features. The transcriptome-based models showed excellent accuracy (AUC > 0.9) and highlighted the contribution of T cell activities. Importantly, nonresponder patients with high prediction score turned out to have high CTLA4 expression, which suggested that neoadjuvant CTLA4 combination therapy might be effective for these patients. Our data and analysis results provide valuable insights into developing biomarkers and strategies for treating LUAD patients using immune checkpoint inhibitors.

Development of a prognostic model for NSCLC based on differential genes in tumour stem cells

Non-small cell lung cancer (NSCLC) constitutes a significant portion of lung cancers and cytotoxic drugs (e.g. cisplatin) are currently the first-line treatment. However, NSCLC has developed resistance to this drug, which limits the therapeutic effect and thus affects prognosis. NSCLC sc-RNA-seq data were downloaded from the GEO database and Ku Leuven Laboratory for Functional Epigenetics, and bulk RNA-seq data were obtained from the TCGA database. The "Seurat" package was employed for scRNA-seq data processing, and the uniform manifold approximation and projection (UMAP) were applied for downscaling and cluster identification. Use the FindAllMarkers function to find differential genes (DEGs) for tumor stem cells. Then, we performed univariate regression analyses on the DEGs to identify potential prognostic genes. We created a machine learning framework based on potential prognostic genes, which combines 10 machine learning methods and their 101 combinations to get the optimal prognostic risk model. The model was evaluated in the training set and validation set. A nomogram was developed to provide physicians with a quantitative tool for prognosis prediction. Finally, we evaluated the expression and functionality of SLC2A1. We discovered 22 cell clusters containing 218379 cells by examining single-cell RNA sequencing datasets (GSE148071, KU_lom, GSE131907, GSE136246, GSE127465). Tumour cells were isolated for subpopulation analysis and 162 differential genes from SOX2_cancer were obtained. After univariate Cox analysis, we found 23 genes with prognostic potential prognostic value and utilized them to develop 101‑combination machine learning computational framework. We eventually picked the best performing 'StepCox[both] + RSF', which includes 8 genes. The model has a relatively high prediction accuracy in both TCGA and GEO datasets. In in vitro investigations, targeted suppression of the SLC2A1 gene resulted in significant reductions in proliferation, invasion and migration in A549 cells. In addition, a significant reduction in cisplatin resistance was seen in A549/DDP cells. The outcomes demonstrated the precision and credibility of the prognostic model for NSCLC, highlighting its potential significance in the treatment and prognosis of individuals affected by this disease. SLC2A1 may become a promising prognostic marker and a potential therapeutic target, offering valuable insights to inform clinical treatment decisions.

Phenotypic and spatial heterogeneity of CD8+ tumour infiltrating lymphocytes

CD8+ T cells are the workhorses executing adaptive anti-tumour response, and targets of various cancer immunotherapies. Latest advances have unearthed the sheer heterogeneity of CD8+ tumour infiltrating lymphocytes, and made it increasingly clear that the bulk of the endogenous and therapeutically induced tumour-suppressive momentum hinges on a particular selection of CD8+ T cells with advantageous attributes, namely the memory and stem-like exhausted subsets. A scrutiny of the contemporary perception of CD8+ T cells in cancer and the subgroups of interest along with the factors arbitrating their infiltration contextures, presented herein, may serve as the groundwork for future endeavours to probe further into the regulatory networks underlying their differentiation and migration, and optimise T cell-based immunotherapies accordingly.

Characterization of pre- and on-treatment soluble immune mediators and the tumor microenvironment in NSCLC patients receiving PD-1/L1 inhibitor monotherapy

BACKGROUND

Despite the favorable therapeutic efficacy observed with ICI monotherapy, the majority of non-small cell lung cancer (NSCLC) patients do not respond. Therefore, identifying patients who could optimally benefit from ICI treatment remains a challenge.

METHODS

Among 183 patients with advanced or recurrent NSCLC who received ICI monotherapy, we analyzed 110 patients whose pre- and post-treatment plasma samples were available. Seventy-three soluble immune mediators were measured at ICI initiation and 6 weeks later. To identify useful biomarkers, we analyzed the association of pre-treatment levels and on-treatment changes of soluble immune mediators with survival of patients. The associations of pre-treatment or on-treatment biomarkers with irAE development, PD-L1 expression, CD8+ TIL density, and neutrophil to lymphocyte ratio (NLR) were also analyzed.

RESULTS

Univariate analysis showed that pre-treatment biomarkers included 6 immune mediators, whereas on-treatment biomarkers included 8 immune mediators. Multivariate analysis showed that pre-treatment biomarkers included 4 immune mediators (CCL19, CCL21, CXCL5, CXCL10), whereas on-treatment biomarkers included 5 immune mediators (CCL7, CCL19, CCL23, CCL25, IL-32). IrAE development was associated with on-treatment change in CCL23. PD-L1 expression was associated with the pre-treatment levels of TNFSF13B and the on-treatment change in CCL25. CD8+ TIL density was associated with the pre-treatment CXCL10 level, whereas NLR was correlated with pre-treatment levels of CCL13 and CCL17.

CONCLUSION

We identified several soluble immune mediators as pre-treatment and on-treatment biomarkers of survival in patients with NSCLC treated with ICI monotherapy. Some of these biomarkers were associated with other possible predictors, including irAE development, PD-L1 expression, CD8+ TIL density and NLR. Further large-scale studies are needed to establish biomarkers for patients with NSCLC who received ICI monotherapy.

Evaluation of the Immune Response within the Tumor Microenvironment in African American and Non-Hispanic White Patients with Non-Small Cell Lung Cancer

BACKGROUND

African Americans have higher incidence and mortality from lung cancer than non-Hispanic Whites, but investigations into differences in immune response have been minimal. Therefore, we compared components of the tumor microenvironment among African Americans and non-Hispanic Whites diagnosed with non-small cell lung cancer based on PDL1 or tertiary lymphoid structure (TLS) status to identify differences of translational relevance.

METHODS

Using a cohort of 280 patients with non-small cell lung cancer from the Inflammation, Health, Ancestry, and Lung Epidemiology study (non-Hispanic White: n = 155; African American: n = 125), we evaluated PDL1 tumor proportion score (<1% vs. ≥1%) and TLS status (presence/absence), comparing differences within the tumor microenvironment based on immune cell distribution and differential expression of genes.

RESULTS

Tumors from African Americans had a higher proportion of plasma cell signatures within the tumor microenvironment than non-Hispanic Whites. In addition, gene expression patterns in African American PDL1-positive samples suggest that these tumors contained greater numbers of γδ T cells and resting dendritic cells, along with fewer CD8+ T cells after adjusting for age, sex, pack-years, stage, and histology. Investigation of differential expression of B cell/plasma cell-related genes between the two patient populations revealed that two immunoglobulin genes (IGKV2-29 and IGLL5) were associated with decreased mortality risk in African Americans.

CONCLUSIONS

In the first known race-stratified analysis of tumor microenvironment components in lung cancer based on PDL1 expression or TLS status, differences within the immune cell composition and transcriptomic signature were identified that may have therapeutic implications.

IMPACT

Future investigation of racial variation within the tumor microenvironment may help direct the use of immunotherapy.

LAMTOR1 decreased exosomal PD-L1 to enhance immunotherapy efficacy in non-small cell lung cancer

Great progress has been made in utilizing immune checkpoint blockade (ICB) for the treatment of non-small-cell lung cancer (NSCLC). Therapies targeting programmed cell death protein 1 (PD-1) and its ligand PD-L1, expressed on tumor cells, have demonstrated potential in improving patient survival rates. An unresolved issue involves immune suppression induced by exosomal PD-L1 within the tumor microenvironment (TME), particularly regarding CD8+ T cells. Our study unveiled the crucial involvement of LAMTOR1 in suppressing the exosomes of PD-L1 and promoting CD8+ T cell infiltration in NSCLC. Through its interaction with HRS, LAMTOR1 facilitates PD-L1 lysosomal degradation, thereby reducing exosomal PD-L1 release. Notably, the ability of LAMTOR1 to promote PD-L1 lysosomal degradation relies on a specific ubiquitination site and an HRS binding sequence. The findings suggest that employing LAMTOR1 to construct peptides could serve as a promising strategy for bolstering the efficacy of immunotherapy in NSCLC. The discovery and comprehension of how LAMTOR1 inhibits the release of exosomal PD-L1 offer insights into potential therapeutic strategies for improving immunotherapy. It is imperative to conduct further research and clinical trials to investigate the feasibility and efficacy of targeting LAMTOR1 in NSCLC treatment.

