T-cell repertoire diversity: friend or foe for protective antitumor response?

Integrated spatial and multimodal single-cell transcriptomics reveal patient-dependent cell heterogeneity in splenic marginal zone lymphoma

Biological hallmarks of splenic marginal zone lymphoma (SMZL) remain poorly described. Herein, we performed in-depth SMZL characterization through multimodal single-cell analyses of paired blood/spleen samples. The 3'-single-cell RNA-sequencing, Cellular Indexing of Transcriptomes and Epitopes by sequencing, and 5'-V(D)J single-cell RNA-sequencing datasets were integrated to characterize SMZL transcriptome profiles, including B-cell receptor and T-cell receptor repertoires. Hyperexpanded B-cell clones in the spleen were at a memory-like stage, whereas recirculating tumor B-cells in blood encompassed multiple differentiation stages, indicating an unexpected desynchronization of the B-cell maturation program in SMZL cells. Spatial transcriptomics showed the enrichment of T-effector and T-follicular helper (TFH) signatures in the nodular subtype of SMZL. This latter also exhibited gene-based cell-cell interactions suggestive of dynamic crosstalk between TFH and cancer cells in transcriptomics, further substantiated by using imaging mass cytometry. Our findings provide a comprehensive high-resolution description of SMZL biological hallmarks and characterize, for the first time in situ, inter- and intra-patient heterogeneity at both transcriptomic and protein levels. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Genomic and T cell repertoire biomarkers associated with malignant mesothelioma survival

BACKGROUND

Malignant mesothelioma (MM) is an exceedingly rare tumor with poor prognosis due to the limited availability of effective treatment. Immunotherapy has emerged as a novel treatment approach for MM, but less than 40% of the patients benefit from it. Thus, it is necessary to identify accurate and effective biomarkers that can predict the overall survival (OS) and immunotherapy efficacy for MM.

METHODS

DNA sequencing was used to identify the genomic landscape based on the data from 86 Chinese patients. T cell receptor (TCR) sequencing was used to characterize MM TCR repertoires of 28 patients between October 2016 and April 2023.

RESULTS

Patients with TP53, NF2, or CDKN2A variants at the genomic level, as well as those exhibiting lower Shannon index (<6.637), lower evenness (<0.028), or higher clonality (≥0.194) according to baseline tumor tissue TCR indexes, demonstrated poorer OS. Furthermore, patients with TP53, CDKN2A, or CDKN2B variants and those with a lower evenness (<0.030) in baseline tumor tissue showed worse immunotherapy efficacy. The present study is the first to identify five special TCR Vβ-Jβ rearrangements associated with MM immunotherapy efficacy.

CONCLUSIONS

The present study reported the largest-scale genomic landscape and TCR repertoire of MM in Chinese patients and identified genomic and TCR biomarkers for the prognosis and immunotherapy efficacy in MM. The study results might provide new insights for prospective MM trials using specific genes, TCR indexes, and TCR clones as biomarkers and offer a reference for future antitumor drugs based on TCR-specific clones.

Tumor mutational burden adjusted by neutrophil-to-lymphocyte ratio serves as a potential biomarker for atezolizumab-treated patients with extensive stage small cell lung cancer

BACKGROUND

There is a desperate for the identification of more accurate and efficient biomarkers for ICI responses in patients with SCLC.

METHODS

The data of our study was obtained from IMpower133 study. A total of 202 patients with SCLC received the treatment of placebo plus carboplatin plus etoposide (EC) while a total of 201 patients with SCLC received the treatment of atezolizumab plus EC. Overall survival (OS) was compared using Kaplan Meier analyses. Univariate and multivariate Cox regression analysis were used to determine independent prognostic variables affecting OS in patients with SCLC.

