Molecular analysis of primary melanoma T cells identifies patients at risk for metastatic recurrence

The tumor immune microenvironment in primary cutaneous melanoma

Melanoma is an immunogenic tumor. The melanoma tumor immune microenvironment (TIME) is made up of a heterogenous mix of both immune and non-immune cells as well as a multitude of signaling molecules. The interactions between tumor cells, immune cells and signaling molecules affect tumor progression and therapeutic responses. Understanding the composition and function of the TIME in primary cutaneous melanoma is useful for prognostication and therapeutic decisions. This review provides an overview of the components of the TIME in primary cutaneous melanoma, and their influence on clinical outcomes.

Magnitude and dynamics of the T-cell response to SARS-CoV-2 infection at both individual and population levels

Introduction

T cells are involved in the early identification and clearance of viral infections and also support the development of antibodies by B cells. This central role for T cells makes them a desirable target for assessing the immune response to SARS-CoV-2 infection.

Methods

Here, we combined two high-throughput immune profiling methods to create a quantitative picture of the T-cell response to SARS-CoV-2. First, at the individual level, we deeply characterized 3 acutely infected and 58 recovered COVID-19 subjects by experimentally mapping their CD8 T-cell response through antigen stimulation to 545 Human Leukocyte Antigen (HLA) class I presented viral peptides. Then, at the population level, we performed T-cell repertoire sequencing on 1,815 samples (from 1,521 COVID-19 subjects) as well as 3,500 controls to identify shared "public" T-cell receptors (TCRs) associated with SARS-CoV-2 infection from both CD8 and CD4 T cells.

Results

Collectively, our data reveal that CD8 T-cell responses are often driven by a few immunodominant, HLA-restricted epitopes. As expected, the T-cell response to SARS-CoV-2 peaks about one to two weeks after infection and is detectable for at least several months after recovery. As an application of these data, we trained a classifier to diagnose SARS-CoV-2 infection based solely on TCR sequencing from blood samples, and observed, at 99.8% specificity, high early sensitivity soon after diagnosis (Day 3-7 = 85.1% [95% CI = 79.9-89.7]; Day 8-14 = 94.8% [90.7-98.4]) as well as lasting sensitivity after recovery (Day 29+/convalescent = 95.4% [92.1-98.3]).

Discussion

The approaches described in this work provide detailed insights into the adaptive immune response to SARS-CoV-2 infection, and they have potential applications in clinical diagnostics, vaccine development, and monitoring.

Investigating TCR-pMHC interactions for TCRs without identified epitopes by constructing a computational pipeline

The molecular mechanisms underlying epitope recognition by T cell receptors (TCRs) are critical for activating T cell immune responses and rationally designing TCR-based therapeutics. Single-cell sequencing techniques vastly boost the accumulation of TCR sequences, while the limitation of available TCR-pMHC structures hampers further investigations. In this study, we proposed a computational pipeline that incorporates structural information and single-cell sequencing data to investigate the epitope-recognition mechanisms for TCRs without identified epitopes. By antigen specificity clustering, we mapped the epitope sequences between epitope-known and epitope-unknown TCRs from COVID-19 patients. One reported SARS-CoV-2 epitope, NQKLIANQF (S919-927), was identified for a TCR expressed by 614 T cells (TCR-614). Epitope screening also identified a potential cross-reactive epitope, KLKTLVATA (NSP31790-1798), for a TCR expressed by 204 T cells (TCR-204). By molecular dynamics (MD) simulations, we revealed the detailed epitope-recognition mechanisms for both TCRs. The structural motifs responsible for epitope recognition revealed by the MD simulations are consistent with the sequential features recognized by the sequence-based clustering method. We hope that this strategy could facilitate the discovery and optimization of TCR-based therapeutics.