Comprehensive assessment of TECENTRIQ® and OPDIVO®: analyzing immunotherapy indications withdrawn in triple-negative breast cancer and hepatocellular carcinoma

Atezolizumab (TECENTRIQ®) and nivolumab (OPDIVO®) are both immunotherapeutic indications targeting programmed cell death 1 ligand 1 (PD-L1) and programmed cell death 1 (PD-1), respectively. These inhibitors hold promise as therapies for triple-negative breast cancer (TNBC) and hepatocellular carcinoma (HCC) and have demonstrated encouraging results in reducing the progression and spread of tumors. However, due to their adverse effects and low response rates, the US Food and Drug Administration (FDA) has withdrawn the approval of atezolizumab in TNBC and nivolumab in HCC treatment. The withdrawals of atezolizumab and nivolumab have raised concerns regarding their effectiveness and the ability to predict treatment responses. Therefore, the current study aims to investigate the immunotherapy withdrawal of PD-1/PD-L1 inhibitors, specifically atezolizumab for TNBC and nivolumab for HCC. This study will examine both the structural and clinical aspects. This review provides detailed insights into the structure of the PD-1 receptor and its ligands, the interactions between PD-1 and PD-L1, and their interactions with the withdrawn antibodies (atezolizumab and nivolumab) as well as PD-1 and PD-L1 modifications. In addition, this review further assesses these antibodies in the context of TNBC and HCC. It seeks to elucidate the factors that contribute to diverse responses to PD-1/PD-L1 therapy in different types of cancer and propose approaches for predicting responses, mitigating the potential risks linked to therapy withdrawals, and optimizing patient outcomes. By better understanding the mechanisms underlying responses to PD-1/PD-L1 therapy and developing strategies to predict these responses, it is possible to create more efficient treatments for TNBC and HCC.

Tertiary lymphoid structures in anticancer immunity

Tertiary lymphoid structures (TLS) are transient ectopic lymphoid aggregates where adaptive antitumour cellular and humoral responses can be elaborated. Initially described in non-small cell lung cancer as functional immune lymphoid structures associated with better clinical outcome, TLS have also been found in many other carcinomas, as well as melanomas and sarcomas, and associated with improved response to immunotherapy. The manipulation of TLS as a therapeutic strategy is now coming of age owing to the likely role of TLS in the improved survival of patients with cancer receiving immune checkpoint inhibitor treatment. TLS have also garnered considerable interest as a predictive biomarker of the response to antitumour therapies, including immune checkpoint blockade and, possibly, chemotherapy. However, several important questions still remain regarding the definition of TLS in terms of both their cellular composition and functions. Here, we summarize the current views on the composition of TLS at different stages of their development. We also discuss the role of B cells and T cells associated with TLS and their dialogue in mounting antibody and cellular antitumour responses, as well as some of the various mechanisms that negatively regulate antitumour activity of TLS. The prognostic value of TLS to the clinical outcome of patients with cancer and the relationship between TLS and the response to therapy are then addressed. Finally, we present some preclinical evidence that favours the idea that manipulating the formation and function of TLS could lead to a potent next-generation cancer immunotherapy.

An 18-gene signature of recurrence-associated endothelial cells predicts tumor progression and castration resistance in prostate cancer

BACKGROUND

The prognostic and therapeutic implications of endothelial cells (ECs) heterogeneity in prostate cancer (PCa) are poorly understood.

METHODS

We investigated associations of EC heterogeneity with PCa recurrence and castration resistance in 8 bulk transcriptomic and 4 single-cell RNA-seq cohorts. A recurrence-associated EC (RAEC) signature was constructed by comparing 11 machine learning algorithms through nested cross-validation. Functional relevances of RAEC-specific genes were also tested.

RESULTS

A subset of ECs was significantly associated with recurrence in primary PCa and named RAECs. RAECs were characteristic of tip and immature cells and were enriched in migration, angiogenesis, and collagen-related pathways. We then developed an 18-gene RAEC signature (RAECsig) representative of RAECs. Higher RAECsig scores independently predicted tumor recurrence and performed better or comparably compared to clinicopathological factors and commercial gene signatures in multiple PCa cohorts. Of the 18 RAECsig genes, FSCN1 was upregulated in ECs from PCa with higher Gleason scores; and the silencing of FSCN1, TMEME255B, or GABRD in ECs either attenuated tube formation or inhibited PCa cell proliferation. Finally, higher RAECsig scores predicted castration resistance in both primary and castration-resistant PCa.

CONCLUSION

This study establishes an endothelial signature that links a subset of ECs to prostate cancer recurrence and castration resistance.

The co-location of CD14+APOE+ cells and MMP7+ tumour cells contributed to worse immunotherapy response in non-small cell lung cancer

Intra-tumour immune infiltration is a crucial determinant affecting immunotherapy response in non-small cell lung cancer (NSCLC). However, its phenotype and related spatial structure have remained elusive. To overcome these restrictions, we undertook a comprehensive study comprising spatial transcriptomic (ST) data (28 712 spots from six samples). We identified two distinct intra-tumour infiltration patterns: immune exclusion (characterised by myeloid cells) and immune activation (characterised by plasma cells). The immune exclusion and immune activation signatures showed adverse and favourable roles in NSCLC patients' survival, respectively. Notably, CD14+APOE+ cells were recognised as the main cell type in immune exclusion samples, with increased epithelial‒mesenchymal transition and decreased immune activities. The co-location of CD14+APOE+ cells and MMP7+ tumour cells was observed in both ST and bulk transcriptomics data, validated by multiplex immunofluorescence performed on 20 NSCLC samples. The co-location area exhibited the upregulation of proliferation-related pathways and hypoxia activities. This co-localisation inhibited T-cell infiltration and the formation of tertiary lymphoid structures. Both CD14+APOE+ cells and MMP7+ tumour cells were associated with worse survival. In an immunotherapy cohort from the ORIENT-3 clinical trial, NSCLC patients who responded unfavourably exhibited higher infiltration of CD14+APOE+ cells and MMP7+ tumour cells. Within the co-location area, the MK, SEMA3 and Macrophage migration inhibitory factor (MIF) signalling pathway was most active in cell‒cell communication. This study identified immune exclusion and activation patterns in NSCLC and the co-location of CD14+APOE+ cells and MMP7+ tumour cells as contributors to immune resistance.

Re-analysis of single cell and spatial transcriptomics data reveals B cell landscape in gastric cancer microenvironment and its potential crosstalk with tumor cells for clinical prognosis

BACKGROUND

At present, immunotherapy has become a powerful treatment for advanced gastric cancer (AGC), but not all patients can benefit from it. According to the latest research, the impact of B cell subpopulations on the immune microenvironment of gastric cancer (GC) is unknown. Exploring whether the interaction between B cells and tumor cells in GC affects the effectiveness of immunotherapy has attracted our interest.

METHODS

This study involved the re-analysis of single-cell RNA (scRNA) and spatial transcriptomics (ST) data from publicly available datasets. The focus was on investigating the subpopulations and differentiation trajectories of B cells in the gastric cancer (GC) tumor immune microenvironment (TIME). Spatial transcriptomics (ST) and multiple immunofluorescence (mIF) revealed a clear co-localization pattern between B cells and tumor cells. Multiple immunotherapy datasets were collected to identify unique immunotherapy biomarkers. The unique immunotherapeutic potential of targeting CCL28 was validated through a mouse gastric cancer model. In addition, flow cytometry revealed changes in the tumor immune microenvironment targeting CCL28.

RESULTS

The re-analysis of ST data from multiple cancer types revealed a co-localization pattern between B cells and tumor cells. A significant number of IgA plasma cells were identified in the GC TIME. Five different tumor-infiltrating B cell subpopulations and two unique B cell differentiation trajectories were characterized, along with seven GC-related states. By analyzing the communication between GC cells and B cells, it was further discovered that tumor cells can influence and recruit plasma cells through CCL28-CCR10 signaling. Additionally, there was a crosstalk between GC cells and B cells. Finally, we identified the LAMA/CD44 signaling axis as a potential prognostic marker for immunotherapy through a large amount of immunotherapy data. We also validated through various animal tumor models that targeting CCL28 can significantly promote CD8+T cell infiltration and function in the TME by regulating B cell and plasma cell functions, and has the ability to synergize immunotherapy.

