A novel signature for stratifying the molecular heterogeneity of the tissue-infiltrating T-cell receptor repertoire reflects gastric cancer prognosis

Profiling the peripheral blood T cell receptor repertoires of gastric cancer patients

Cancer driven by somatic mutations may express neoantigens that can trigger T-cell immune responses. Since T-cell receptor (TCR) repertoires play critical roles in anti-tumor immune responses for oncology, next-generation sequencing (NGS) was used to profile the hypervariable complementarity-determining region 3 (CDR3) of the TCR-beta chain in peripheral blood samples from 68 gastric cancer patients and 49 healthy controls. We found that most hyper-expanded CDR3 are individual-specific, and the gene usage of TRBV3-1 is more frequent in the tumor group regardless of tumor stage than in the healthy control group. We identified 374 hyper-expanded tumor-specific CDR3, which may play a vital role in anti-tumor immune responses. The patients with stage IV gastric cancer have higher EBV-specific CDR3 abundance than the control. In conclusion, analysis of the peripheral blood TCR repertoires may provide the biomarker for gastric cancer prognosis and guide future immunotherapy.

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.

Comprehensive analysis of prognostic genes in gastric cancer

Background: Gastric cancer is associated with high mortality, and effective methods for predicting prognosis are lacking. We aimed to identify potential prognostic markers associated with the development of gastric cancer through bioinformatic analyses.

Methods: Gastric cancer-associated gene expression profiles were obtained from The Cancer Genome Atlas and Gene Expression Omnibus databases. The key genes involved in the development of gastric cancer were obtained by differential expression analysis, coexpression analysis, and short time-series expression miner (STEM) analysis. The potential prognostic value of differentially expressed genes was further evaluated using a Cox regression model and risk scores. Hierarchical clustering was applied to validate the impact of key genes on the overall survival of gastric cancer patients.

Results: A total of 1381 genes were consistently dysregulated in the development of gastric cancer. Among them, 186 genes affected the overall survival of gastric cancer patients. The following genes had areas under the receiver operating characteristic curve greater than 0.9 in both datasets and were therefore considered key genes: ADAM12, CEP55, LRFN4, INHBA, ADH1B, DPT, FAM107A, and LOC100506388. LRFN4, DPT, and LOC100506388 were identified as potential prognostic genes for gastric cancer through a nomogram. Overexpression of LRFN4 and LOC100506388 was associated with a higher risk of gastric cancer. Finally, we found that tumors were infiltrated with high levels of Th2 cells and mast cells, and the infiltration levels were associated with overall survival in gastric cancer patients.

Conclusions: We found that key dysregulated genes may have a prognostic value for the development of gastric cancer.

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.

Construction and Validation of a Novel Prognostic Signature for Intestinal Type of Gastric Cancer

Background

Intestinal type of gastric cancer (IGC) is the largest subtype of gastric cancer (GC) by Lauren classification. The purpose of this present study was to construct a prognostic signature for IGC patients, based on the high-grade dysplasia (HGD) and IGC tissues, to improve and enhance the prognostic accuracy.

Methods

The microarray datasets and associated clinical characteristics of HGD and IGC were obtained from the Gene Expression Omnibus (GEO) database. Based on the differential expression analysis between HGD and IGC, the prognostic-related differential expression genes (DEGs) were identified in a training set by univariate COX regression analysis. The least absolute shrinkage and selection operator (LASSO) regression was used to construct an optimal prognostic signature. The enrichment analysis was performed by using Gene Set Enrichment Analysis (GSEA). The performance of the nomogram was assessed by the calibration curve and concordance index (C-index). The results were validated by using a testing set.

Results

We identified 35 prognostic-related DGEs in the training set. The nine-gene signature was established by LASSO analysis. The nine-gene signature was an independent risk factor in both the training and testing sets. The areas under the curve (AUC) values of receiver operating characteristic (ROC) analysis were 0.733 and 0.700 for the training and testing sets, respectively. In GSEA analysis, the gene expression in high-risk group was enriched in hedgehog signaling, epithelial mesenchymal transition, and angiogenesis. The nomogram for IGC showed good performance with C-index of 0.81 (95% CI: 0.76-0.86) and 0.70 (95% CI: 0.63-0.77) in the training and testing sets, respectively.

Conclusion

We identified and verified a nine-gene signature for the prognostic prediction of IGC patients, which might identify subgroups of IGC patients and select more suitable therapeutic options.