Reversing immunosuppression in the tumor microenvironment of fibrolamellar carcinoma via PD-1 and IL-10 blockade

Fibrolamellar carcinoma (FLC) is a rare liver tumor driven by the DNAJ-PKAc fusion protein that affects healthy young patients. Little is known about the immune response to FLC, limiting rational design of immunotherapy. Multiplex immunohistochemistry and gene expression profiling were performed to characterize the FLC tumor immune microenvironment and adjacent non-tumor liver (NTL). Flow cytometry and T cell receptor (TCR) sequencing were performed to determine the phenotype of tumor-infiltrating immune cells and the extent of T cell clonal expansion. Fresh human FLC tumor slice cultures (TSCs) were treated with antibodies blocking programmed cell death protein-1 (PD-1) and interleukin-10 (IL-10), with results measured by cleaved caspase-3 immunohistochemistry. Immune cells were concentrated in fibrous stromal bands, rather than in the carcinoma cell compartment. In FLC, T cells demonstrated decreased activation and regulatory T cells in FLC had more frequent expression of PD-1 and CTLA-4 than in NTL. Furthermore, T cells had relatively low levels of clonal expansion despite high TCR conservation across individuals. Combination PD-1 and IL-10 blockade signficantly increased cell death in human FLC TSCs. Immunosuppresion in the FLC tumor microenvironment is characterized by T cell exclusion and exhaustion, which may be reversible with combination immunotherapy.

Predicting Recurrence-Free and Overall Survival for Patients With Stage II Melanoma: The MIA Calculator

PURPOSE

Improvements in recurrence-free survival (RFS) were demonstrated in two recent randomized trials for patients with sentinel node (SN)-negative stage IIB or IIC melanoma receiving adjuvant systemic therapy (pembrolizumab/nivolumab). However, adverse events also occurred. Accurate individualized prognostic estimates of RFS and overall survival (OS) would allow patients to more accurately weigh the risks and benefits of adjuvant therapy. Since the current American Joint Committee on Cancer eighth edition (AJCC-8) melanoma staging system focuses on melanoma-specific survival, we developed a multivariable risk prediction calculator that provides estimates of 5- and 10-year RFS and OS for these patients.

METHODS

Data were extracted from the Melanoma Institute Australia (MIA) database for patients diagnosed with stage II (clinical or pathological) melanoma (n = 3,220). Survival prediction models were developed using multivariable Cox regression analyses (MIA models) and externally validated twice using data sets from the United States and the Netherlands. Each model's performance was assessed using C-statistics and calibration plots and compared with Cox models on the basis of AJCC-8 staging (stage models).

RESULTS

The 5-year and 10-year RFS C-statistics were 0.70 and 0.73 (MIA-model) versus 0.61 and 0.60 (stage-model), respectively. For OS, the 5-year and 10-year C-statistics were 0.71 and 0.75 (MIA-model) compared with 0.62 and 0.61 (stage-model), respectively. The MIA models were well calibrated and externally validated.

CONCLUSION

The MIA models offer accurate and personalized estimates of both RFS and OS in patients with stage II melanoma even in the absence of pathological staging with SN biopsy. These models were robust on external validations and may be used in everyday practice both with (ideally) and without performing SN biopsy to identify high-risk patients for further management strategies. An online tool will be available at the MIA website (Risk Prediction Tools).

Complete loss of TP53 and RB1 is associated with complex genome and low immune infiltrate in pleomorphic rhabdomyosarcoma

Rhabdomyosarcoma accounts for roughly 1% of adult sarcomas, with pleomorphic rhabdomyosarcoma (PRMS) as the most common subtype. Survival outcomes remain poor for patients with PRMS, and little is known about the molecular drivers of this disease. To better characterize PRMS, we performed a broad array of genomic and immunostaining analyses on 25 patient samples. In terms of gene expression and methylation, PRMS clustered more closely with other complex karyotype sarcomas than with pediatric alveolar and embryonal rhabdomyosarcoma. Immune infiltrate levels in PRMS were among the highest observed in multiple sarcoma types and contrasted with low levels in other rhabdomyosarcoma subtypes. Lower immune infiltrate was associated with complete loss of both TP53 and RB1. This comprehensive characterization of the genetic, epigenetic, and immune landscape of PRMS provides a roadmap for improved prognostications and therapeutic exploration.

Localized immune surveillance of primary melanoma in the skin deciphered through executable modeling

While skin is a site of active immune surveillance, primary melanomas often escape detection. Here, we have developed an in silico model to determine the local cross-talk between melanomas and Langerhans cells (LCs), the primary antigen-presenting cells at the site of melanoma development. The model predicts that melanomas fail to activate LC migration to lymph nodes until tumors reach a critical size, which is determined by a positive TNF-α feedback loop within melanomas, in line with our observations of murine tumors. In silico drug screening, supported by subsequent experimental testing, shows that treatment of primary tumors with MAPK pathway inhibitors may further prevent LC migration. In addition, our in silico model predicts treatment combinations that bypass LC dysfunction. In conclusion, our combined approach of in silico and in vivo studies suggests a molecular mechanism that explains how early melanomas develop under the radar of immune surveillance by LC.