CONCLUSION

The co-localization and crosstalk between GC cells and B cells significantly affect the efficacy of immunotherapy, and inhibiting the CCL28-CCR10 signal axis is a potential immunotherapy target for GC. Meanwhile, LAMA/CD44 pair may be a potential adverse indicator for immunotherapy and tumor prognosis.

Case report: complete response and long-term survival on third-line immunotherapy in patient with pleural mesothelioma

Introduction

Pleural mesothelioma (PM) is a rare neoplasm with median survival time range from 8 to 14 months from diagnosis, and the 5-year survival rate less than 10%, indicating a poor prognosis. The standard treatment for unresectable PM for a long time has been polychemotherapy with pemetrexed and cisplatin for fit patients. Currently, the combination of the anti PD-1 inhibitor nivolumab and the anti-CTLA4 inhibitor ipilimumab has been recognized as the best possible frontline therapy (especially in the sarcomatoid or biphasic type) due to improved outcomes compared to the standard chemotherapy combination. There are still no established predictive biomarkers for any type of systemic therapy in this disease.

Case presentation

Patient who presented with cough and dyspnea has been diagnosed with advanced epithelioid type PM in May 2016. He was treated with three lines of therapy, including an antiangiogenic agent and immunotherapy with pembrolizumab in the third line. Immunotherapy with the PD-1 inhibitor pembrolizumab achieved a complete and prolonged response that transferred to long- term survival. Seven years from diagnosis, the patient is still alive. Histological findings showed an unusually immune-inflamed tumor microenvironment possibly leading to excellent response on immunotherapy.

Conclusions

The course of the disease in our patient points out that we need better predictive biomarkers to direct the treatment algorithm, as some of the patients, although chemorefractory to the best chemotherapy option, can sustain great benefit of second-line chemotherapy in combination with antiangiogenic agent, and especially immunotherapy, even in late lines of therapy.

Tertiary lymphoid structures in diseases: immune mechanisms and therapeutic advances

Tertiary lymphoid structures (TLSs) are defined as lymphoid aggregates formed in non-hematopoietic organs under pathological conditions. Similar to secondary lymphoid organs (SLOs), the formation of TLSs relies on the interaction between lymphoid tissue inducer (LTi) cells and lymphoid tissue organizer (LTo) cells, involving multiple cytokines. Heterogeneity is a distinguishing feature of TLSs, which may lead to differences in their functions. Growing evidence suggests that TLSs are associated with various diseases, such as cancers, autoimmune diseases, transplant rejection, chronic inflammation, infection, and even ageing. However, the detailed mechanisms behind these clinical associations are not yet fully understood. The mechanisms by which TLS maturation and localization affect immune function are also unclear. Therefore, it is necessary to enhance the understanding of TLS development and function at the cellular and molecular level, which may allow us to utilize them to improve the immune microenvironment. In this review, we delve into the composition, formation mechanism, associations with diseases, and potential therapeutic applications of TLSs. Furthermore, we discuss the therapeutic implications of TLSs, such as their role as markers of therapeutic response and prognosis. Finally, we summarize various methods for detecting and targeting TLSs. Overall, we provide a comprehensive understanding of TLSs and aim to develop more effective therapeutic strategies.

Pan-cancer single-cell dissection reveals phenotypically distinct B cell subtypes

Characterizing the compositional and phenotypic characteristics of tumor-infiltrating B cells (TIBs) is important for advancing our understanding of their role in cancer development. Here, we establish a comprehensive resource of human B cells by integrating single-cell RNA sequencing data of B cells from 649 patients across 19 major cancer types. We demonstrate substantial heterogeneity in their total abundance and subtype composition and observe immunoglobulin G (IgG)-skewness of antibody-secreting cell isotypes. Moreover, we identify stress-response memory B cells and tumor-associated atypical B cells (TAABs), two tumor-enriched subpopulations with prognostic potential, shared in a pan-cancer manner. In particular, TAABs, characterized by a high clonal expansion level and proliferative capacity as well as by close interactions with activated CD4 T cells in tumors, are predictive of immunotherapy response. Our integrative resource depicts distinct clinically relevant TIB subsets, laying a foundation for further exploration of functional commonality and diversity of B cells in cancer.

MOSBY enables multi-omic inference and spatial biomarker discovery from whole slide images

The utility of deep neural nets has been demonstrated for mapping hematoxylin-and-eosin (H&E) stained image features to expression of individual genes. However, these models have not been employed to discover clinically relevant spatial biomarkers. Here we develop MOSBY (Multi-Omic translation of whole slide images for Spatial Biomarker discoverY) that leverages contrastive self-supervised pretraining to extract improved H&E whole slide images features, learns a mapping between image and bulk omic profiles (RNA, DNA, and protein), and utilizes tile-level information to discover spatial biomarkers. We validate MOSBY gene and gene set predictions with spatial transcriptomic and serially-sectioned CD8 IHC image data. We demonstrate that MOSBY-inferred colocalization features have survival-predictive power orthogonal to gene expression, and enable concordance indices highly competitive with survival-trained multimodal networks. We identify and validate (1) an ER stress-associated colocalization feature as a chemotherapy-specific risk factor in lung adenocarcinoma, and (2) the colocalization of T effector cell vs cysteine signatures as a negative prognostic factor in multiple cancer indications. The discovery of clinically relevant biologically interpretable spatial biomarkers showcases the utility of the model in unraveling novel insights in cancer biology as well as informing clinical decision-making.

Spatial profiling of non-small cell lung cancer provides insights into tumorigenesis and immunotherapy response

Lung cancer is the second most common cancer worldwide and a leading cause of cancer-related deaths. Despite advances in targeted therapy and immunotherapy, the prognosis remains unfavorable, especially in metastatic cases. This study aims to identify molecular changes in non-small cell lung cancer (NSCLC) patients based on their response to treatment. Using tumor and matched immune cell rich peritumoral tissues, we perform a retrospective, comprehensive spatial transcriptomic analysis of a proven malignant NSCLC sample treated with immune checkpoint inhibitor (ICI). In addition to T cells, other immune cell types, such as B cells and macrophages, were also activated in responders to ICI treatment. In particular, B cells and B cell-mediated immunity pathways are consistently found to be activated. Analysis of the histologic subgroup (lung squamous cell carcinoma, LUSC; lung adenocarcinoma, LUAD) of NSCLC also confirms activation of B cell mediated immunity. Analysis of B cell subtypes shows that B cell subtypes were more activated in immune cell-rich tissues near tumor tissue. Furthermore, increased expression of B cell immunity-related genes is associated with better prognosis. These findings provide insight into predicting ICI treatment responses and identifying appropriate candidates for immunotherapy in NSCLC patients.

Tumor-associated tertiary lymphoid structures in cancer: implications for immunotherapy

INTRODUCTION

Tertiary lymphoid structures (TLS) arise at chronic inflammatory sites where they function as miniature lymph nodes to generate immune responses, which can be beneficial or detrimental, in diseases as diverse as autoimmunity, chronic infections and cancer. A growing number of studies show that a TLS presence in tumors from cancer patients treated with immune checkpoint inhibitors is closely linked with improved clinical outcomes. TLS may foster the generation of specific anti-tumor immune responses and immunological memory that recognizes a patient's own tumor. Due to repeated rounds of chronic inflammation, some tumor-associated TLS may be immunologically inactive, with immune checkpoint inhibitors functioning to revitalize them through pathway activation.

AREAS COVERED

This review summarizes work on TLS and how they mediate immune responses in human tumors. We also explore TLS as potential prognostic and predictive biomarkers for immunotherapy.

EXPERT OPINION

The presence of TLS in human tumors has been linked with a better clinical prognosis, response to treatment(s) and overall survival. TLS provide a structured microenvironment for the activation, expansion and maturation of immune cells at the tumor site. These activities can enhance the efficacy of immunotherapeutic treatments such as checkpoint inhibitors and cancer vaccines by revitalizing local anti-tumor immunity.

Demethylzeylasteral exerts potent efficacy against non-small-cell lung cancer via the P53 signaling pathway

Lung cancer has one of the highest mortality rates worldwide, with non-small-cell lung cancer (NSCLC) constituting approximately 85% of all cases. Demethylzeylasteral (DEM), extracted from Tripterygium wilfordii Hook F, exhibits notable anti-tumor properties. In this study, we revealed that DEM could effectively induce NSCLC cell apoptosis. Specifically, DEM can dose-dependently suppress the viability and migration of human NSCLC cells. RNA-seq analysis revealed that DEM regulates the P53-signaling pathway, which was further validated by assessing crucial proteins involved in this pathway. Biacore analysis indicated that DEM has high affinity with the P53 protein. The CDX model demonstrated DEM's anti-tumor actions. This work provided evidence that DEM-P53 interaction stabilizes P53 protein and triggers downstream anti-tumor activities. These findings indicate that DEM treatment holds promise as a potential therapeutic approach for NSCLC, which warrants further clinical assessment in patients with NSCLC.