RESULTS

We have demonstrated that a higher TMB adjusted by a lower neutrophil-to-lymphocyte ratio (NLR) is significantly correlated with improved OS, in patients with SCLC subject to either atezolizumab or placebo (P = 0.001 for atezolizumab and P = 0.034 for placebo). Moreover, Cox model showed that TMB < 10 mut/Mb adjusted by NLR ≥ median was an independent factor of OS for atezolizumab-treated SCLC patients (hazard ratio [HR], 2.82; 95% confidence interval; 1.52-5.24; P = 0.001). Both univariate and multivariate cox regression analysis showed that for patients with SCLC harboring low NLR and high TMB, survival is significantly longer in those treated with atezolizumab than those treated with placebo. Survival benefit is significantly higher in atezolizumab-treated patients with SCLC than those treated with placebo (P = 0.018 for TMB cutoff = 10 mut/Mb, P = 0.034 for TMB cutoff = 16 mut/Mb).

CONCLUSION

Our findings provide a promising insight into the utility of NLR-adjusted TMB in the prognosis and immune responses in patients with SCLC.

HIV infection and ART exposure affect tumor TCR repertoire of diffuse large B cell lymphoma

The most common subtype of lymphoma globally, diffuse large B cell lymphoma (DLBCL), is a leading cause of cancer death in people with HIV. The restructuring of the T cell compartment because of HIV infection and antiretroviral therapy (ART) may have implications for modern treatment selection, but current understanding of these dynamic interactions is limited. Here, we investigated the T cell response to DLBCL by sequencing the T cell receptor (TCR) repertoire in a cohort of HIV-negative (HIV-), HIV+/ART-experienced, and HIV+/ART-naive patients with DLBCL. HIV+/ART-naive tumor TCR repertoires were more clonal and more distinct from each other than HIV- and HIV+/ART-experienced ones. Further, increased overlap between tumor and blood TCR repertoires was associated with improved survival and HIV/ART status. Our study describes TCR repertoire characteristics for the first time to our knowledge in an African DLBCL cohort and demonstrates contributions of HIV infection and ART exposure to the DLBCL TCR repertoire.

Exploring the Molecular Tumor Microenvironment and Translational Biomarkers in Brain Metastases of Non-Small-Cell Lung Cancer

Brain metastases represent a significant clinical challenge in the treatment of non-small-cell lung cancer (NSCLC), often leading to a severe decline in patient prognosis and survival. Recent advances in imaging and systemic treatments have increased the detection rates of brain metastases, yet clinical outcomes remain dismal due to the complexity of the metastatic tumor microenvironment (TME) and the lack of specific biomarkers for early detection and targeted therapy. The intricate interplay between NSCLC tumor cells and the surrounding TME in brain metastases is pivotal, influencing tumor progression, immune evasion, and response to therapy. This underscores the necessity for a deeper understanding of the molecular underpinnings of brain metastases, tumor microenvironment, and the identification of actionable biomarkers that can inform multimodal treatment approaches. The goal of this review is to synthesize current insights into the TME and elucidate molecular mechanisms in NSCLC brain metastases. Furthermore, we will explore the promising horizon of emerging biomarkers, both tissue- and liquid-based, that hold the potential to radically transform the treatment strategies and the enhancement of patient outcomes.

Ovarian cancer is detectable from peripheral blood using machine learning over T-cell receptor repertoires

The extraordinary diversity of T cells and B cells is critical for body maintenance. This diversity has an important role in protecting against tumor formation. In humans, the T-cell receptor (TCR) repertoire is generated through a striking stochastic process called V(D)J recombination, in which different gene segments are assembled and modified, leading to extensive variety. In ovarian cancer (OC), an unfortunate 80% of cases are detected late, leading to poor survival outcomes. However, when detected early, approximately 94% of patients live longer than 5 years after diagnosis. Thus, early detection is critical for patient survival. To determine whether the TCR repertoire obtained from peripheral blood is associated with tumor status, we collected blood samples from 85 women with or without OC and obtained TCR information. We then used machine learning to learn the characteristics of samples and to finally predict, over a set of unseen samples, whether the person is with or without OC. We successfully stratified the two groups, thereby associating the peripheral blood TCR repertoire with the formation of OC tumors. A careful study of the origin of the set of T cells most informative for the signature indicated the involvement of a specific invariant natural killer T (iNKT) clone and a specific mucosal-associated invariant T (MAIT) clone. Our findings here support the proposition that tumor-relevant signal is maintained by the immune system and is coded in the T-cell repertoire available in peripheral blood. It is also possible that the immune system detects tumors early enough for repertoire technologies to inform us near the beginning of tumor formation. Although such detection is made by the immune system, we might be able to identify it, using repertoire data from peripheral blood, to offer a pragmatic way to search for early signs of cancer with minimal patient burden, possibly with enhanced sensitivity.

