TCR repertoire profiling of tumors, adjacent normal tissues, and peripheral blood predicts survival in nasopharyngeal carcinoma

Multiple instance learning method based on convolutional neural network and self-attention for early cancer detection

Early cancer detection using T-cell receptor sequencing (TCR-seq) and multiple instances learning methods has shown significant effectiveness. We introduce a multiple instance learning method based on convolutional neural networks and self-attention (MICA). First, MICA preprocesses TCR-seq using word vectors and then extracts features using convolutional neural networks. Second, MICA uses an enhanced self-attention mechanism to extract relational features of instances. Finally, MICA can extract the crucial TCR-seq. After cross-validation, MICA achieves an area under the curve (AUC) of 0.911 and 0.946 on the lung and thyroid cancer datasets, which are 7.1% and 2.1% higher than other methods, respectively.

The intratumoral landscape of T cell receptor repertoire in esophageal squamous cell carcinoma

BACKGROUND

Esophageal squamous cell carcinoma (ESCC) is a malignant neoplasm with detrimental implications for human health. The landscape of ESCC therapy has been revolutionized by the introduction of immunotherapy, specifically involving immune checkpoint inhibitors (ICIs). A number of studies have documented the prognostic significance of T-cell receptor (TCR) repertoire and its association with many tumors. Nevertheless, the TCR repertoire landscape and its significance in ESCC still need to be explored.

METHODS

In this study, we conducted RNA-Seq analysis to investigate the characteristics of the TCR repertoire in 90 patients. Moreover, high-throughput TCR sequencing was performed on tumor tissues from 41 patients who received immunotherapy. Additionally, a comprehensive analysis of the T-cell receptor repertoire landscape within ESCC tumors was carried out through immunohistochemical staining on all patient samples.

RESULTS

We noticed a diminished diversity of TCR repertoire within the tumor compared to its adjacent normal tissue. In terms of immunotherapy responses, non-responsive patients exhibited higher TCR repertoire diversity indices and an increased frequency of common V and J genes. Additionally, elevated TCR repertoire diversity correlated with improved overall survival rates. Lastly, immunohistochemical staining results indicated a correlation between TCR repertoire diversity and the tumor immune microenvironment (TIME).

CONCLUSIONS

Our study primarily describes the landscape of TCR repertoires in ESCC through three aspects: differences in tumor tissues, immune response to immunotherapy, and survival prognosis of patients. These results emphasize the importance of TCR repertoire characteristics as unique and relevant biomarkers for ESCC immunotherapy.

Tumor-reactive T cell clonotype dynamics underlying clinical response to TIL therapy in melanoma

Adoptive cell therapy (ACT) using in vitro expanded tumor-infiltrating lymphocytes (TILs) has inconsistent clinical responses. To better understand determinants of therapeutic success, we tracked TIL clonotypes from baseline tumors to ACT products and post-ACT blood and tumor samples in melanoma patients using single-cell RNA and T cell receptor (TCR) sequencing. Patients with clinical responses had baseline tumors enriched in tumor-reactive TILs, and these were more effectively mobilized upon in vitro expansion, yielding products enriched in tumor-specific CD8+ cells that preferentially infiltrated tumors post-ACT. Conversely, lack of clinical responses was associated with tumors devoid of tumor-reactive resident clonotypes and with cell products mostly composed of blood-borne clonotypes that persisted in blood but not in tumors post-ACT. Upon expansion, tumor-specific TILs lost tumor-associated transcriptional signatures, including exhaustion, and responders exhibited an intermediate exhausted effector state after TIL engraftment in the tumor, suggesting functional reinvigoration. Our findings provide insight into the nature and dynamics of tumor-specific clonotypes associated with clinical response to TIL-ACT, with implications for treatment optimization.

Exploring the potential of the TCR repertoire as a tumor biomarker (Review)

T cells play an important role in adaptive immunity. Mature T cells specifically recognize antigens on major histocompatibility complex molecules through T-cell receptors (TCRs). As the TCR repertoire is highly diverse, its analysis is vital in the assessment of T cells. Advances in sequencing technology have provided convenient methods for further investigation of the TCR repertoire. In the present review, the TCR structure and the mechanisms by which TCRs function in tumor recognition are described. In addition, the potential value of the TCR repertoire in tumor diagnosis is reviewed. Furthermore, the role of the TCR repertoire in tumor immunotherapy is introduced, and the relationships between the TCR repertoire and the effects of different tumor immunotherapies are discussed. Based on the reviewed literature, it may be concluded that the TCR repertoire has the potential to serve as a biomarker for tumor prognosis. However, a wider range of cancer types and more diverse subjects require evaluation in future research to establish the TCR repertoire as a biomarker of tumor immunity.

Global analysis of T-cell groups reveals immunological features and common antigen targets of digestive tract tumors

BACKGROUND

T cells are key players in the tumor immune microenvironment (TIME), as they can recognize and eliminate cancer cells that express neoantigens derived from somatic mutations. However, the diversity and specificity of T-cell receptors (TCRs) that recognize neoantigens are largely unknown, due to the high variability of TCR sequences among individuals.