Perturbations of the T-cell immune repertoire in kidney transplant rejection

In this cross-sectional and longitudinal analysis of mapping the T-cell repertoire in kidney transplant recipients, we have investigated and validated T-cell clonality, immune repertoire chronology at rejection, and contemporaneous allograft biopsy quantitative tissue injury, to better understand the pathobiology of acute T-cell fraction, T-cell repertoire and antibody-mediated kidney transplant rejection. To follow the dynamic evolution of T-cell repertoire changes before and after engraftment and during biopsy-confirmed acute rejection, we sequenced 323 peripheral blood samples from 200 unique kidney transplant recipients, with (n=100) and without (n=100) biopsy-confirmed acute rejection. We report that patients who develop acute allograft rejection, have lower (p=0.01) T-cell fraction even before transplantation, followed by its rise after transplantation and at the time of acute rejection accompanied by high TCR repertoire turnover (p=0.004). Acute rejection episodes occurring after the first 6 months post-transplantation, and those with a component of antibody-mediated rejection, had the highest turnover; p=0.0016) of their T-cell repertoire. In conclusion, we validated that detecting repertoire changes in kidney transplantation correlates with post-transplant rejection episodes suggesting that T-cell receptor sequencing may provide recipient pre-transplant and post-transplant predictors of rejection risk.

Evolution and modulation of antigen-specific T cell responses in melanoma patients

Analyzing antigen-specific T cell responses at scale has been challenging. Here, we analyze three types of T cell receptor (TCR) repertoire data (antigen-specific TCRs, TCR-repertoire, and single-cell RNA + TCRαβ-sequencing data) from 515 patients with primary or metastatic melanoma and compare it to 783 healthy controls. Although melanoma-associated antigen (MAA) -specific TCRs are restricted to individuals, they share sequence similarities that allow us to build classifiers for predicting anti-MAA T cells. The frequency of anti-MAA T cells distinguishes melanoma patients from healthy and predicts metastatic recurrence from primary melanoma. Anti-MAA T cells have stem-like properties and frequent interactions with regulatory T cells and tumor cells via Galectin9-TIM3 and PVR-TIGIT -axes, respectively. In the responding patients, the number of expanded anti-MAA clones are higher after the anti-PD1(+anti-CTLA4) therapy and the exhaustion phenotype is rescued. Our systems immunology approach paves the way for understanding antigen-specific responses in human disorders.

Previous studies have characterized the diversity and dynamics of the T cell receptor (TCR) repertoire in patients with solid cancer. Here, by analyzing TCR repertoire data from multiple datasets, the authors report that melanoma-associated antigen-specific TCRs can be used to separate metastatic melanoma patients from healthy controls and to follow anti-tumor responses in patients treated with immunotherapy.

Autoreactive napsin A-specific T cells are enriched in lung tumors and inflammatory lung lesions during immune checkpoint blockade

Cancer treatment with immune checkpoint blockade (ICB) often induces immune-related adverse events (irAEs). We hypothesized that proteins coexpressed in tumors and normal cells could be antigenic targets in irAEs and herein described DITAS (discovery of tumor-associated self-antigens) for their identification. DITAS computed transcriptional similarity between lung tumors and healthy lung tissue based on single-sample gene set enrichment analysis. This identified 10 lung tissue-specific genes highly expressed in the lung tumors. Computational analysis was combined with functional T cell assays and single-cell RNA sequencing of the antigen-specific T cells to validate the lung tumor self-antigens. In patients with non-small cell lung cancer (NSCLC) treated with ICB, napsin A was a self-antigen that elicited strong CD8⁺ T cell responses, with ICB responders harboring higher frequencies of these CD8⁺ T cells compared with nonresponders. Human leukocyte antigen (HLA) class I ligands derived from napsin A were present in human lung tumors and in nontumor lung tissues, and napsin A tetramers confirmed the presence of napsin A-specific CD8⁺ T cells in blood and tumors of patients with NSCLC. Napsin A-specific T cell clonotypes were enriched in lung tumors and ICB-induced inflammatory lung lesions and could kill immortalized HLA-matched NSCLC cells ex vivo. Single-cell RNA sequencing revealed that these T cell clonotypes expressed proinflammatory cytokines and cytotoxic markers. Thus, DITAS successfully identified self-antigens, including napsin A, that likely mediate effective antitumor T cell responses in NSCLC and may simultaneously underpin lung irAEs.

