A T cell repertoire timestamp is at the core of responsiveness to CTLA-4 blockade

Immune Checkpoint Inhibition Perturbs Neuro-immune Homeostasis and Impairs Cognitive Function

Background

Blockade of Cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) and Programmed Cell Death Protein 1 (PD-1) significantly improves progression-free survival of individuals with cancers, including melanoma. In addition to unleashing antitumor immunity, immune checkpoint inhibition (ICI) therapies disrupt immune regulatory networks critical for maintaining homeostasis in various tissues, including the central nervous system (CNS). Despite growing reports of cancer- and ICI-related cognitive impairments among survivors, our understanding of the pathophysiology of ICI-related neurodegenerative effects is limited.

Methods

In this study, using a murine model of melanoma, cognitive function tests, and neuroimmunological assays, we investigate the cellular mechanisms and impact of combinatorial blockade of CTLA-4 and PD-1 on brain function. Syngeneic melanoma was induced in a C57Bl6 mouse model using D4M-3A.UV2 melanoma cells. After confirmation of tumor growth, cancer-bearing and non-cancer mice received combinatorial treatment of anti-CTLA-4 (two doses per week) and anti-PD-1 (three doses per week) for three weeks. One month after completing ICI treatment, mice were administered learning, memory, and memory consolidation cognitive function tasks. Neuroinflammation, synaptic, and myelin integrity analyses and immune cell status in the brain were conducted to analyze neuroimmunological changes post-ICI treatment.

Results

While tumor-related alterations in brain function were evident, combination ICI specifically disrupted synaptic integrity and reduced myelin levels independent of neurogenesis and neuronal plasticity in both cancer-bearing and non-cancer mice brains. Combination ICI selectively impaired hippocampal-dependent cognitive function. This is associated with two-fold increase in T cell numbers within the brain along with immune activation of myeloid cells, especially microglia. Furthermore, an experimental autoimmune encephalomyelitis model revealed that combination ICI predisposes the CNS to exacerbated autoimmunity, highlighting neuroinflammation-related, and tumor-independent, neurodegenerative sequelae of combination ICI.

Conclusion

Our results demonstrate that combinatorial blockade of CTLA-4 and PD-1 destabilizes neuroimmune-regulatory networks and activates microglia, contributing to long-term neurodegeneration and cognitive impairments. Therefore, selectively limiting microglial activation could be a potential avenue to preserve CNS functions while maintaining the therapeutic benefits of rapidly evolving ICIs and their combinations.

The Current Status of T Cell Receptor (TCR) Repertoire Analysis in Colorectal Cancer

The rapid increase in colorectal cancer (CRC) cases recently has highlighted the need to use predictive biomarkers to guide therapeutic approaches. Current studies have focused on the tumor-infiltrating lymphocytes present in the tumor microenvironment (TME), in which cytotoxic T cell activation and the amount are associated with CRC patient prognosis. The T cell receptor (TCR) is essential for antigen recognition and T cell identification, playing a central role in cancer immunotherapy. The T cell status reflects TCR diversity or clonality, known as the TCR repertoire. Accordingly, analyzing the TCR repertoire dynamics may help predict the immunological circumstances of the TME in a timely way. In this review, we summarize the TCR repertoire-related knowledge, including its potential use as predictive biomarkers in CRC. The intratumoral TCR repertoire is restricted in CRC patients compared with healthy individuals, as well as in peripheral blood. Patients with deficient mismatch repair display more restriction than those with proficient mismatch repair. Importantly, a higher TCR diversity before treatment and a decrease following treatment may indicate a good response and a better clinical outcome in CRC patients. The future use of TCR repertoire sequencing technology combined with artificial intelligence-based analysis is a potential strategy for CRC therapeutic decision making.

Local Enrichment with Convergence of Enriched T-Cell Clones Are Hallmarks of Effective Peptide Vaccination against B16 Melanoma

BACKGROUND

Some peptide anticancer vaccines elicit a strong T-cell memory response but fail to suppress tumor growth. To gain insight into tumor resistance, we compared two peptide vaccines, p20 and p30, against B16 melanoma, with both exhibiting good in vitro T-cell responses but different tumor suppression abilities.

METHODS

We compared activation markers and repertoires of T-lymphocytes from tumor-draining (dLN) and non-draining (ndLN) lymph nodes for the two peptide vaccines.

RESULTS

We showed that the p30 vaccine had better tumor control as opposed to p20. p20 vaccine induced better in vitro T-cell responsiveness but failed to suppress tumor growth. Efficient antitumor vaccination is associated with a higher clonality of cytotoxic T-cells (CTLs) in dLNs compared with ndLNs and the convergence of most of the enriched clones. With the inefficient p20 vaccine, the most expanded and converged were clones of the bystander T-cells without an LN preference.

CONCLUSIONS

Here, we show that the clonality and convergence of the T-cell response are the hallmarks of efficient antitumor vaccination. The high individual and methodological dependencies of these parameters can be avoided by comparing dLNs and ndLNs.