METHODS

To address this challenge, we applied GLIPH2, a novel algorithm that groups TCRs based on their predicted antigen specificity and HLA restriction, to cluster the TCR repertoire of 1,702 patients with digestive tract cancer. The patients were divided into five groups based on whether they carried tumor-infiltrating or clonal-expanded TCRs and calculated their TCR diversity. The prognosis, tumor subtype, gene mutation, gene expression, and immune microenvironment of these groups were compared. Viral specificity inference and immunotherapy relevance analysis performed for the TCR groups.

RESULTS

This approach reduced the complexity of TCR sequences to 249 clonally expanded and 150 tumor-infiltrating TCR groups, which revealed distinct patterns of TRBV usage, HLA association, and TCR diversity. In gastric adenocarcinoma (STAD), patients with tumor-infiltrating TCRs (Patients-TI) had significantly worse prognosis than other patients (Patients-nonTI). Patients-TI had richer CD8+ T cells in the immune microenvironment, and their gene expression features were positively correlated with immunotherapy response. We also found that tumor-infiltrating TCR groups were associated with four distinct tumor subtypes, 26 common gene mutations, and 39 gene expression signatures. We discovered that tumor-infiltrating TCRs had cross-reactivity with viral antigens, indicating a possible link between viral infections and tumor immunity.

CONCLUSION

By applying GLIPH2 to TCR sequences from digestive tract tumors, we uncovered novel insights into the tumor immune landscape and identified potential candidates for shared TCRs and neoantigens.

Translational bioinformatics approach to combat cardiovascular disease and cancers

Bioinformatics is an interconnected subject of science dealing with diverse fields including biology, chemistry, physics, statistics, mathematics, and computer science as the key fields to answer complicated physiological problems. Key intention of bioinformatics is to store, analyze, organize, and retrieve essential information about genome, proteome, transcriptome, metabolome, as well as organisms to investigate the biological system along with its dynamics, if any. The outcome of bioinformatics depends on the type, quantity, and quality of the raw data provided and the algorithm employed to analyze the same. Despite several approved medicines available, cardiovascular disorders (CVDs) and cancers comprises of the two leading causes of human deaths. Understanding the unknown facts of both these non-communicable disorders is inevitable to discover new pathways, find new drug targets, and eventually newer drugs to combat them successfully. Since, all these goals involve complex investigation and handling of various types of macro- and small- molecules of the human body, bioinformatics plays a key role in such processes. Results from such investigation has direct human application and thus we call this filed as translational bioinformatics. Current book chapter thus deals with diverse scope and applications of this translational bioinformatics to find cure, diagnosis, and understanding the mechanisms of CVDs and cancers. Developing complex yet small or long algorithms to address such problems is very common in translational bioinformatics. Structure-based drug discovery or AI-guided invention of novel antibodies that too with super-high accuracy, speed, and involvement of considerably low amount of investment are some of the astonishing features of the translational bioinformatics and its applications in the fields of CVDs and cancers.

Characterization of T cell receptor repertoire in penile cancer

Tumor-infiltrating lymphocytes (TILs) play a key role in regulating the host immune response and shaping tumor microenvironment. It has been previously shown that T cell infiltration in penile tumors was associated with clinical outcomes. However, few studies have reported the T cell receptor (TCR) repertoire in patients with penile cancer. In the present study, we evaluated the TCR repertoires in tumor and adjacent normal tissues from 22 patients with penile squamous cell carcinoma (PSCC). Analysis of the T cell receptor beta-variable (TRBV) and joining (TRBJ) genes usage and analysis of complementarity determining region 3 (CDR3) length distribution did not show significant differences between tumor and matched normal tissues. Moreover, analysis of the median Jaccard index indicated a limited overlap of TCR repertoire between these groups. Compared with normal tissues, a significantly lower diversity and higher clonality of TCR repertoire was observed in tumor samples, which was associated with clinical characteristics. Further analysis of transcriptional profiles demonstrated that tumor samples with high clonality showed increased expression of genes associated with CD8 + T cells. In addition, we analyzed the TCR repertoire of CD4 + T cells and CD8 + T cells isolated from tumor tissues. We identified that expanded clonotypes were predominantly in the CD8 + T cell compartment, which presented with an exhausted phenotype. Overall, we comprehensively compared TCR repertoire between penile tumor and normal tissues and demonstrated the presence of distinct T cell immune microenvironments in patients with PSCC.