Detailed spatial immunophenotyping of primary melanomas reveals immune cell subpopulations associated with patient outcome

While the tumor immune microenvironment (TIME) of metastatic melanoma has been well characterized, the primary melanoma TIME is comparatively poorly understood. Additionally, although the association of tumor-infiltrating lymphocytes with primary melanoma patient outcome has been known for decades, it is not considered in the current AJCC melanoma staging system. Detailed immune phenotyping of advanced melanoma has revealed multiple immune biomarkers, including the presence of CD8+ T-cells, for predicting response to immunotherapies. However, in primary melanomas, immune biomarkers are lacking and CD8+ T-cells have yet to be extensively characterized. As recent studies combining immune features and clinicopathologic characteristics have created more accurate predictive models, this study sought to characterize the TIME of primary melanomas and identify predictors of patient outcome. We first phenotyped CD8+ T cells in fresh stage II primary melanomas using flow cytometry (n = 6), identifying a CD39+ tumor-resident CD8+ T-cell subset enriched for PD-1 expression. We then performed Opal multiplex immunohistochemistry and quantitative pathology-based immune profiling of CD8+ T-cell subsets, along with B cells, NK cells, Langerhans cells and Class I MHC expression in stage II primary melanoma specimens from patients with long-term follow-up (n = 66), comparing patients based on their recurrence status at 5 years after primary diagnosis. A CD39+CD103+PD-1- CD8+ T-cell population (P2) comprised a significantly higher proportion of intratumoral and stromal CD8+ T-cells in patients with recurrence-free survival (RFS) ≥5 years vs those with RFS <5 years (p = 0.013). Similarly, intratumoral B cells (p = 0.044) and a significantly higher B cell density at the tumor/stromal interface were associated with RFS. Both P2 and B cells localized in significantly closer proximity to melanoma cells in patients who remained recurrence-free (P2 p = 0.0139, B cell p = 0.0049). Our results highlight how characterizing the TIME in primary melanomas may provide new insights into how the complex interplay of the immune system and tumor can modify the disease outcomes. Furthermore, in the context of current clinical trials of adjuvant anti-PD-1 therapies in high-risk stage II primary melanoma, assessment of B cells and P2 could identify patients at risk of recurrence and aid in long-term treatment decisions at the point of primary melanoma diagnosis.

Generic Multiplex Digital PCR for Accurate Quantification of T Cells in Copy Number Stable and Unstable DNA Samples

An accurate T cell quantification is prognostically and therapeutically relevant in various clinical applications, including oncology care and research. In this chapter, we describe how T cell quantifications can be obtained from bulk DNA samples with a multiplex digital PCR experiment. The experimental setup includes the concurrent quantification of three different DNA targets within one reaction: a unique T cell DNA marker, a regional corrector, and a reference DNA marker. The T cell marker is biallelically absent in T cells due to VDJ rearrangements, while the reference is diploid in all cells. The so-called regional corrector allows to correct for possible copy number alterations at the T cell marker locus in cancer cells. By mathematically integrating the measurements of all three markers, T cells can be accurately quantified in both copy number stable and unstable DNA samples.

Longitudinal analysis of T cell receptor repertoires reveals shared patterns of antigen-specific response to SARS-CoV-2 infection

T cells play a prominent role in orchestrating the immune response to viral diseases, but their role in the clinical presentation and subsequent immunity to SARS-CoV-2 infection remains poorly understood. As part of a population-based survey of the municipality of Vo', Italy, conducted after the initial SARS-CoV-2 outbreak, we sampled the T cell receptor (TCR) repertoires of the population 2 months after the initial PCR survey and followed up positive cases 9 and 15 months later. At 2 months, we found that 97.0% (98 of 101) of cases had elevated levels of TCRs associated with SARS-CoV-2. T cell frequency (depth) was increased in individuals with more severe disease. Both depth and diversity (breadth) of the TCR repertoire were positively associated with neutralizing antibody titers, driven mostly by CD4+ T cells directed against spike protein. At the later time points, detection of these TCRs remained high, with 90.7% (78 of 96) and 86.2% (25 of 29) of individuals having detectable signal at 9 and 15 months, respectively. Forty-three individuals were vaccinated by month 15 and showed a significant increase in TCRs directed against spike protein. Taken together, these results demonstrate the central role of T cells in mounting an immune defense against SARS-CoV-2 that persists out to 15 months.