Tertiary Lymphoid Structure in Tumor Microenvironment and Immunotherapy of Lung Cancer

Immune checkpoint inhibitors have opened an era of lung cancer therapy. However, a notable disparity exists in the efficacy of immunotherapy among individual patients. The tertiary lymphoid structure (TLS) is an ectopic lymphocyte aggregation that appears under pathological conditions and is the primary site of action for anti-tumor immunity. It is commonly reported that the presence of TLS within the tumor microenvironment (TME) relates to a favorable clinical prognosis and an excellent response to immunotherapy in lung cancer patients. A thorough understanding of TLS and its dynamic changes in TME has become an attractive focus for optimizing immunotherapy strategies for lung cancer. In this review, we comprehensively generalize the composition, formation, mechanism, detection methods of TLS, and summarize the role of TLS in lung cancer immunotherapy. Finally, induction of TLS is also discussed, which may provide more effective therapeutic strategies for lung cancer therapy.

MAGE-A4-Responsive Plasma Cells Promote Non-Small Cell Lung Cancer

Adaptive immunity is critical to eliminate malignant cells, while multiple tumor-intrinsic factors can alter this protective function. Melanoma antigen-A4 (MAGE-A4), a cancer-testis antigen, is expressed in several solid tumors and correlates with poor survival in non-small cell lung cancer (NSCLC), but its role in altering antitumor immunity remains unclear. We found that expression of MAGE-A4 was highly associated with the loss of PTEN , a tumor suppressor, in human NSCLC. Here we show that constitutive expression of human MAGE-A4 combined with the loss of Pten in mouse airway epithelial cells results in metastatic adenocarcinoma enriched in CD138 + CXCR4 + plasma cells, predominantly expressing IgA. Consistently, human NSCLC expressing MAGE-A4 showed increased CD138 + IgA + plasma cell density surrounding tumors. The abrogation of MAGE-A4-responsive plasma cells (MARPs) decreased tumor burden, increased T cell infiltration and activation, and reduced CD163 + CD206 + macrophages in mouse lungs. These findings suggest MAGE-A4 promotes NSCLC tumorigenesis, in part, through the recruitment and retention of IgA + MARPs in the lungs.

Immune Response following FLASH and Conventional Radiation in Diffuse Midline Glioma

PURPOSE

Diffuse midline glioma (DMG) is a fatal tumor traditionally treated with radiation therapy (RT) and previously characterized as having a noninflammatory tumor immune microenvironment (TIME). FLASH is a novel RT technique using ultra-high dose rate that is associated with decreased toxicity and effective tumor control. However, the effect of FLASH and conventional (CONV) RT on the DMG TIME has not yet been explored.

METHODS AND MATERIALS

Here, we performed single-cell RNA sequencing (scRNA-seq) and flow cytometry on immune cells isolated from an orthotopic syngeneic murine model of brainstem DMG after the use of FLASH (90 Gy/sec) or CONV (2 Gy/min) dose-rate RT and compared to unirradiated tumor (SHAM).

RESULTS

At day 4 post-RT, FLASH exerted similar effects as CONV in the predominant microglial (MG) population, including the presence of two activated subtypes. However, at day 10 post-RT, we observed a significant increase in the type 1 interferon α/β receptor (IFNAR+) in MG in CONV and SHAM compared to FLASH. In the non-resident myeloid clusters of macrophages (MACs) and dendritic cells (DCs), we found increased type 1 interferon (IFN1) pathway enrichment for CONV compared to FLASH and SHAM by scRNA-seq. We observed this trend by flow cytometry at day 4 post-RT in IFNAR+ MACs and DCs, which equalized by day 10 post-RT. DMG control and murine survival were equivalent between RT dose rates.

CONCLUSIONS

Our work is the first to map CONV and FLASH immune alterations of the DMG TIME with single-cell resolution. Although DMG tumor control and survival were similar between CONV and FLASH, we found that changes in immune compartments differed over time. Importantly, although both RT modalities increased IFN1, we found that the timing of this response was cell-type and dose-rate dependent. These temporal differences, particularly in the context of tumor control, warrant further study.

Using a pan-cancer atlas to investigate tumour associated macrophages as regulators of immunotherapy response

The paradigm for macrophage characterization has evolved from the simple M1/M2 dichotomy to a more complex model that encompasses the broad spectrum of macrophage phenotypic diversity, due to differences in ontogeny and/or local stimuli. We currently lack an in-depth pan-cancer single cell RNA-seq (scRNAseq) atlas of tumour-associated macrophages (TAMs) that fully captures this complexity. In addition, an increased understanding of macrophage diversity could help to explain the variable responses of cancer patients to immunotherapy. Our atlas includes well established macrophage subsets as well as a number of additional ones. We associate macrophage composition with tumour phenotype and show macrophage subsets can vary between primary and metastatic tumours growing in sites like the liver. We also examine macrophage-T cell functional cross talk and identify two subsets of TAMs associated with T cell activation. Analysis of TAM signatures in a large cohort of immune checkpoint inhibitor-treated patients (CPI1000 + ) identify multiple TAM subsets associated with response, including the presence of a subset of TAMs that upregulate collagen-related genes. Finally, we demonstrate the utility of our data as a resource and reference atlas for mapping of novel macrophage datasets using projection. Overall, these advances represent an important step in both macrophage classification and overcoming resistance to immunotherapies in cancer.

Tertiary lymphoid structures: new immunotherapy biomarker

Immunotherapy shows substantial advancement in cancer and is becoming widely used in clinical practice. A variety of biomarkers have been proposed to predict the efficacy of immunotherapy, but most of them have low predictive ability. Tertiary lymphoid structures (TLSs), the aggregation of multiple lymphocytes, have been found to exist in various tumor tissues. TLSs have been shown to correlate with patient prognosis and immunotherapy response. This review summarizes the characteristics of TLSs and the inducing factors of TLS formation, presents available evidence on the role of TLSs in predicting immunotherapy response in different cancers, and lastly emphasizes their predictive potential for neoadjuvant immunotherapy efficacy.

The single cell immunogenomic landscape after neoadjuvant immunotherapy combined chemotherapy in esophageal squamous cell carcinoma

Neoadjuvant immunotherapy represents promising strategy in the treatment of esophageal squamous cell carcinoma (ESCC). However, the mechanisms underlying its impact on treatment sensitivity or resistance remain a subject of controversy. In this study, we conducted single-cell RNA and T/B cell receptor (scTCR/scBCR) sequencing of CD45+ immune cells on samples from 10 patients who received neoadjuvant immunotherapy and chemotherapy. We also validated our findings using multiplexed immunofluorescence and analyzed bulk RNA-seq from other cohorts in public database. By integrating analysis of 87357 CD45+ cells, we found GZMK + effector memory T cells (Tem) were relatively enriched and CXCL13+ exhausted T cells (Tex) and regulator T cells (Treg) decreased among responders, indicating a persistent anti-tumor memory process. Additionally, the enhanced presence of BCR expansion and somatic hypermutation process within TNFRSF13B + memory B cells (Bmem) suggested their roles in antigen presentation. This was further corroborated by the evidence of the T-B co-stimulation pattern and CXCL13-CXCR5 axis. The complexity of myeloid cell heterogeneity was also particularly pronounced. The elevated expression of S100A7 in ESCC, as detected by bulk RNA-seq, was associated with an exhausted and immunosuppressive tumor microenvironment. In summary, this study has unveiled a potential regulatory network among immune cells and the clonal dynamics of their functions, and the mechanisms of exhaustion and memory conversion between GZMK + Tem and TNFRSF13B + Bmem from antigen presentation and co-stimulation perspectives during neoadjuvant PD-1 blockade treatment in ESCC.