Predicting patient outcomes after treatment with immune checkpoint blockade: A review of biomarkers derived from diverse data modalities

Immune checkpoint blockade (ICB) therapy targeting cytotoxic T-lymphocyte-associated protein 4, programmed death 1, and programmed death ligand 1 has shown durable remission and clinical success across different cancer types. However, patient outcomes vary among disease indications. Studies have identified prognostic biomarkers associated with immunotherapy response and patient outcomes derived from diverse data types, including next-generation bulk and single-cell DNA, RNA, T cell and B cell receptor sequencing data, liquid biopsies, and clinical imaging. Owing to inter- and intra-tumor heterogeneity and the immune system's complexity, these biomarkers have diverse efficacy in clinical trials of ICB. Here, we review the genetic and genomic signatures and image features of ICB studies for pan-cancer applications and specific indications. We discuss the advantages and disadvantages of computational approaches for predicting immunotherapy effectiveness and patient outcomes. We also elucidate the challenges of immunotherapy prognostication and the discovery of novel immunotherapy targets.

Systems immunology spanning tumors, lymph nodes, and periphery

The immune system defines a complex network of tissues and cell types that orchestrate responses across the body in a dynamic manner. The local and systemic interactions between immune and cancer cells contribute to disease progression. Lymphocytes are activated in lymph nodes, traffic through the periphery, and impact cancer progression through their interactions with tumor cells. As a result, therapeutic response and resistance are mediated across tissues, and a comprehensive understanding of lymphocyte dynamics requires a systems-level approach. In this review, we highlight experimental and computational methods that can leverage the study of leukocyte trafficking through an immunomics lens and reveal how adaptive immunity shapes cancer.

Circulating pre-treatment T-cell receptor repertoire as a predictive biomarker in advanced or metastatic non-small-cell lung cancer patients treated with pembrolizumab alone or in combination with chemotherapy

BACKGROUND

The circulating T-cell receptor (TCR) repertoire is a dynamic representation of overall immune responses in an individual.

MATERIALS AND METHODS

We prospectively collected baseline blood from patients treated with first-line pembrolizumab monotherapy or in combination with chemotherapy. TCR repertoire metrics were correlated with clinical benefit rate (CBR), progression-free survival (PFS), overall survival (OS) and immune-related adverse events (irAEs). We built a logistic regression classifier by fitting all four TCR-β repertoire metrics to the immune checkpoint inhibitor (ICI) CBR data. In the subsequent receiver operating characteristic (ROC) analysis of the resulting logistic regression model probabilities, the best cut-off value was selected to maximise sensitivity to predict CBR to ICI.

RESULTS

We observed an association between reduced number of unique clones and CBR among patients treated with pembrolizumab monotherapy (cohort 1) [risk ratio = 2.86, 95% confidence interval (CI) 1.04-8.73, P = 0.039]. For patients treated with pembrolizumab plus chemotherapy (cohort 2), increased number of unique clones [hazard ratio (HR) = 2.96, 95% CI 1.28-6.88, P = 0.012] and Shannon diversity (HR = 2.73, 95% CI 1.08-6.87, P = 0.033), and reduced evenness (HR = 0.43, 95% CI 0.21-0.90, P = 0.025) and convergence (HR = 0.41, 95% CI 0.19-0.90, P = 0.027) were associated with improved PFS, while only an increased number of unique clones (HR = 4.62, 95% CI 1.52-14.02, P = 0.007) were associated with improved OS. Logistic regression models combining the TCR repertoire metrics improved the prediction of CBR (cohorts 1 and 2) and were strongly associated with PFS (cohort 1, HR = 0.38, 95% CI 0.19-0.78, P = 0.009) and OS (cohort 2, HR = 0.20, 95% CI 0.05-0.76, P < 0.0001). Reduced TCR conversion was associated with increased frequency of irAEs needing systemic steroid treatment.