Peripheral blood TCR clonotype diversity as an age-associated marker of breast cancer progression

Immune escape is a prerequisite for tumor growth. We previously described a decline in intratumor activated cytotoxic T cells and T cell receptor (TCR) clonotype diversity in invasive breast carcinomas compared to ductal carcinoma in situ (DCIS), implying a central role of decreasing T cell responses in tumor progression. To determine potential associations between peripheral immunity and breast tumor progression, here, we assessed the peripheral blood TCR clonotype of 485 breast cancer patients diagnosed with either DCIS or de novo stage IV disease at younger (<45) or older (≥45) age. TCR clonotype diversity was significantly lower in older compared to younger breast cancer patients regardless of tumor stage at diagnosis. In the younger age group, TCR-α clonotype diversity was lower in patients diagnosed with de novo stage IV breast cancer compared to those diagnosed with DCIS. In the older age group, DCIS patients with higher TCR-α clonotype diversity were more likely to have a recurrence compared to those with lower diversity. Whole blood transcriptome profiles were distinct depending on the TCR-α Chao1 diversity score. There were more CD8+ T cells and a more active immune environment in DCIS tumors of young patients with higher peripheral blood TCR-α Chao1 diversity than in those with lower diversity. These results provide insights into the role that host immunity plays in breast cancer development across different age groups.

Transcriptomics of Epstein-Barr virus aids to the classification of T-cell evasion in nasopharyngeal carcinoma

Epstein-Barr virus (EBV) contributes to oncogenesis and immune evasion in nasopharyngeal carcinoma (NPC). At present, an aggregated, higher-level view on the impact of EBV genes toward the immune microenvironment of NPC is lacking. To this end, we have interrogated tumor-derived RNA sequences of 106 treatment-naive NPC patients for 98 EBV transcripts, and captured the presence of 10 different immune cell populations as well as 23 different modes of T-cell evasion. We discovered 3 clusters of EBV genes that each associate with distinct immunophenotypes of NPC. Cluster 1 associated with gene sets related to immune cell recruitment, such as those encoding for chemoattractants and their receptors. Cluster 2 associated with antigen processing and presentation, such as interferon-related genes, whereas cluster 3 associated with presence of M1-like macrophages, absence of CD4+ T cells, and oncogenic pathways, such as the nuclear factor kappa light-chain enhancer of activated B-cell pathway. We discuss these 3 EBV clusters regarding their potential for stratification for T-cell immunity in NPC together with the next steps needed to validate such therapeutic value.

Identification and tracking of HTLV-1-infected T cell clones in virus-associated neurologic disease

Human T lymphotropic virus type 1-assoicated (HTLV-1-associated) myelopathy/tropical spastic paraparesis (HAM/TSP) is a neuroinflammatory disease caused by the persistent proliferation of HTLV-1-infected T cells. Here, we performed a T cell receptor (TCR) repertoire analysis focused on HTLV-1-infected cells to identify and track the infected T cell clones that are preserved in patients with HAM/TSP and migrate to the CNS. TCRβ repertoire analysis revealed higher clonal expansion in HTLV-1-infected cells compared with noninfected cells from patients with HAM/TSP and asymptomatic carriers (ACs). TCR clonality in HTLV-1-infected cells was similar in patients with HAM/TSP and ACs. Longitudinal analysis showed that the TCR repertoire signature in HTLV-1-infected cells remained stable, and highly expanded infected clones were preserved within each patient with HAM/TSP over years. Expanded HTLV-1-infected clones revealed different distributions between cerebrospinal fluid (CSF) and peripheral blood and were enriched in the CSF of patients with HAM/TSP. Cluster analysis showed similarity in TCRβ sequences in HTLV-1-infected cells, suggesting that they proliferate after common antigen stimulation. Our results indicate that exploring TCR repertoires of HTLV-1-infected cells can elucidate individual clonal dynamics and identify potential pathogenic clones expanded in the CNS.

Multiple White Plaques in the Esophagus: A Possible Case of Esophageal Mucosal Alteration Associated With Immune-Related Adverse Events of Immune Checkpoint Inhibitors

We report two cases of multiple white plaques in the esophagus that emerged after the administration of immune checkpoint inhibitors. Both patients developed enterocolitis as immune-related adverse events associated with immune checkpoint inhibitors. Esophagogastroduodenoscopy revealed duodenal involvement and multiple white plaques in the esophagus. A biopsy of the esophagus showed predominant CD3⁺ lymphocyte infiltration, suggesting that esophageal mucosal alterations were associated with immune-related adverse events. In addition, histopathology showed keratinized stratified squamous epithelium in the first case while increased inflammatory cell infiltration in the intraepithelial and subepithelial layers was observed in the second case. These data suggest a different pathogenesis of the multiple esophageal white plaques between the two cases. Although further investigation is needed to elucidate the significance of these observations, recognition of the esophageal plaques may be important for prompt diagnosis of immune-related adverse events when associated with immune checkpoint inhibitors.

Evaluation of the TCR Repertoire as a Predictive and Prognostic Biomarker in Cancer: Diversity or Clonality?

Simple Summary

The TCR is the T cell antigen receptor, and it is responsible of the T cell activation, through the HLA-antigen complex recognition. Studying the TCR repertoire in patients with cancer can help to better understand the anti-tumoural responses and it has been suggested to have predictive and or/prognostic values, both for the disease and in response to treatments. The aim of this review is to summarize TCR repertoire studies performed in patients with cancer found in the literature, thoroughly analyse the different factors that can be involved in shaping the TCR repertoire, and draw the current conclusions in this field, especially focusing on whether the TCR diversity—or its opposite, the clonality—can be used as predictors or prognostic biomarkers of the disease.