A Pathologically Friendly Strategy for Determining the Organ-specific Spatial Tumor Microenvironment Topology in Lung Adenocarcinoma Through the Integration of snRandom-seq and Imaging Mass Cytometry

Heterogeneous organ-specific responses to immunotherapy exist in lung cancer. Dissecting tumor microenvironment (TME) can provide new insights into the mechanisms of divergent responses, the process of which remains poor, partly due to the challenges associated with single-cell profiling using formalin-fixed paraffin-embedded (FFPE) materials. In this study, single-cell nuclei RNA sequencing and imaging mass cytometry (IMC) are used to dissect organ-specific cellular and spatial TME based on FFPE samples from paired primary lung adenocarcinoma (LUAD) and metastases. Single-cell analyses of 84 294 cells from sequencing and 250 600 cells from IMC reveal divergent organ-specific immune niches. For sites of LUAD responding well to immunotherapy, including primary LUAD and adrenal gland metastases, a significant enrichment of B, plasma, and T cells is detected. Spatially resolved maps reveal cellular neighborhoods recapitulating functional units of the tumor ecosystem and the spatial proximity of B and CD4+ T cells at immunogenic sites. Various organ-specific densities of tertiary lymphoid structures are observed. Immunosuppressive sites, including brain and liver metastases, are deposited with collagen I, and T cells at these sites highly express TIM-3. This study originally deciphers the single-cell landscape of the organ-specific TME at both cellular and spatial levels for LUAD, indicating the necessity for organ-specific treatment approaches.

Automated immunoassay of serum NY-ESO-1 and XAGE1 antibodies for predicting clinical benefit with immune checkpoint inhibitor (ICI) in advanced non-small cell lung cancer

BACKGROUND

NY-ESO-1 and XAGE1 cancer/testis antigens elicit humoral and cellular immune responses in NSCLC patients. We aimed to predict clinical benefit with ICI monotherapy, using an automated immunoassay of NY-ESO-1/XAGE1 antibodies (Abs).

METHODS

This study enrolled 99 NSCLC patients who received nivolumab after chemotherapy, including 21 patients harboring EGFR, ALK, or KRAS alterations. The cutoff value (10 units/mL) of NY-ESO-1 and XAGE1 Ab was determined based on Ab levels in non-malignant controls, and NY-ESO-1/XAGE1 Abs in NSCLC were measured before nivolumab. Differences in PFS and OS between the Ab-positive and Ab-negative groups were retrospectively analyzed using Cox regression analysis after applying inverse probability of treatment weighting (IPTW).

RESULTS

NY-ESO-1/XAGE1 Abs were positive in 28 NSCLC, who responded more highly to nivolumab than the Ab-negatives (response rate 50.0% vs. 15.5 %, p < 0.0007). The IPTW-adjusted positives and negatives for NY-ESO-1/XAGE1 Abs were 24.5 and 70.2, respectively. The Ab-positives showed longer IPTW-adjusted PFS (HR = 0.59, 95 % CI: 0.39-0.90, p = 0.014) and IPTW-adjusted OS (HR = 0.51, 95 % CI: 0.32-0.81, p = 0.004) than the Ab-negatives. Among NSCLC harboring driver genes, the Ab-positives (n = 10) showed longer PFS (HR = 0.34, 95 % CI: 0.13-0.89, p = 0.029) and OS (HR = 0.27, 95 % CI: 0.098-0.75, p = 0.012) than the Ab-negatives (n = 11).

CONCLUSION

Our immunoassay of NY-ESO-1/XAGE1 Abs is probably useful for predicting the clinical benefit with nivolumab in NSCLC, including those harboring driver genes. These results suggest that our immunoassay may be useful in ICI monotherapy for NSCLC.

TimiGP-Response: the pan-cancer immune landscape associated with response to immunotherapy

Accumulating evidence suggests that the tumor immune microenvironment (TIME) significantly influences the response to immunotherapy, yet this complex relationship remains elusive. To address this issue, we developed TimiGP-Response (TIME Illustration based on Gene Pairing designed for immunotherapy Response), a computational framework leveraging single-cell and bulk transcriptomic data, along with response information, to construct cell-cell interaction networks associated with responders and estimate the role of immune cells in treatment response. This framework was showcased in triple-negative breast cancer treated with immune checkpoint inhibitors targeting the PD-1:PD-L1 interaction, and orthogonally validated with imaging mass cytometry. As a result, we identified CD8+ GZMB+ T cells associated with responders and its interaction with regulatory T cells emerged as a potential feature for selecting patients who may benefit from these therapies. Subsequently, we analyzed 3,410 patients with seven cancer types (melanoma, non-small cell lung cancer, renal cell carcinoma, metastatic urothelial carcinoma, hepatocellular carcinoma, breast cancer, and esophageal cancer) treated with various immunotherapies and combination therapies, as well as several chemo- and targeted therapies as controls. Using TimiGP-Response, we depicted the pan-cancer immune landscape associated with immunotherapy response at different resolutions. At the TIME level, CD8 T cells and CD4 memory T cells were associated with responders, while anti-inflammatory (M2) macrophages and mast cells were linked to non-responders across most cancer types and datasets. Given that T cells are the primary targets of these immunotherapies and our TIME analysis highlights their importance in response to treatment, we portrayed the pan-caner landscape on 40 T cell subtypes. Notably, CD8+ and CD4+ GZMK+ effector memory T cells emerged as crucial across all cancer types and treatments, while IL-17-producing CD8+ T cells were top candidates associated with immunotherapy non-responders. In summary, this study provides a computational method to study the association between TIME and response across the pan-cancer immune landscape, offering resources and insights into immune cell interactions and their impact on treatment efficacy.

The genomic landscape of the immune system in lung cancer: present insights and continuing investigations

Lung cancer is one of the most prevalent malignancies worldwide, contributing to over a million cancer-related deaths annually. Despite extensive research investigating the genetic factors associated with lung cancer susceptibility and prognosis, few studies have explored genetic predispositions regarding the immune system. This review discusses the most recent genomic findings related to the susceptibility to or protection against lung cancer, patient survival, and therapeutic responses. The results demonstrated the effect of immunogenetic variations in immune system-related genes associated with innate and adaptive immune responses, cytokine, and chemokine secretions, and signaling pathways. These genetic diversities may affect the crosstalk between tumor and immune cells within the tumor microenvironment, influencing cancer progression, invasion, and prognosis. Given the considerable variability in the individual immunegenomics profiles, future studies should prioritize large-scale analyses to identify potential genetic variations associated with lung cancer using highthroughput technologies across different populations. This approach will provide further information for predicting response to targeted therapy and promotes the development of new measures for individualized cancer treatment.

Neoadjuvant camrelizumab (an anti-PD-1 antibody) plus chemotherapy or apatinib (a VEGFR-2 inhibitor) for initially unresectable stage II-III non-small-cell lung cancer: a multicentre, two-arm, phase 2 exploratory study

This multicentre, two-arm, phase 2 study aimed to explore the efficacy and safety of neoadjuvant camrelizumab plus chemotherapy or apatinib in patients with initially unresectable stage II-III non-small-cell lung cancer (NSCLC). Eligible patients regardless of PD-L1 expression received neoadjuvant camrelizumab 200 mg and platinum-doublet chemotherapy every 3 weeks (arm A) or those with PD-L1-positive tumors received neoadjuvant camrelizumab and apatinib 250 mg once daily (arm B), for 2-4 cycles, followed by surgery. The primary endpoint was major pathological response (MPR) rate. Thirty patients in arm A and 21 in arm B were enrolled. Surgery rates were 50.0% (15/30) in arm A and 42.9% (9/21) in arm B, with all patients achieving R0 resections. Of these patients, the MPR and pathological complete response rates were both 20.0% (95% CI 4.3-48.1) in arm A and were 55.6% (95% CI 21.2-86.3) and 11.1% (95% CI 0.3-48.2) in arm B, respectively. The corresponding objective response rates were 33.3% (95% CI 11.8-61.6) and 55.6% (95% CI 21.2-86.3). With a median follow-up of 22.4 months (95% CI 19.0-26.0), the median event-free survival was not reached (NR; 95% CI 13.6-NR) in arm A and 16.8 months (95% CI 8.6-NR) in arm B. Grade 3 or above treatment-related adverse events occurred in eight (26.7%) patients in arm A and three (14.3%) in arm B. Biomarker analysis showed baseline TYROBP expression was predictive of treatment response in arm B. Neoadjuvant camrelizumab plus chemotherapy or apatinib exhibits preliminary efficacy and manageable toxicity in patients with initially unresectable stage II-III NSCLC.