T-Cell Repertoire in Combination with T-Cell Density Predicts Clinical Outcomes in Patients with Merkel Cell Carcinoma

The integrity of the immune system represents a pivotal risk factor and prognostic biomarker for Merkel cell carcinoma. A higher density of tumor-associated T cells correlates with improved Merkel cell carcinoma-specific survival, but the prognostic importance of the T-cell infiltrate reactivity is unknown. We evaluated the T-cell receptor repertoire associated with 72 primary Merkel cell carcinomas and correlated metrics of the T-cell receptor repertoire with clinicopathologic characteristics and patient outcomes. We showed that a high Simpson's Dominance index (SDom) was significantly associated with fewer metastases (P = 0.01), lower stage at presentation (P = 0.02), lower final stage at last follow-up (P = 0.05), and longer time to first lymph node metastasis (P = 0.04). These correlations were mostly preserved in the Merkel cell polyomavirus-negative subgroup. Combining SDom with CD3⁺ or CD8⁺ T-cell density revealed three distinct prognostic groups with respect to disease-specific survival. Patients with both high SDom and high CD3⁺ or CD8⁺ T-cell density had markedly improved disease-specific survival compared with patients with low SDom and low CD3⁺ or CD8⁺ T-cell density (P = 0.002 and P = 0.03, respectively). Patients with either high SDom or high CD3⁺ or CD8⁺ had intermediate disease-specific survival. Our findings demonstrate that the quality of the tumor-associated T-cell infiltrate informs patient prognosis in primary Merkel cell carcinoma beyond the T-cell density.

Systematic Review of Prognostic Gene Signature in Gastric Cancer Patients

Gastric cancer (GC) is the second leading cause of cancer mortality and remains the fourth common cancer worldwide. The effective and feasible methods for predicting the possible outcomes for GC patients are still lacking. While genetic profiling might be suitable in some way, the application of gene expression signatures has been show to be a robust tool. Here, by performing a comprehensive search in PubMed, we provided an up-to-date summary of 39 prognostic gene signatures for GC patients, and described the processing procedure of the selection, calculation and construction of gene signature. We also reviewed current web tools including PROGgene and SurvExpress that can be used to analyze the prognostic value of multiple genes for GC. This review will aid in comprehensive understanding of the current prognostic gene signatures to accurately predict the outcome of GC patients, and may guide the future clinical management when the reliability of these signatures is validated in clinics.

Evaluating the Potential of T Cell Receptor Repertoires in Predicting the Prognosis of Resectable Non-Small Cell Lung Cancers

For resectable cancer patients, a method that could precisely predict the risk of postoperative recurrence would be crucial for guiding adjuvant treatment. Since T cell receptor (TCR) repertoires had been shown to be closely related to the dynamics of cancers, here we enrolled a cohort of patients to evaluate the potential of TCR repertoires in predicting the prognosis of resectable non-small cell lung cancers. Specifically, TCRβ repertoires were analyzed in surgical tumor tissues and matched adjacent non-tumor tissues from 39 patients enrolled with resectable non-small cell lung cancer, through target enrichment and high-throughput sequencing. As a result, there are significant differences between the TCR repertories of tumor samples and those of matched adjacent non-tumor samples as evaluated by criteria like the number of clonotypes. In addition, TCR repertoires were significantly associated with a few clinical features, as well as somatic mutations. Finally, certain TCRβ variable-joining (V-J) pairings were featured to build a logistic regression model in predicting postoperative recurrence of resectable non-small cell lung cancers with a testing area under the receiver operating characteristic curve (AUC) of around 0.9. Thus, we hypothesize that TCR repertoires could be potentially used to predict prognosis after curative surgery for non-small cell lung cancer patients.

Immune repertoire of digestive system tumors

Immune repertoire refers to the sum of T cells and B cells with functional diversity in the circulatory system of one individual at any given time. Immune repertoire sequencing aims to study T and B lymphocytes, evaluate the diversity of the immune system, and dig deeper into the relationship between immune repertoire and diseases, using multiple polymerase chain reaction or rapid amplification of 5' cDNA ends to amplify the complementary determining regions that determine the diversity of B cell receptors or T cell receptors as well as high-throughput sequencing and data analysis. Recently, immune repertoire has been widely studied in the identification of biomarkers and therapeutic targets, efficacy monitoring, and prognosis analysis in cancer. This paper reviews the progress in the research of immune repertoire of digestive system tumors.

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.