Abstract

T cells play a vital role in the anti-tumoural response, and the presence of tumour-infiltrating lymphocytes has shown to be directly correlated with a good prognosis in several cancer types. Nevertheless, some patients presenting tumour-infiltrating lymphocytes do not have favourable outcomes. The TCR determines the specificities of T cells, so the analysis of the TCR repertoire has been recently considered to be a potential biomarker for patients’ progression and response to therapies with immune checkpoint inhibitors. The TCR repertoire is one of the multiple elements comprising the immune system and is conditioned by several factors, including tissue type, tumour mutational burden, and patients’ immunogenetics. Its study is crucial to understanding the anti-tumoural response, how to beneficially modulate the immune response with current or new treatments, and how to better predict the prognosis. Here, we present a critical review including essential studies on TCR repertoire conducted in patients with cancer with the aim to draw the current conclusions and try to elucidate whether it is better to encounter higher clonality with few TCRs at higher frequencies, or higher diversity with many different TCRs at lower frequencies.

Characteristics and Clinical Significance of T-Cell Receptor Repertoire in Hepatocellular Carcinoma

Several studies have demonstrated that the T-cell receptor (TCR) repertoire is associated with prognosis and immune therapy response in several types of cancer. However, the comprehensive features of TCR repertoire in tumor-infiltrating and circulating T cells, as well as its clinical significance of diagnosis in hepatocellular carcinoma (HCC) patients, are still unknown. In this study, we perform paired tumor/peritumoral tissues and peripheral blood samples from 58 patients with HCC and sequenced them with high-throughput TCR to comprehensively analyze the characteristics of TCR and the clinical significance of peripheral TCR sequence. By exploring the abundance and diversity of TCR repertoires, we observe that there was a significantly higher TCR diversity in peripheral blood than in tumoral and peritumoral tissues, while tumoral and peritumoral tissues showed similar TCR diversity. A substantial difference in the usage frequencies of several Vβ, Jβ genes, and TCRβ VJ pairings was found among three types of tissues. Moreover, we reveal that HCC patients have a unique profile of TCR repertoire in peripheral blood in contrast to healthy individuals. We further establish an HCC diagnostic model based on TCRβ VJ pairing usage in peripheral blood, which yields a best-fit area under the curve (AUC) of 0.9746 ± 0.0481 (sensitivity = 0.9675 ± 0.0603, specificity = 0.9998 ± 0.0007, average of 100 repeats) in the test set. Our study describes the characteristics of tissue infiltration and circulating T-cell bank in patients with HCC and shows the potential of using circulating TCR sequence as a biomarker for the non-invasive diagnosis of patients with HCC.

Circulating T-Cell Repertoires Correlate With the Tumor Response in Patients With Breast Cancer Receiving Neoadjuvant Chemotherapy

PURPOSE

Neoadjuvant chemotherapy (NAC) has been widely used in patients with breast cancer to minish tumor burden and increase resection rate of cancer. T-cell repertoire has been believed to be able to monitor antitumor immune responses. This study aimed to explore the dynamic change of T-cell repertoire and its clinical value in evaluating the tumor response in patients with breast cancer receiving NAC.

MATERIALS AND METHODS

Ninety-four patients who underwent NAC before surgery were recruited, and peripheral blood samples were collected at multiple time points during NAC. High-throughput T-cell receptor (TCR)-β sequencing was used to characterize the T-cell repertoire of every sample and analyzed the changes in circulating T-cell repertoire during NAC.

RESULTS

We found that the diversity of TCR repertoires was associated with age and clinical stage of the patients with breast cancer. The distribution of Vβ and Jβ genes in TCR repertoires was skewed in patients with human epidermal growth factor receptor 2-positive (HER2+) breast cancer. Vβ20.1 and Vβ30 expression levels before NAC correlate with tumor response after all cycles of NAC in HER2- and HER2+ patients, respectively. Some CDR3 motifs that correlated with clinical response in either HER2+ or HER2- patients were identified. Besides, TCR repertoire evolved during NAC and the diversity of TCR repertoire decreased more after two cycles of NAC in patients with good tumor response after all cycles of NAC (P = .0061).

CONCLUSION

Our results demonstrated that TCR repertoire correlated with the characteristics of the tumor, such as the expression status of HER2. Moreover, some characteristics of TCR repertoires that correlated with clinical response were identified and they might provide useful information to tailor therapeutic regimens at the early cycle of NAC.