Spatial Architecture of Myeloid and T Cells Orchestrates Immune Evasion and Clinical Outcome in Lung Cancer

Understanding the role of the tumor microenvironment (TME) in lung cancer is critical to improving patient outcomes. We identified four histology-independent archetype TMEs in treatment-naïve early-stage lung cancer using imaging mass cytometry in the TRACERx study (n = 81 patients/198 samples/2.3 million cells). In immune-hot adenocarcinomas, spatial niches of T cells and macrophages increased with clonal neoantigen burden, whereas such an increase was observed for niches of plasma and B cells in immune-excluded squamous cell carcinomas (LUSC). Immune-low TMEs were associated with fibroblast barriers to immune infiltration. The fourth archetype, characterized by sparse lymphocytes and high tumor-associated neutrophil (TAN) infiltration, had tumor cells spatially separated from vasculature and exhibited low spatial intratumor heterogeneity. TAN-high LUSC had frequent PIK3CA mutations. TAN-high tumors harbored recently expanded and metastasis-seeding subclones and had a shorter disease-free survival independent of stage. These findings delineate genomic, immune, and physical barriers to immune surveillance and implicate neutrophil-rich TMEs in metastasis.

SIGNIFICANCE

This study provides novel insights into the spatial organization of the lung cancer TME in the context of tumor immunogenicity, tumor heterogeneity, and cancer evolution. Pairing the tumor evolutionary history with the spatially resolved TME suggests mechanistic hypotheses for tumor progression and metastasis with implications for patient outcome and treatment. This article is featured in Selected Articles from This Issue, p. 897.

The tumor-driven antibody-mediated immune response in cancer

Immune cells in the tumor microenvironment play a crucial role in cancer prognosis and response to immunotherapy. Recent studies highlight the significance of tumor-infiltrating B cells and tertiary lymphoid structures as markers of favorable prognosis and patient-positive response to immune checkpoint blockers in some types of cancer. Although the presence of germinal center B cells and plasma cells in the tumor microenvironment has been established, determining their tumor reactivity remains challenging. The few known tumor targets range from viral proteins to self and altered self-proteins. The emergence of self-reactive antibodies in patients with cancer, involves the opposing forces of antigen-driven affinity increase and peripheral tolerance mechanisms. Here, B cell tumor antigen specificity and affinity maturation in tumor-directed immune responses in cancer are discussed.

Immunotherapy in Sarcoma: Current Data and Promising Strategies

Traditionally sarcomas have been considered immunologically quiet tumours, with low tumour mutational burden (TMB) and an immunosuppressive tumour microenvironment (TME), consisting of decreased T-cell infiltration and elevated levels of H1F1α, macrophages and neutrophils.1,2 However, research has shown that a subset of sarcomas are immunologically 'hot' with either high TMB, PDL-1 expression, CD8+ T cells or presence of tertiary lymphoid structures (TLS) demonstrating sensitivity to immunotherapy.3,4 Here, we review the current evidence for immunotherapy use in bone sarcomas (BS) and soft tissue sarcomas (STS), with immune checkpoint inhibitors (ICI) and adoptive cellular therapies including engineered T-cell therapies, chimeric antigen receptor (CAR) T-cell therapies, tumour infiltrating lymphocytes (TILs) and cancer vaccines and biomarkers of response.

Bulk and single-cell RNA sequencing reveal the contribution of laminin γ2 -CD44 to the immune resistance in lymphocyte-infiltrated squamous lung cancer subtype

The high heterogeneity of lung squamous cell carcinomas (LUSC) and the complex tumor microenvironment lead to non-response to immunotherapy in many patients. Therefore, characterizing the heterogeneity of the tumor microenvironment in patients with LUSC and further exploring the immune features and molecular mechanisms that lead to immune resistance will help improve the efficacy of immunotherapy in such patients. Herein, we retrospectively analyzed the RNA sequencing (RNA-seq) data of 513 LUSC samples with other multiomics and single-cell RNA-seq data and validated key features using multiplex immunohistochemistry. We divided these samples into six subtypes (CS1-CS6) based on the RNA-seq data and found that CS3 activates the immune response with a high level of lymphocyte infiltration and gathers a large number of patients with advanced-stage disease but increases the expression of exhausted markers cytotoxic T-lymphocyte associated protein 4, lymphocyte-activation gene 3, and programmed death-1. The prediction of the response to immunotherapy showed that CS3 is potentially resistant to immune checkpoint blockade therapy, and multi-omic data analysis revealed that CS3 specifically expresses immunosuppression-related proteins B cell lymphoma 2, GRB2-associated binding protein, and dual-specificity phosphatase 4 and has a high mutation ratio of the driver gene ATP binding cassette subfamily A member 13. Furthermore, single-cell RNA-seq verified lymphocyte infiltration in the CS3 subtype and revealed a positive relationship between the expression of LAMC2-CD44 and immune resistance. LAMC2 and CD44 are epithelial-mesenchymal transition-associated genes that modulate tumor proliferation, and multicolor immunofluorescence validated the negative relationship between the expression of LAMC2-CD44 and immune infiltration. Thus, we identified a lymphocyte-infiltrated subtype (CS3) in patients with LUSC that exhibited resistance to immune checkpoint blockade therapy, and the co-hyperexpression of LAMC2-CD44 contributed to immune resistance, which could potentially improve immunological efficacy by targeting this molecule pair in combination with immunotherapy.

Identification of prognostic risk model based on plasma cell markers in hepatocellular carcinoma through single-cell sequencing analysis

Hepatocellular carcinoma (HCC) represents a substantial global health burden. Tumorinfiltrating B lymphocytes (TIL-Bs) contribute to tumor progression and significantly impact the efficacy of tumor therapy. However, the characteristics of TIL-Bs in HCC and their effect on HCC therapy remain elusive. Single-cell RNA sequencing (scRNAseq) was applied to investigate the heterogeneity, cellular differentiation and cell-cell communication of TIL-Bs in HCC. Further, the Cancer Genome Atlas-liver hepatocellular carcinoma (TCGA-LIHC) and liver cancer institutes (LCI) cohorts were applied to construct and validate the plasma cell marker-based prognostic risk model. The relationship between the prognostic risk model and the responsiveness of immunotherapy and chemotherapy in patients with HCC were estimated by OncoPredict and tumor immune dysfunction and exclusion (TIDE) algorithm. Finally, we established nomogram and calibration curves to evaluate the precision of the risk score in predicating survival probability. Our data identified five subtypes of TIL-Bs in HCC, each exhibiting varying levels of infiltration in tumor tissues. The interactions between TIL-Bs and other cell types contributed to shaping distinct tumor microenvironments (TME). Moreover, we found that TIL-Bs subtypes had disparate prognostic values in HCC patients. The prognostic risk model demonstrated exceptional predictive accuracy for overall survival and exhibited varying sensitivities to immunotherapy and chemotherapy among patients with HCC. Our data demonstrated that the risk score stood as an independent prognostic predictor and the nomogram results further affirmed its strong prognostic capability. This study reveals the heterogeneity of TIL-Bs and provides a prognostic risk model based on plasma cell markers in HCC, which could prove valuable in predicting prognosis and guiding the choice of suitable therapies for patients with HCC.

Themis: advancing precision oncology through comprehensive molecular subtyping and optimization

Recent advances in tumor molecular subtyping have revolutionized precision oncology, offering novel avenues for patient-specific treatment strategies. However, a comprehensive and independent comparison of these subtyping methodologies remains unexplored. This study introduces 'Themis' (Tumor HEterogeneity analysis on Molecular subtypIng System), an evaluation platform that encapsulates a few representative tumor molecular subtyping methods, including Stemness, Anoikis, Metabolism, and pathway-based classifications, utilizing 38 test datasets curated from The Cancer Genome Atlas (TCGA) and significant studies. Our self-designed quantitative analysis uncovers the relative strengths, limitations, and applicability of each method in different clinical contexts. Crucially, Themis serves as a vital tool in identifying the most appropriate subtyping methods for specific clinical scenarios. It also guides fine-tuning existing subtyping methods to achieve more accurate phenotype-associated results. To demonstrate the practical utility, we apply Themis to a breast cancer dataset, showcasing its efficacy in selecting the most suitable subtyping methods for personalized medicine in various clinical scenarios. This study bridges a crucial gap in cancer research and lays a foundation for future advancements in individualized cancer therapy and patient management.

Association of pretreatment neutrophil-to-lymphocyte ratio with clinical outcomes in cancer immunotherapy: An evidence synthesis from 30 meta-analyses

BACKGROUND

The Neutrophil-to-lymphocyte ratio (NLR) holds relevance in cancer immunotherapy outcomes, yet its validation remains limited. Thus, we conducted an umbrella review to comprehensively assess the association between pretreatment NLR and immunotherapy outcomes, along with evaluating their credibility and strength.