Characterization of Distinct T Cell Receptor Repertoires in Tumor and Distant Non-tumor Tissues from Lung Cancer Patients

T cells and T cell receptors (TCRs) play pivotal roles in adaptive immune responses against tumors. The development of next-generation sequencing technologies has enabled the analysis of the TCRβ repertoire usage. Given the scarce investigations on the TCR repertoire in lung cancer tissues, in this study, we analyzed TCRβ repertoires in lung cancer tissues and the matched distant non-tumor lung tissues (normal lung tissues) from 15 lung cancer patients. Based on our results, the general distribution of T cell clones was similar between cancer tissues and normal lung tissues; however, the proportion of highly expanded clones was significantly higher in normal lung tissues than in cancer tissues (0.021% ± 0.002% vs. 0.016% ± 0.001%, P = 0.0054, Wilcoxon signed rank test). In addition, a significantly higher TCR diversity was observed in cancer tissues than in normal lung tissues (431.37 ± 305.96 vs. 166.20 ± 101.58, P = 0.0075, Mann-Whitney U test). Moreover, younger patients had a significantly higher TCR diversity than older patients (640.7 ± 295.3 vs. 291.8 ± 233.6, P = 0.036, Mann-Whitney U test), and the higher TCR diversity in tumors was significantly associated with worse cancer outcomes. Thus, we provided a comprehensive comparison of the TCR repertoires between cancer tissues and matched normal lung tissues and demonstrated the presence of distinct T cell immune microenvironments in lung cancer patients.

TCR Repertoire as a Novel Indicator for Immune Monitoring and Prognosis Assessment of Patients With Cervical Cancer

There is increasing evidence that deep sequencing-based T cell repertoire can sever as a biomarker of immune response in cancer patients; however, the characteristics of T cell repertoire including diversity and similarity, as well as its prognostic significance in patients with cervical cancer (CC) remain unknown. In this study, we applied a high throughput T cell receptor (TCR) sequencing method to characterize the T cell repertoires of peripheral blood samples from 25 CC patients, 30 cervical intraepithelial neoplasia (CIN) patients and 20 healthy women for understanding the immune alterations during the cervix carcinogenesis. In addition, we also explored the signatures of TCR repertoires in the cervical tumor tissues and paired sentinel lymph nodes from 16 CC patients and their potential value in predicting the prognosis of patients. Our results revealed that the diversity of circulating TCR repertoire gradually decreased during the cervix carcinogenesis and progression, but the circulating TCR repertoires in CC patients were more similar to CIN patients than healthy women. Interestingly, several clonotypes uniquely detected in CC patients tended to share similar CDR3 motifs, which differed from those observed in CIN patients. In addition, the TCR repertoire diversity in sentinel lymphatic nodes from CC patients was higher than in tumor tissues. More importantly, less clonotypes in TCR repertoire of sentinel lymphatic node was associated with the poor prognosis of the patients. Overall, our findings suggested that TCR repertoire might be a potential indicator of immune monitoring and a biomarker for predicting the prognosis of CC patients. Although functional studies of T cell populations are clearly required, this study have expanded our understanding of T cell immunity during the development of CC and provided an experimental basis for further studies on its pathogenesis and immunotherapy.

RepSeq Data Representativeness and Robustness Assessment by Shannon Entropy

High-throughput sequencing (HTS) has the potential to decipher the diversity of T cell repertoires and their dynamics during immune responses. Applied to T cell subsets such as T effector and T regulatory cells, it should help identify novel biomarkers of diseases. However, given the extreme diversity of TCR repertoires, understanding how the sequencing conditions, including cell numbers, biological and technical sampling and sequencing depth, impact the experimental outcome is critical to proper use of these data. Here, we assessed the representativeness and robustness of TCR repertoire diversity assessment according to experimental conditions. By comparative analyses of experimental datasets and computer simulations, we found that (i) for small samples, the number of clonotypes recovered is often higher than the number of cells per sample, even after removing the singletons; (ii) high-sequencing depth for small samples alters the clonotype distributions, which can be corrected by filtering the datasets using Shannon entropy as a threshold; and (iii) a single sequencing run at high depth does not ensure a good coverage of the clonotype richness in highly polyclonal populations, which can be better covered using multiple sequencing. Altogether, our results warrant better understanding and awareness of the limitation of TCR diversity analyses by HTS and justify the development of novel computational tools for improved modeling of the highly complex nature of TCR repertoires.

Single-cell technologies for profiling T cells to enable monitoring of immunotherapies

Immunotherapy relies on the reinvigoration of immune system to combat diseases and has transformed the landscape of cancer treatments. Clinical trials using immune checkpoint inhibitors (ICI), and adoptive transfer of genetically modified T cells have demonstrated durable remissions in subsets of cancer patients. A comprehensive understanding of the polyfunctionality of T lymphocytes in ICI or adoptive cell transfer (ACT), at single-cell resolution, will quantify T-cell properties that are essential for therapeutic benefit. We briefly highlight several emerging integrated single-cell technologies focusing on the profiling of multiple properties/functionalities of T cells. We envision that these tools have the potential to provide valuable experimental and clinical insights on T-cell biology, and eventually pave the road for the discovery of surrogate T-cell biomarkers for immunotherapy.