Intratumor heterogeneity: the hidden barrier to immunotherapy against MSI tumors from the perspective of IFN-γ signaling and tumor-infiltrating lymphocytes

In this era of precision medicine, with the help of biomarkers, immunotherapy has significantly improved prognosis of many patients with malignant tumor. Deficient mismatch repair (dMMR)/microsatellite instability (MSI) status is used as a biomarker in clinical practice to predict favorable response to immunotherapy and prognosis. MSI is an important characteristic which facilitates mutation and improves the likelihood of a favorable response to immunotherapy. However, many patients with dMMR/MSI still respond poorly to immunotherapies, which partly results from intratumor heterogeneity propelled by dMMR/MSI. In this review, we discuss how dMMR/MSI facilitates mutations in tumor cells and generates intratumor heterogeneity, especially through type II interferon (IFN-γ) signaling and tumor-infiltrating lymphocytes (TILs). We discuss the mechanism of immunotherapy from the perspective of dMMR/MSI, molecular pathways and TILs, and we discuss how intratumor heterogeneity hinders the therapeutic effect of immunotherapy. Finally, we summarize present techniques and strategies to look at the tumor as a whole to design personalized regimes and achieve favorable prognosis.

A comprehensive model based on temporal dynamics of peripheral T cell repertoire for predicting post-treatment distant metastasis of nasopharyngeal carcinoma

Many nasopharyngeal carcinoma (NPC) patients develop distant metastases after treatment, leading to poor outcomes. To date, there are no peripheral biomarkers suitable for all NPC patients to predict distant metastasis. Hence, we purposed to develop a noninvasive comprehensive model for predicting post-treatment distant metastasis of all NPC. Since T-cell receptor β chain (TCRB) repertoire has achieved prognostic prediction in many cancers, the clinical characteristics and parameters of TCRB repertoire of 71 cases of peripheral blood samples (pairwise pre-treatment and post-treatment samples from 40 NPC patients who without (nM, n = 21) or with (M, n = 19) post-treatment distant metastasis) were collected. The least absolute shrinkage and selection operator algorithm was used to construct a distant metastasis prediction model. In terms of TCRB repertoire parameters, the diversity of TCRB repertoire was significantly decreased in M group after treatment but not in nM group. Ascending TCRB diversity and higher similarity between pre- and post-treatment samples showed better distant metastasis-free survival (DMFS). The similarity still had robust DMFS prediction in patients with reduced TCRB diversity. More importantly, the 5-factor comprehensive model consisting of basic clinical characteristics and TCRB repertoire indices showed a higher prognostic accuracy than any one individual factor in DMFS predicting. In conclusion, treatment had different effects on the composition of TCRB repertoire in patients without and with post-treatment distant metastasis. The dynamics of TCRB diversity, the similarity of TCRB repertoires, and combinations of these factors with basic clinical characteristics could serve as noninvasive DMFS predictors for all NPC patients.

TCR repertoire characteristics predict clinical response to adoptive CTL therapy against nasopharyngeal carcinoma

The past decade has witnessed the gradual and steady progress of adoptive T cell therapy in treating various types of cancer. In combination with gemcitabine and carboplatin chemotherapy, we previously conducted a clinical trial, NCT00690872, to treat Epstein-Barr virus (EBV)-positive nasopharyngeal carcinoma (NPC) patients with autologous EBV-expanded cytotoxic T lymphocytes (CTLs). While achieving a 2-year overall survival rate of 62.9%, this trial failed to induce an anti-tumor response in a sizable fraction of patients. Thus, the identification of benchmarks capable of evaluating CTL products and predicting clinical immunotherapeutic efficacy remains an urgent need. We conducted T cell receptor (TCR) repertoire sequencing to assess EBV-expanded infusion-ready CTL products. To depict the overall repertoire landscape, we evaluated the individual repertoire diversity by Shannon entropy, and, compared the inter-patient CDR3 similarity to estimate T cells expanded by common antigens. With a recently developed bioinformatics algorithm, termed Motif Analysis, we made a machine-learning prediction of structural regions within the CDR3 of TCRβ that associate with CTL therapy prognosis. We found that long term survivors, defined as patients surviving longer than two years, had a higher CTL repertoire diversity with reduced inter-patient similarity. Furthermore, TCR Motif Analysis identified 11 structural motifs distinguishing long term survivors from short term survivors. Specifically, two motifs with a high area under the curve (AUC) values were identified as potential predictive benchmarks for efficacious CTL production. Together, these results reveal that the presence of diverse TCR sequences containing a common core motif set is associated with a favorable response to CTL immunotherapy against EBV-positive NPC.

Exploiting Single-Cell Tools in Gene and Cell Therapy

Single-cell molecular tools have been developed at an incredible pace over the last five years as sequencing costs continue to drop and numerous molecular assays have been coupled to sequencing readouts. This rapid period of technological development has facilitated the delineation of individual molecular characteristics including the genome, transcriptome, epigenome, and proteome of individual cells, leading to an unprecedented resolution of the molecular networks governing complex biological systems. The immense power of single-cell molecular screens has been particularly highlighted through work in systems where cellular heterogeneity is a key feature, such as stem cell biology, immunology, and tumor cell biology. Single-cell-omics technologies have already contributed to the identification of novel disease biomarkers, cellular subsets, therapeutic targets and diagnostics, many of which would have been undetectable by bulk sequencing approaches. More recently, efforts to integrate single-cell multi-omics with single cell functional output and/or physical location have been challenging but have led to substantial advances. Perhaps most excitingly, there are emerging opportunities to reach beyond the description of static cellular states with recent advances in modulation of cells through CRISPR technology, in particular with the development of base editors which greatly raises the prospect of cell and gene therapies. In this review, we provide a brief overview of emerging single-cell technologies and discuss current developments in integrating single-cell molecular screens and performing single-cell multi-omics for clinical applications. We also discuss how single-cell molecular assays can be usefully combined with functional data to unpick the mechanism of cellular decision-making. Finally, we reflect upon the introduction of spatial transcriptomics and proteomics, its complementary role with single-cell RNA sequencing (scRNA-seq) and potential application in cellular and gene therapy.