METHODS

Electronic databases, including PubMed, Web of Science, Embase, Scopus, and Cochrane, were systematically searched for eligible systematic reviews and meta-analyses. Quality assessment and evidence grading utilized AMSTAR, GRADE, and additional classification criteria, following PRISMA and PRIOR guidelines.

RESULTS

Thirty unique meta-analyses were included, with 24 associations (80%) exhibiting statistical significance. Notably, associations between pretreatment NLR and the prognosis of renal cell carcinoma, hepatocellular carcinoma, melanoma, and non-small cell lung cancer garnered highly suggestive or convincing evidence grading.

CONCLUSIONS

Elevated pretreatment NLR correlates with poor outcomes in cancer immunotherapy, suggesting its potential as a biomarker for identifying appropriate treatment populations and predicting clinical outcomes. Nevertheless, further validation through prospective cohort studies is warranted.

A blueprint for tumor-infiltrating B cells across human cancers

B lymphocytes are essential mediators of humoral immunity and play multiple roles in human cancer. To decode the functions of tumor-infiltrating B cells, we generated a B cell blueprint encompassing single-cell transcriptome, B cell-receptor repertoire, and chromatin accessibility data across 20 different cancer types (477 samples, 269 patients). B cells harbored extraordinary heterogeneity and comprised 15 subsets, which could be grouped into two independent developmental paths (extrafollicular versus germinal center). Tumor types grouped into the extrafollicular pathway were linked with worse clinical outcomes and resistance to immunotherapy. The dysfunctional extrafollicular program was associated with glutamine-derived metabolites through epigenetic-metabolic cross-talk, which promoted a T cell-driven immunosuppressive program. These data suggest an intratumor B cell balance between extrafollicular and germinal-center responses and suggest that humoral immunity could possibly be harnessed for B cell-targeting immunotherapy.

Intratumoral CD38+CD19+B cells associate with poor clinical outcomes and immunosuppression in patients with pancreatic ductal adenocarcinoma

BACKGROUND

The widespread involvement of tumor-infiltrating B cells highlights their potential role in tumor behavior. However, B cell heterogeneity in PDAC remains unexplored. Studying TIL-Bs in PDAC aims to identify new treatment strategies.

METHODS

We performed single-cell RNA sequencing to study the heterogeneity of B cells in PDAC. The prognostic and immunologic value of the identified CD38+ B cells was explored in FUSCC (n = 147) and TCGA (n = 176) cohorts. Flow cytometry was conducted to characterize the relationship between CD38+ B cells and other immune cells, as well as their phenotypic features. In vitro and in vivo experiments were performed to assess the putative effect of CD38+ B cells on antitumor immunity.

FINDINGS

The presence of CD38+ B cells in PDAC was associated with unfavorable clinicopathological features and poorer overall survival (p < 0.001). Increased infiltration of CD38+ B cells was accompanied by reduced natural killer (NK) cells (p = 0.021) and increased regulatory T cells (p = 0.016). Molecular profiling revealed high expression of IL-10, IL-35, TGF-β, GZMB, TIM-1, CD5 and CD21, confirming their putative regulatory B cell-like features. Co-culture experiments demonstrated suppression of NK cell cytotoxicity by CD38+ B cell-derived IL-10 (p < 0.001). Finally, in vivo experiments suggested adoptive transfer of CD38+ B cells reduced antitumor immunity and administration of a CD38 inhibitor hampered tumor growth (p < 0.001).

INTERPRETATION

We discovered regulatory B cell-like CD38+ B cell infiltration as an independent prognostic factor in PDAC. The use of CD38 inhibitor may provide new possibilities for PDAC immunotherapy.

FUNDING

This study was supported by the National Natural Science Foundation of China (U21A20374), Shanghai Municipal Science and Technology Major Project (21JC1401500), Scientific Innovation Project of Shanghai Education Committee (2019-01-07-00-07-E00057), Special Project for Clinical Research in the Health Industry of the Shanghai Health Commission (No. 20204Y0265) and Natural Science Foundation of Shanghai (23ZR1479300).

Tumour-reactive plasma cells in antitumour immunity: current insights and future prospects

Tumour-reactive plasma cells (TRPCs) have been reported to be positively associated with the long-term survival of patients with various cancers. However, unlike tumour-specific antigen (TSA)-induced T cells which have precise effects against tumours, plasma cells require TSA to obtain specific responses. Therefore, the search for a TSA suitable for B-cell recognition is urgent. In this review, we discuss the functions of tumour-reactive plasma cells. Further, this review also explores the concept of screening for neoantigen-reactive plasma cells, drawing inspiration from T-cell screening methods. While challenges exist, such as epitope prediction and efficient screening, the development of novel techniques may lead to the discovery of highly specific plasma cells for adoptive cell therapy. In conclusion, tumour-reactive plasma cells are emerging as powerful players in cancer immunotherapy. Their ability to produce antibodies against a variety of antigens, especially neoantigens, opens new avenues for personalised treatments. Overcoming challenges in epitope prediction and screening will be crucial in harnessing the full potential of these plasma cells for the benefit of cancer patients.

Tumor immune dysfunction and exclusion subtypes in bladder cancer and pan-cancer: a novel molecular subtyping strategy and immunotherapeutic prediction model

BACKGROUND

Molecular subtyping is expected to enable precise treatment. However, reliable subtyping strategies for clinical application remains defective and controversial. Given the significance of tumor immune dysfunction and exclusion (TIDE), we aimed to develop a novel TIDE-based subtyping strategy to guide personalized immunotherapy in the bladder cancer (BC).

METHODS

Transcriptome data of BC was used to evaluate the heterogeneity and the status of TIDE patterns. Subsequently, consensus clustering was applied to classify BC patients based on TIDE marker-genes. Patients' clinicopathological, molecular features and signaling pathways of the different TIDE subtypes were well characterized. We also utilize the deconvolution algorithms to analyze the tumor microenvironment, and further explore the sensitivity and mechanisms of each subtype to immunotherapy. Furthermore, BC patient clinical information, real-world BC samples and urine samples were collected for the validation of our findings, which were used for RNA-seq analysis, H&E staining, immunohistochemistry and immunofluorescence staining, and enzyme-linked immunosorbent assay. Finally, we also explored the conservation of our novel TIDE subtypes in pan-cancers.

RESULTS

We identified 69 TIDE biomarker genes and classified BC samples into three subtypes using consensus clustering. Subtype I showed the lowest TIDE status and malignancy with the best prognosis and highest sensitivity to immune checkpoint blockade (ICB) treatment, which was enriched of metabolic related signaling pathways. Subtype III represented the highest TIDE status and malignancy with the poorest prognosis and resistance to ICB treatment, resulting from its inhibitory immune microenvironment and T cell terminal exhaustion. Subtype II was in a transitional state with intermediate TIDE level, malignancy, and prognosis. We further confirmed the existence and characteristics of our novel TIDE subtypes using real-world BC samples and collected patient clinical data. This subtyping method was proved to be more efficient than previous known methods in identifying non-responders to immunotherapy. We also propose that combining our TIDE subtypes with known biomarkers can potentially improve the sensitivity and specificity of these biomarkers. Moreover, besides guiding ICB treatment, this classification approach can assist in selecting the frontline or recommended drugs. Finally, we confirmed that the TIDE subtypes are conserved across the pan-tumors.

CONCLUSIONS

Our novel TIDE-based subtyping method can serve as a powerful clinical tool for BC and pan-cancer patients, and potentially guiding personalized therapy decisions for selecting potential beneficiaries and excluding resistant patients of ICB therapy.

B cells and the coordination of immune checkpoint inhibitor response in patients with solid tumors

Immunotherapy profoundly changed the landscape of cancer therapy by providing long-lasting responses in subsets of patients and is now the standard of care in several solid tumor types. However, immunotherapy activity beyond conventional immune checkpoint inhibition is plateauing, and biomarkers are overall lacking to guide treatment selection. Most studies have focused on T cell engagement and response, but there is a growing evidence that B cells may be key players in the establishment of an organized immune response, notably through tertiary lymphoid structures. Mechanisms of B cell response include antibody-dependent cellular cytotoxicity and phagocytosis, promotion of CD4+ and CD8+ T cell activation, maintenance of antitumor immune memory. In several solid tumor types, higher levels of B cells, specific B cell subpopulations, or the presence of tertiary lymphoid structures have been associated with improved outcomes on immune checkpoint inhibitors. The fate of B cell subpopulations may be widely influenced by the cytokine milieu, with versatile roles for B-specific cytokines B cell activating factor and B cell attracting chemokine-1/CXCL13, and a master regulatory role for IL-10. Roles of B cell-specific immune checkpoints such as TIM-1 are emerging and could represent potential therapeutic targets. Overall, the expanding field of B cells in solid tumors of holds promise for the improvement of current immunotherapy strategies and patient selection.