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.

The temporal behavior of the murine T cell receptor repertoire following Immunotherapy

Immunotherapy is now an essential tool for cancer treatment, and the unique features of an individual's T cell receptor repertoire are known to play a key role in its effectiveness. The repertoire, famously vast due to a cascade of cellular mechanisms, can be quantified using repertoire sequencing. In this study, we sampled the repertoire over several time points following treatment with anti-CTLA-4, in a syngeniec mouse model for colorectal cancer, generating a longitudinal dataset of T cell clones and their abundance. The dynamics of the repertoire can be observed in response to treatment over a period of four weeks, as clonal expansion of specific clones ascends and descends. The data made available here can be used to determine treatment and predict its effect, while also providing a unique look at the behavior of the immune system over time.

GENTLE: a novel bioinformatics tool for generating features and building classifiers from T cell repertoire cancer data

BACKGROUND

In the global effort to discover biomarkers for cancer prognosis, prediction tools have become essential resources. TCR (T cell receptor) repertoires contain important features that differentiate healthy controls from cancer patients or differentiate outcomes for patients being treated with different drugs. Considering, tools that can easily and quickly generate and identify important features out of TCR repertoire data and build accurate classifiers to predict future outcomes are essential.

RESULTS

This paper introduces GENTLE (GENerator of T cell receptor repertoire features for machine LEarning): an open-source, user-friendly web-application tool that allows TCR repertoire researchers to discover important features; to create classifier models and evaluate them with metrics; and to quickly generate visualizations for data interpretations. We performed a case study with repertoires of TRegs (regulatory T cells) and TConvs (conventional T cells) from healthy controls versus patients with breast cancer. We showed that diversity features were able to distinguish between the groups. Moreover, the classifiers built with these features could correctly classify samples ('Healthy' or 'Breast Cancer')from the TRegs repertoire when trained with the TConvs repertoire, and from the TConvs repertoire when trained with the TRegs repertoire.

CONCLUSION

The paper walks through installing and using GENTLE and presents a case study and results to demonstrate the application's utility. GENTLE is geared towards any researcher working with TCR repertoire data and aims to discover predictive features from these data and build accurate classifiers. GENTLE is available on https://github.com/dhiego22/gentle and https://share.streamlit.io/dhiego22/gentle/main/gentle.py .

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

Profiling the T-Cell Receptor (TCR) repertoire is establishing as a potent approach to investigate autologous and treatment-induced antitumor immune response. Technical and computational breakthroughs, including high throughput next-generation sequencing (NGS) approaches and spatial transcriptomics, are providing unprecedented insight into the mechanisms underlying antitumor immunity. A precise spatiotemporal variation of T-cell repertoire, which dynamically mirrors the functional state of the evolving host-cancer interaction, allows the tracking of the T-cell populations at play, and may identify the key cells responsible for tumor eradication, the evaluation of minimal residual disease and the identification of biomarkers of response to immunotherapy. In this review we will discuss the relationship between global metrics characterizing the TCR repertoire such as T-cell clonality and diversity and the resultant functional responses. In particular, we will explore how specific TCR repertoires in cancer patients can be predictive of prognosis or response to therapy and in particular how a given TCR re-arrangement, following immunotherapy, can predict a specific clinical outcome. Finally, we will examine current improvements in terms of T-cell sequencing, discussing advantages and challenges of current methodologies.

Proportional Tumor Infiltration of T Cells via Circulation Duplicates the T Cell Receptor Repertoire in a Bilateral Tumor Mouse Model

Temporal analysis of the T cell receptor (TCR) repertoire has been used to monitor treatment-induced changes in antigen-specific T cells in patients with cancer. However, the lack of experimental models that allow a temporal analysis of the TCR repertoire in the same individual in a homogeneous population limits the understanding of the causal relationship between changes in TCR repertoire and antitumor responses. A bilateral tumor model, where tumor cells were inoculated bilaterally into the backs of mice, could be used for temporal analysis of the TCR repertoire. This study examined the prerequisite for this strategy: the TCR repertoire is conserved between bilateral tumors that grow symmetrically. Bilateral tumors and draining lymph nodes (dLNs) were collected 13 days after tumor inoculation to analyze the TCR repertoire of CD4⁺ and CD8⁺ T cells. The tumor-infiltrating T-cell clones were highly similar between the bilateral tumors and expanded to a similar extent. In addition, the differences of TCR repertoire between the bilateral tumors were equivalent to Intra-tumoral heterogeneity on one side. On the other hand, the similarity of the TCR repertoire in the bilateral dLNs was markedly lower than that in the tumor, suggesting that tumor-reactive T cell clones induced independently in each dLN are mixed during recirculation and then proportionally infiltrated the bilateral tumors. These findings provide the basis for future analysis of temporal and treatment-induced changes in tumor-reactive T cell clones using this bilateral tumor model.