OUP accepted manuscript

Alemtuzumab is a monoclonal antibody that causes rapid depletion of CD52-expressing immune cells. It has proven to be highly efficacious in active relapsing–remitting multiple sclerosis; however, the high risk of secondary autoimmune disorders has greatly complicated its use. Thus, deeper insight into the pathophysiology of secondary autoimmunity and potential biomarkers is urgently needed. The most critical time points in the decision-making process for alemtuzumab therapy are before or at Month 12, where the ability to identify secondary autoimmunity risk would be instrumental. Therefore, we investigated components of blood and CSF of up to 106 multiple sclerosis patients before and after alemtuzumab treatment focusing on those critical time points.

Consistent with previous reports, deep flow cytometric immune-cell profiling (n = 30) demonstrated major effects on adaptive rather than innate immunity, which favoured regulatory immune cell subsets within the repopulation. The longitudinally studied CSF compartment (n = 18) mainly mirrored the immunological effects observed in the periphery. Alemtuzumab-induced changes including increased numbers of naïve CD4⁺ T cells and B cells as well as a clonal renewal of CD4⁺ T- and B-cell repertoires were partly reminiscent of haematopoietic stem cell transplantation; in contrast, thymopoiesis was reduced and clonal renewal of T-cell repertoires after alemtuzumab was incomplete. Stratification for secondary autoimmunity did not show clear immununological cellular or proteomic traits or signatures associated with secondary autoimmunity. However, a restricted T-cell repertoire with hyperexpanded T-cell clones at baseline, which persisted and demonstrated further expansion at Month 12 by homeostatic proliferation, identified patients developing secondary autoimmune disorders (n = 7 without secondary autoimmunity versus n = 5 with secondary autoimmunity). Those processes were followed by an expansion of memory B-cell clones irrespective of persistence, which we detected shortly after the diagnosis of secondary autoimmune disease.

In conclusion, our data demonstrate that (i) peripheral immunological alterations following alemtuzumab are mirrored by longitudinal changes in the CSF; (ii) incomplete T-cell repertoire renewal and reduced thymopoiesis contribute to a proautoimmune state after alemtuzumab; (iii) proteomics and surface immunological phenotyping do not identify patients at risk for secondary autoimmune disorders; (iv) homeostatic proliferation with disparate dynamics of clonal T- and B-cell expansions are associated with secondary autoimmunity; and (v) hyperexpanded T-cell clones at baseline and Month 12 may be used as a biomarker for the risk of alemtuzumab-induced autoimmunity.

Keratinocyte differentiation antigen-specific T cells in immune checkpoint inhibitor-treated NSCLC patients are associated with improved survival

Immune checkpoint inhibitors (ICIs) have improved the survival of patients with non-small cell lung cancer (NSCLC) by reinvigorating tumor-specific T cell responses. However, the specificity of such T cells and the human leukocyte antigen (HLA)-associated epitopes recognized, remain elusive. In this study, we identified NSCLC T cell epitopes of recently described NSCLC-associated antigens, termed keratinocyte differentiation antigens. Epitopes of these antigens were presented by HLA-A 03:01 and HLA-C 04:01 and were associated with responses to ICI therapy. Patients with CD8⁺ T cell responses to these epitopes had improved overall and progression-free survival. T cells specific for such epitopes could eliminate HLA class I-matched NSCLC cells ex vivo and were enriched in patient lung tumors. The identification of novel lung cancer HLA-associated epitopes that correlate with improved ICI-dependent treatment outcomes suggests that keratinocyte-specific proteins are important tumor-associated antigens in NSCLC. These findings improve our understanding of the mechanisms of ICI therapy and may help support the development of vaccination strategies to improve ICI-based treatment of these tumors.