CONCLUSION

Combined pre-treatment circulating TCR metrics might serve as a predictive biomarker for clinical outcomes among patients with advanced non-small-cell lung cancer treated with pembrolizumab alone or in combination with chemotherapy.

The association between aspirin use and immune-related adverse events in specific cancer patients receiving ICIs therapy: analysis of the FAERS database

Background: The promise of immune checkpoint inhibitors (ICIs) therapy in cancer treatment is tempered by the occurrence of immune-related adverse events (irAEs). Many patients undergoing ICIs also take aspirin, but the association between aspirin and irAEs is not well understood. Methods: This study analyzed adverse reaction data associated with the use of ICIs in the US Food and Drug Administration (FDA) Adverse Event Reporting System FDA Adverse Event Reporting System database, from the approval date of each drug until 1 October 2022. Multivariate logistic regression was employed to assess the association of aspirin use with irAEs in patients receiving ICIs. Results: The results indicated that aspirin use was associated with an increased risk of irAEs in a pan-cancer analysis, with a more pronounced association in specific cancer types such as lung cancer, mesothelioma, and pancreatic cancer. However, in lymphoma, aspirin use was associated with a reduced risk of irAEs. Furthermore, aspirin use was associated with an increased risk of certain irAEs, such as anemia, colitis, myocarditis, myositis, pancreatitis, pericarditis, and pneumonia, while it was associated with a reduced risk of rash, Stevens-Johnson syndrome, and thyroiditis. Conclusion: This study has unveiled an association between aspirin use and irAEs in cancer patients receiving ICIs therapy, emphasizing the need for individualized consideration of patients' medication history when devising cancer treatment plans to enhance efficacy and reduce risks.

The components of tumor microenvironment as biomarker for immunotherapy in metastatic renal cell carcinoma

Substantial improvement in prognosis among metastatic renal cell carcinoma (mRCC) patients has been achieved, owing to the rapid development and utilization of immunotherapy. In particular, immune checkpoint inhibitors (ICIs) have been considered the backbone of systemic therapy for patients with mRCC alongside multi-targeted tyrosine kinase inhibitors (TKIs) in the latest clinical practice guidelines. However, controversies and challenges in optimal individualized treatment regarding immunotherapy remains still About 2/3 of the patients presented non-response or acquired resistance to ICIs. Besides, immune-related toxicities, namely immune-related adverse events, are still elusive and life-threatening. Thus, reliable biomarkers to predict immunotherapeutic outcomes for mRCC patients are needed urgently. Tumor microenvironment (TME), consisting of immune cells, vasculature, signaling molecules, and extracellular matrix and regulates tumor immune surveillance and immunological evasion through complex interplay, plays a critical role in tumor immune escape and consequently manipulates the efficacy of immunotherapy. Various studied have identified the different TME components are significantly associated with the outcome of mRCC patients receiving immunotherapy, making them potential valuable biomarkers in therapeutic guidance. The present review aims to summarize the latest evidence on the associations between the components of TME including immune cells, cytokines and extracellular matrix, and the therapeutic responses among mRCC patients with ICI-based treatment. We further discuss the feasibility and limitation of these components as biomarkers.

Thymic expression of immune checkpoint molecules and their implication for response to immunotherapies

The thymus is responsible for generating a diverse T cell repertoire that is tolerant to self, but capable of responding to various immunologic insults, including cancer. Checkpoint blockade has changed the face of cancer treatment by targeting inhibitory molecules, which are known to regulate peripheral T cell responses. However, these inhibitory molecules and their ligands are expressed during T cell development in the thymus. In this review, we describe the underappreciated role of checkpoint molecule expression during the formation of the T cell repertoire and detail the importance of inhibitory molecules in regulating T cell lineage commitment. Understanding how these molecules function in the thymus may inform therapeutic strategies for better patient outcomes.