The Diagnostic and Prognostic Potential of the B-Cell Repertoire in Membranous Nephropathy

Membranous nephropathy (MN), an autoimmune glomerular disease, is one of the most common causes of nephrotic syndrome in adults. In current clinical practice, the diagnosis is dependent on renal tissue biopsy. A new method for diagnosis and prognosis surveillance is urgently needed for patients. In the present study, we recruited 66 MN patients before any treatment and 11 healthy control (HC) and analyzed multiple aspects of the immunoglobulin heavy chain (IGH) repertoire of these samples using high-throughput sequencing. We found that the abnormalities of CDR-H3 length, hydrophobicity, somatic hypermutation (SHM), and germ line index were progressively more prominent in patients with MN, and the frequency of IGHV3-66 in post-therapy patients was significantly lower than that in pre-therapy patients. Moreover, we found that the IGHV3-38 gene was significantly related to PLA2R, which is the most commonly used biomarker. The most important discovery was that several IGHV, IGHD transcripts, CDR-H3 length, and SHM rate in pre-therapy patients had the potential to predict the therapeutic effect. Our study further demonstrated that the IGH repertoire could be a potential biomarker for prognosis prediction of MN. The landscape of circulating B-lymphocyte repertoires sheds new light on the detection and surveillance of MN.

A comparative study of multiple instance learning methods for cancer detection using T-cell receptor sequences

As a branch of machine learning, multiple instance learning (MIL) learns from a collection of labeled bags, each containing a set of instances. The learning process is weakly supervised due to ambiguous instance labels. Since its emergence, MIL has been applied to solve various problems including content-based image retrieval, object tracking/detection, and computer-aided diagnosis. In biomedical research, the use of MIL has been focused on medical image analysis and molecule activity prediction. We review and apply 16 methods to investigate the applicability of MIL to a novel biomedical application, cancer detection using T-cell receptor (TCR) sequences. This important application can be a viable approach for large-scale cancer screening, as TCRs can be easily profiled from a subject's peripheral blood. We consider two feasible data-generating mechanisms, and for the purpose of performance evaluation, we simulate data under each mechanism, where we vary potentially important factors to mimic realistic situations. We also apply the methods to sequencing data of ten cancer types from The Cancer Genome Atlas, as an early proof of concept for distinguishing tumor patients from healthy individuals via TCR sequencing of peripheral blood. We find that given an appropriate MIL method is used, satisfactory performance with Area Under the Receiver Operating Characteristic Curve above 80% can be achieved for five in the ten cancers. Based on our numerical results, we make suggestions about selection of a proper method and avoidance of any method with poor performance. We further point out directions of future research as well as identify a pressing need of new MIL methodologies for improved performance (for some cancer types) and more explainable outcomes.

Blood T cell diversity associated with the prognosis of advanced non-small cell lung carcinoma treated with first-line pemetrexed based chemotherapy

BACKGROUND

The tumor microenvironment is associated with prognosis in advanced non-small cell lung carcinoma (NSCLC). The aim of this study was to explore the relationship between blood T cell diversity and survival of patients treated with pemetrexed-based chemotherapy for nonsquamous NSCLC.

METHODS

This prospective clinical study enrolled 26 patients with advanced NSCLC treated with 4-6 cycles of first-line pemetrexed combined with platinum-based therapy. The complementarity-determining region 3 (CDR3) located in the T cell receptor beta chain (TCR β chain) was captured and deeply sequenced using next-generation sequencing (NGS) technology, and the correlation between TCR changes and efficacy after chemotherapy was analyzed.

RESULTS

Patients with an inferior quarter diversity index showed a significantly shorter progression-free survival (PFS) than the others (median, 5.0 months vs. 8.1 months, P = 0.014). After two cycles of chemotherapy, the TCR diversity was significantly higher than the baseline (P = 0.034). Just as with the baseline, patients with an inferior quarter diversity index at the endpoint of cycle 2 showed a shorter progression-free survival (PFS) than the others (median, 5.0 months vs. 8.4 months, P = 0.024).

CONCLUSIONS

In advanced NSCLC patients treated with first-line pemetrexed combined with platinum, the low level of blood TCR diversity at baseline with an endpoint of two cycles of chemotherapy was correlated with a poor prognosis.