Accurate Quantification of T Cells in Copy Number Stable and Unstable DNA Samples Using Multiplex Digital PCR

An accurate T-cell quantification is prognostically and therapeutically relevant in various malignancies. We previously developed a digital PCR-based approach offering a precise T-cell enumeration in small amounts of DNA. However, it may be challenging to apply this method in malignant specimens, as copy number instability can disturb the underlying mathematical model. For example, approximately 24% of the tumors from The Cancer Genome Atlas pan-cancer data set carried a copy number alteration affecting our TRB gene T-cell marker, which would cause an underestimation or overestimation of the T-cell fraction. In this study, we introduce a multiplex digital PCR experimental setup to quantify T cells in copy number unstable DNA samples. By implementing a so-called regional corrector, genetic alterations involving the T-cell marker locus can be recognized and corrected for. This novel setup is evaluated mathematically in silico and validated in vitro by measuring T-cell presence in various samples with a known T-cell fraction. The utility of the approach is further demonstrated in copy number altered cutaneous melanomas. Our novel multiplex setup provides a simple, but accurate, DNA-based T-cell quantification in both copy number stable and unstable specimens. This approach has potential clinical and diagnostic applications, as it does not depend on availability of T-cell epitopes, has low requirements for sample quantity and quality, and can be performed in a relatively easy experiment.

Immune checkpoint blockade sensitivity and progression-free survival associates with baseline CD8+ T cell clone size and cytotoxicity

[Figure: see text].

Associations between T cell infiltration, T cell receptor clonality, histology and recurrence in renal cell carcinoma

Renal cell carcinoma (RCC) is comprised of clear-cell (ccRCC) and non-clear-cell (nccRCC) tumors. Despite definitive surgical resection in localized disease, recurrence often occurs. A commercial method based on a multiplex polymerase chain reaction (PCR) assay exclusively targets rearranged T cell receptor (TCR) genes to generate high-throughput sequencing-based data, allowing characterization of the immune repertoire within tumors. In this study we performed a retrospective analysis on archived tumor samples from patients with recurring versus non-recurring T3 ccRCC and on samples from early nccRCC versus ccRCC. Following genomic DNA extraction and multiplex PCR, the fraction of T cells within tumors, the number of unique receptors ('richness') and their relative abundances ('clonality') were calculated. Statistical significance and correlations were calculated using Student's t-test and Spearman's rho, respectively. Average fraction and clonality of T cells in tumors from non-recurring patients was 2.5- and 4.3-fold higher than in recurring patients (P = 0.025 and P = 0.043, respectively). A significant positive correlation was found between T cell fraction and clonality (Spearman's rho = 0.78, P = 0.008). The average fraction of T cells in ccRCC tumors was 2.8-fold higher than in nccRCC tumors (P = 0.015). Clonality and estimated richness were similar between ccRCC and nccRCC tumors. In summary, recurrence of ccRCC is associated with a lower fraction and clonality of T cells within tumors; nccRCC tumors are more 'deserted' than ccRCC, but similar in their ability to generate a clonal T cell repertoire. Our work suggests associations between the characteristics of T cell infiltrate, histology and tumor recurrence.

Tumor microenvironment immune-related lncRNA signature for patients with melanoma

Background

The incidence of malignant melanoma accounts for only approximately 5% of skin malignant tumors, however, it accounts for 75% of its mortality. Long-chain non-coding RNA (lncRNA) has a wide range of functional activities. Disorders of lncRNAs may lead to the occurrence and development of melanoma, and may also be related to immunotherapy.

Methods

The transcriptomic data of primary and metastatic melanoma patients and 331 immune-related genes were downloaded from skin cutaneous melanoma (SKCM) in the The Cancer Genome Atlas (TCGA) database. On this basis, 460 immunologically relevant lncRNAs were identified by constructing a co-expression network of immunogenic genes and lncRNAs in primary and metastatic melanoma patients. Prognostic genes were screened using univariate Cox regression analysis. ROC analysis was performed to evaluate the robustness of the prognostic signature.

Results

Univariate correlation analysis showed that only 3 of the 23 immune-related lncRNAs were at high risk and the rest were at low risk. Signatures of 7 immune-related lncRNAs were identified by multivariate correlation analysis. The clinical correlation analysis showed that the 7 immune-related lncRNAs were associated with the clinical stage of primary and metastatic melanoma. Principal component analysis (PCA) showed that only 7 immune-related lncRNA signals divided tumor patients into high-risk and low-risk groups, while the low-risk group was enriched in the immune system process M13664 and immune response M19817 sets. PPI interaction network analysis showed that 11 G protein-coupled receptors and 6 corresponding ligands in the 2 gene sets affected the tumor microenvironment and were negatively related to the risk of the 7 immune-related lncRNAs. The tumor microenvironment immune cell infiltration analysis also supported the finding that anti-tumor immunity in the low-risk group was stronger than in the high-risk group.