Gene features of tumor-specific T cells relevant to immunotherapy, targeted therapy and chemotherapy in lung cancer

1 Background

In lung cancer, the use of small-molecule inhibitors, chemotherapy and immunotherapy has led to unprecedented survival benefits in selected patients. Considering most patients will experience a relapse within a short period of time due to single drug resistance, combination therapy is also particularly important to improve patient prognosis. Therefore, more robust biomarkers to predict responses to immunotherapy, targeted therapy, chemotherapy and rationally drug combination therapies may be helpful in clinical treatment choices.

2 Methods

We defined tumor-specific T cells (TSTs) and their features (TSTGs) by single-cell RNA sequencing. We applied LASSO regression to filter out the most survival-relevant TSTGs to form the Tumor-specific T cell score (TSTS). Immunological characteristics, enriched pathways, and mutation were evaluated in high- and low TSTS groups.

3 Results

We identified six clusters of T cells as TSTs in lung cancer, and four most robust genes from 9 feature genes expressed only on tumor-specific T cells were screened to construct a tumor-specific T cells score (TSTS). TSTS was positively correlated with immune infiltration and angiogenesis and negatively correlated with malignant cell proliferation. Moreover, potential vascular-immune crosstalk in lung cancer provides the theoretical basis for combined anti-angiogenic and immunotherapy. Noticeable, patients in high TSTS had better response to ICB and targeted therapy and patients in the low TSTS group often benefit from chemotherapy.

4 Conclusion

The proposed TSTS is a promising indicator to predict immunotherapy, targeted therapy and chemotherapy responses in lung cancer patients for helping clinical treatment choices.

Exploiting Tertiary Lymphoid Structures to Stimulate Antitumor Immunity and Improve Immunotherapy Efficacy

Tumor-associated tertiary lymphoid structures (TLS) have been associated with favorable clinical outcomes and response to immune checkpoint inhibitors in many cancer types, including non-small cell lung cancer. Although the detailed cellular and molecular mechanisms underlying these clinical associations have not been fully elucidated, growing preclinical and clinical studies are helping to elucidate the mechanisms at the basis of TLS formation, composition, and regulation of immune responses. However, a major challenge remains how to exploit TLS to enhance naïve and treatment-mediated antitumor immune responses. Here, we discuss the current understanding of tumor-associated TLS, preclinical models that can be used to study them, and potential therapeutic interventions to boost TLS formation, with a particular focus on lung cancer research.

Tertiary lymphoid structural heterogeneity determines tumour immunity and prospects for clinical application

Tertiary lymphoid structures (TLS) are clusters of immune cells that resemble and function similarly to secondary lymphoid organs (SLOs). While TLS is generally associated with an anti-tumour immune response in most cancer types, it has also been observed to act as a pro-tumour immune response. The heterogeneity of TLS function is largely determined by the composition of tumour-infiltrating lymphocytes (TILs) and the balance of cell subsets within the tumour-associated TLS (TA-TLS). TA-TLS of varying maturity, density, and location may have opposing effects on tumour immunity. Higher maturity and/or higher density TLS are often associated with favorable clinical outcomes and immunotherapeutic response, mainly due to crosstalk between different proportions of immune cell subpopulations in TA-TLS. Therefore, TLS can be used as a marker to predict the efficacy of immunotherapy in immune checkpoint blockade (ICB). Developing efficient imaging and induction methods to study TA-TLS is crucial for enhancing anti-tumour immunity. The integration of imaging techniques with biological materials, including nanoprobes and hydrogels, alongside artificial intelligence (AI), enables non-invasive in vivo visualization of TLS. In this review, we explore the dynamic interactions among T and B cell subpopulations of varying phenotypes that contribute to the structural and functional diversity of TLS, examining both existing and emerging techniques for TLS imaging and induction, focusing on cancer immunotherapies and biomaterials. We also highlight novel therapeutic approaches of TLS that are being explored with the aim of increasing ICB treatment efficacy and predicting prognosis.

Plasma cell signatures predict prognosis and treatment efficacy for lung adenocarcinoma

PURPOSE

This study aims to identify key genes regulating tumor infiltrating plasma cells (PC) and provide new insights for innovative immunotherapy.

METHODS

Key genes related to PC were identified using machine learning in lung adenocarcinoma (LUAD) patients. A prognostic model called PC scores was developed using TCGA data and validated with GEO cohorts. We assessed the molecular background, immune features, and drug sensitivity of the high PC scores group. Real-time PCR was utilized to assess the expression of hub genes in both localized LUAD patients and LUAD cell lines.

RESULTS

We constructed PC scores based on seventeen PC-related hub genes (ELOVL6, MFI2, FURIN, DOK1, ERO1LB, CLEC7A, ZNF431, KIAA1324, NUCB2, TXNDC11, ICAM3, CR2, CLIC6, CARNS1, P2RY13, KLF15, and SLC24A4). Higher age, TNM stage, and PC scores independently predicted shorter overall survival. The AUC value of PC scores for one year, three years, and five years of overall survival were 0.713, 0.716, and 0.690, separately. The nomogram model that integrated age, stage, and PC scores showed significantly higher predictive value than stage alone (P < 0.01). High PC scores group exhibited an immune suppressing microenvironment with lower B, CD8 + T, CD4 + T, and dendritic cell infiltration. Docetaxel, gefitinib, and erlotinib had lower IC50 in high PC groups (P < 0.001). After validation through the local cohort and in vitro experiments, we ultimately confirmed three key potential targets: MFI2, KLF15, and CLEC7A.

CONCLUSION

We proposed a prediction mode which can effectively identify high-risk LUAD patients and found three novel genes closely correlated with PC tumor infiltration.

Tertiary lymphoid structures and B cells determine clinically relevant T cell phenotypes in ovarian cancer

Intratumoral tertiary lymphoid structures (TLSs) have been associated with improved outcome in various cohorts of patients with cancer, reflecting their contribution to the development of tumor-targeting immunity. Here, we demonstrate that high-grade serous ovarian carcinoma (HGSOC) contains distinct immune aggregates with varying degrees of organization and maturation. Specifically, mature TLSs (mTLS) as forming only in 16% of HGSOCs with relatively elevated tumor mutational burden (TMB) are associated with an increased intratumoral density of CD8+ effector T (TEFF) cells and TIM3+PD1+, hence poorly immune checkpoint inhibitor (ICI)-sensitive, CD8+ T cells. Conversely, CD8+ T cells from immunologically hot tumors like non-small cell lung carcinoma (NSCLC) are enriched in ICI-responsive TCF1+ PD1+ T cells. Spatial B-cell profiling identifies patterns of in situ maturation and differentiation associated with mTLSs. Moreover, B-cell depletion promotes signs of a dysfunctional CD8+ T cell compartment among tumor-infiltrating lymphocytes from freshly isolated HGSOC and NSCLC biopsies. Taken together, our data demonstrate that - at odds with NSCLC - HGSOC is associated with a low density of follicular helper T cells and thus develops a limited number of mTLS that might be insufficient to preserve a ICI-sensitive TCF1+PD1+ CD8+ T cell phenotype. These findings point to key quantitative and qualitative differences between mTLSs in ICI-responsive vs ICI-irresponsive neoplasms that may guide the development of alternative immunotherapies for patients with HGSOC.

A signature of enhanced proliferation associated with response and survival to anti-PD-L1 therapy in early-stage non-small cell lung cancer

In early-stage non-small cell lung cancer, the combination of neoadjuvant anti-PD-L1 and subablative stereotactic body radiation therapy (SBRT) is associated with higher rates of major pathologic response compared to anti-PD-L1 alone. Here, we identify a 140-gene set, enriched in genes characteristic of highly proliferating cells, associated with response to the dual therapy. Analysis of on-treatment transcriptome data indicate roles for T and B cells in response. The 140-gene set is associated with disease-free survival when applied to the combined trial arms. This 140-gene set identifies a subclass of tumors in all 7 of The Cancer Genome Atlas tumor types examined. Worse survival is associated with the 140-gene signature in 5 of these tumor types. Collectively, our data support that this 140-gene set, discovered in association with response to combined anti-PD-L1 and SBRT, identifies a clinically aggressive subclass of solid tumors that may be more likely to respond to immunotherapies.