T Cell Receptor Beta-Chain Profiling of Tumor Tissue, Peripheral Blood and Regional Lymph Nodes From Patients With Papillary Thyroid Carcinoma

Objective: To study the characteristics of the T cell receptor (TCR) repertoire in cancer tissue, peripheral blood and regional lymph nodes (LNs) from patients with papillary thyroid carcinoma (PTC).

Methods: PTC tissue, peripheral blood mononuclear cells (PBMCs) and regional LNs of six patients with papillary thyroid carcinoma were harvested. T cell receptor beta-chain (TCRβ) profiling was performed though high-throughput sequencing (HTS), and IMonitor, MiXCR and VDJtools were used to analyze the characteristics of the TCR repertoire.

Results: The results of IMonitor and those of MiXCR and VDJtools were very similar. The unique CDR3 of TCRβ from LNs was higher than that of PBMCs, and the CDR3 of TCRβ from LNs was higher than that of PTC tissue. Shannon's diversity index, D50, inverse Simpson index_mean and normalized Shannon's diversity index_mean of CDR3 from LNs were higher than those of PTCs and PBMCs. The HEC (high expansion clones) rate of CDR3 sequences at the amino acid level in PTC tissue was higher than that of PBMCs, which was higher than that of LNs. The V-J HEC rate of CDR3 was highest in PTC tissue, followed by PBMCs and LNs.

Conclusion: TCR CDR3 profiling showed differences among and within the PBMCs, PTC tissues and regional LNs of PTC, including unique CDR3, CDR3 HEC at the amino acid level, CDR3 V-J HEC at the amino acid level, Shannon's diversity index and D50. The TCRβ repertoire of PTC tissue, peripheral blood and regional LNs of PTC provide a reference for further study of immunity mechanisms against PTC.

Benchmarking of T cell receptor repertoire profiling methods reveals large systematic biases

Monitoring the T cell receptor (TCR) repertoire in health and disease can provide key insights into adaptive immune responses, but the accuracy of current TCR sequencing (TCRseq) methods is unclear. In this study, we systematically compared the results of nine commercial and academic TCRseq methods, including six rapid amplification of complementary DNA ends (RACE)-polymerase chain reaction (PCR) and three multiplex-PCR approaches, when applied to the same T cell sample. We found marked differences in accuracy and intra- and inter-method reproducibility for T cell receptor α (TRA) and T cell receptor β (TRB) TCR chains. Most methods showed a lower ability to capture TRA than TRB diversity. Low RNA input generated non-representative repertoires. Results from the 5' RACE-PCR methods were consistent among themselves but differed from the RNA-based multiplex-PCR results. Using an in silico meta-repertoire generated from 108 replicates, we found that one genomic DNA-based method and two non-unique molecular identifier (UMI) RNA-based methods were more sensitive than UMI methods in detecting rare clonotypes, despite the better clonotype quantification accuracy of the latter.

Stereotactic Body Radiotherapy Is Effective in Modifying the Tumor Genome and Tumor Immune Microenvironment in Non-Small Cell Lung Cancer or Lung Metastatic Carcinoma

Background and Purpose

To directly reveal the change in genome mutation, RNA transcript of tumor cells, and tumor microenvironment (TME) after stereotactic body radiotherapy (SBRT) in paired human lung tumor specimens.

Materials and Methods

Paired tumor samples were collected from 10 patients with non-small cell lung cancer (NSCLC) or lung metastatic carcinoma within a week before and after SBRT. DNA and RNA of tumor tissues was extracted from the paired samples. Whole-exome and RNA sequencing assays were performed by next-generation sequencing. Gene mutation, genomic expression, T-cell receptor (TCR) repertoire, and profiling of tumor-infiltrating immune cells were analyzed through bioinformatics analysis in paired tumor samples. CD8+ T-cell infiltration and PD-L1 expressions were detected by immunostaining in tumor tissues.

Results

The diversity of TCR repertoire and PD-L1 expression increased significantly in the TME, and the most enriched term of the gene ontology analysis was the immune response gene after receiving SBRT. SBRT induced neo-mutation of genes in tumor cells but did not increase tumor mutation burden in tumor tissues. TME displayed complex immune cell changes and infiltration and expression of immune-regulating factors such as C-X-C motif chemokine (CXCL) 10, CXCL16, interferons (IFNs), and IFN receptors. CD8+ T-cells in tumor tissues did not improve significantly after SBRT while the infiltrating TH1 and TH2 cells decreased remarkably.

Conclusion

SBRT improved the TCR repertoire diversity and PD-L1 expression in the TME and induced neo-mutation of genes in tumor cells but did not increase CD8+ T-cell infiltration and IFN expression in the tumor tissue within a week.