Conclusions

These results indicate that characteristics of the 7 immune-related lncRNAs have prognostic value for melanoma patients and can be used as potential immunotherapy targets.

Tumour gene expression signature in primary melanoma predicts long-term outcomes

Adjuvant systemic therapies are now routinely used following resection of stage III melanoma, however accurate prognostic information is needed to better stratify patients. We use differential expression analyses of primary tumours from 204 RNA-sequenced melanomas within a large adjuvant trial, identifying a 121 metastasis-associated gene signature. This signature strongly associated with progression-free (HR = 1.63, p = 5.24 × 10-5) and overall survival (HR = 1.61, p = 1.67 × 10-4), was validated in 175 regional lymph nodes metastasis as well as two externally ascertained datasets. The machine learning classification models trained using the signature genes performed significantly better in predicting metastases than models trained with clinical covariates (pAUROC = 7.03 × 10-4), or published prognostic signatures (pAUROC < 0.05). The signature score negatively correlated with measures of immune cell infiltration (ρ = -0.75, p < 2.2 × 10-16), with a higher score representing reduced lymphocyte infiltration and a higher 5-year risk of death in stage II melanoma. Our expression signature identifies melanoma patients at higher risk of metastases and warrants further evaluation in adjuvant clinical trials.

Magnitude and Dynamics of the T-Cell Response to SARS-CoV-2 Infection at Both Individual and Population Levels

T cells are involved in the early identification and clearance of viral infections and also support the development of antibodies by B cells. This central role for T cells makes them a desirable target for assessing the immune response to SARS-CoV-2 infection. Here, we combined two high-throughput immune profiling methods to create a quantitative picture of the T-cell response to SARS-CoV-2. First, at the individual level, we deeply characterized 3 acutely infected and 58 recovered COVID-19 subjects by experimentally mapping their CD8 T-cell response through antigen stimulation to 545 Human Leukocyte Antigen (HLA) class I presented viral peptides (class II data in a forthcoming study). Then, at the population level, we performed T-cell repertoire sequencing on 1,815 samples (from 1,521 COVID-19 subjects) as well as 3,500 controls to identify shared "public" T-cell receptors (TCRs) associated with SARS-CoV-2 infection from both CD8 and CD4 T cells. Collectively, our data reveal that CD8 T-cell responses are often driven by a few immunodominant, HLA-restricted epitopes. As expected, the T-cell response to SARS-CoV-2 peaks about one to two weeks after infection and is detectable for at least several months after recovery. As an application of these data, we trained a classifier to diagnose SARS-CoV-2 infection based solely on TCR sequencing from blood samples, and observed, at 99.8% specificity, high early sensitivity soon after diagnosis (Day 3-7 = 85.1% [95% CI = 79.9-89.7]; Day 8-14 = 94.8% [90.7-98.4]) as well as lasting sensitivity after recovery (Day 29+/convalescent = 95.4% [92.1-98.3]). These results demonstrate an approach to reliably assess the adaptive immune response both soon after viral antigenic exposure (before antibodies are typically detectable) as well as at later time points. This blood-based molecular approach to characterizing the cellular immune response has applications in clinical diagnostics as well as in vaccine development and monitoring.

T-cell repertoire analysis and metrics of diversity and clonality

The recent developments of high-throughput bulk and single-cell sequencing technologies accelerated the understanding of the complexity of immune repertoire dynamics combined to transcriptomics. Also, profiling of cellular repertoires in health or disease requires statistical metrics to capture clonal diversity characterized by clones frequency, repertoire richness and convergence. Here we present the common technologies of bulk and single-cell sequencing of T-cell receptors (TCRs), discuss current knowledge regarding computational tools clustering and predicting specificity of TCR repertoires based on shared structural motifs and review main indices for repertoire diversity and convergence analyses. These tools represent potential biomarkers to decipher the fitness of immune repertoires in diseased or treated patients but also the presages and promises of computational approaches to revolutionize personalized immunotherapy.