Multiregion single-cell sequencing reveals the transcriptional landscape of the immune microenvironment of colorectal cancer

The tumor microenvironment is a complex ecosystem formed by distinct and interacting cell populations, and its composition is related to cancer prognosis and response to clinical treatment. In this study, we have taken the advantage of two single-cell RNA sequencing technologies (Smart-seq2 and DNBelab C4) to generate an atlas of 15,115 immune and nonimmune cells from primary tumors and hepatic metastases of 18 colorectal cancer (CRC) patients. We observed extensive changes in the proportions and functional states of T cells and B cells in tumor tissues, compared to those of paired non-tumor tissues. Importantly, we found that B cells from early CRC tumor were identified to be pre-B like expressing tumor suppressors, whereas B cells from advanced CRC tumors tended to be developed into plasma cells. We also identified the association of IgA+ IGLC2+ plasma cells with poor CRC prognosis, and demonstrated a significant interaction between B-cell and myeloid-cell signaling, and found CCL8+ cycling B cells/CCR5+ T-cell interactions as a potential antitumoral mechanism in advanced CRC tumors. Our results provide deeper insights into the immune infiltration within CRC, and a new perspective for the future research in immunotherapies for CRC.

The Landscape and Prognosis Potential of the T-Cell Repertoire in Membranous Nephropathy

Membranous nephropathy (MN), a common pathological type of adult nephrotic syndrome, is an antibody-mediated kidney disease. It is widely accepted now that MN is an immune-related disease that involves the whole immune system. In this study, we analyzed the T-cell receptor beta chain (TCRβ) repertoire of the circulating T lymphocytes of MN patients and healthy controls using high-throughput sequencing. We compared multiple aspects of the TCRβ repertoire, including diversity and the Vβ and Jβ genes between MN patients and healthy controls, and we found that the diversities within the VJ cassette combination in the peripheral blood of MN patients were lower than in the healthy controls. We also found the TCRβ repertoire similarity between pre- and post-therapy could reflect the clinical outcome, and two Vβ genes in pre-therapy had the potential to predict the therapeutic effect. These findings indicated the potential of the TCRβ repertoire as non-invasive biomarkers for the prognosis prediction of MN. The characteristics of circulating T-lymphocyte repertoires shed light on MN detection, treatment, and surveillance.

T-cell receptor diversity as a prognostic biomarker in melanoma patients

There is increasing evidence that T-cell receptor (TCR) repertoire diversity can be a predictive biomarker of immune responses in cancer patients. However, the characteristics of the T-cell repertoire together with its prognostic significance in melanoma patients and impact on disease progression remain unknown. We investigated the combinatorial TCR repertoire diversity by semi-quantitative multi-N-plex PCR in peripheral blood samples from 44 melanoma patients together with seven matched metastatic lymph nodes and explored its potential predictive value on clinical prognosis. The diversity was quantified by calculating both richness (number of different specificities) and evenness (relative abundance of the different specificities). Our results revealed that a higher TCR repertoire diversity in blood of patients was associated with a longer PFS, while divpenia (low repertoire diversity) was linked with poor prognosis. The diversity was significantly higher in patients undergoing late relapse and long survival compared to patients who progressed rapidly. Interestingly, the TCR repertoire diversity in tumor may have a potential prognostic value. Thus, our study highlights that the TCR repertoire diversity is a prognostic indicator of clinical outcome in patients with melanoma.

Bioinformatics for Cancer Immunotherapy

Our immune system plays a key role in health and disease as it is capable of responding to foreign antigens as well as acquired antigens from cancer cells. Latter are caused by somatic mutations, the so-called neoepitopes, and might be recognized by T cells if they are presented by HLA molecules on the surface of cancer cells. Personalized mutanome vaccines are a class of customized immunotherapies, which is dependent on the detection of individual cancer-specific tumor mutations and neoepitope (i.e., prediction, followed by a rational vaccine design, before on-demand production. The development of next generation sequencing (NGS) technologies and bioinformatic tools allows a large-scale analysis of each parameter involved in this process. Here, we provide an overview of the bioinformatic aspects involved in the design of personalized, neoantigen-based vaccines, including the detection of mutations and the subsequent prediction of potential epitopes, as well as methods for associated biomarker research, such as high-throughput sequencing of T-cell receptors (TCRs), followed by data analysis and the bioinformatics quantification of immune cell infiltration in cancer samples.

Spatial heterogeneity of the T cell receptor repertoire reflects the mutational landscape in lung cancer

Somatic mutations together with immunoediting drive extensive heterogeneity within non-small-cell lung cancer (NSCLC). Herein we examine heterogeneity of the T cell antigen receptor (TCR) repertoire. The number of TCR sequences selectively expanded in tumors varies within and between tumors and correlates with the number of nonsynonymous mutations. Expanded TCRs can be subdivided into TCRs found in all tumor regions (ubiquitous) and those present in a subset of regions (regional). The number of ubiquitous and regional TCRs correlates with the number of ubiquitous and regional nonsynonymous mutations, respectively. Expanded TCRs form part of clusters of TCRs of similar sequence, suggestive of a spatially constrained antigen-driven process. CD8+ tumor-infiltrating lymphocytes harboring ubiquitous TCRs display a dysfunctional tissue-resident phenotype. Ubiquitous TCRs are preferentially detected in the blood at the time of tumor resection as compared to routine follow-up. These findings highlight a noninvasive method to identify and track relevant tumor-reactive TCRs for use in adoptive T cell immunotherapy.