Integrative Tumor and Immune Cell Multi-omic Analyses Predict Response to Immune Checkpoint Blockade in Melanoma

Exploiting temporal aspects of cancer immunotherapy

Many mechanisms underlying an effective immunotherapy-induced antitumour response are transient and critically time dependent. This is equally true for several immunological events in the tumour microenvironment induced by other cancer treatments. Immune checkpoint therapy (ICT) has proven to be very effective in the treatment of some cancers, but unfortunately, with many cancer types, most patients do not experience a benefit. To improve outcomes, a multitude of clinical trials are testing combinations of ICT with various other treatment modalities. Ideally, those combination treatments should take time-dependent immunological events into account. Recent studies have started to map the dynamic cellular and molecular changes that occur during treatment with ICT, in the tumour and systemically. Here, we overlay the dynamic ICT response with the therapeutic response following surgery, radiotherapy, chemotherapy and targeted therapies. We propose that by combining treatments in a time-conscious manner, we may optimally exploit the interactions between the individual therapies.

Defining clinically useful biomarkers of immune checkpoint inhibitors in solid tumours

Although more than a decade has passed since the approval of immune checkpoint inhibitors (ICIs) for the treatment of melanoma and non-small-cell lung, breast and gastrointestinal cancers, many patients still show limited response. US Food and Drug Administration (FDA)-approved biomarkers include programmed cell death 1 ligand 1 (PDL1) expression, microsatellite status (that is, microsatellite instability-high (MSI-H)) and tumour mutational burden (TMB), but these have limited utility and/or lack standardized testing approaches for pan-cancer applications. Tissue-based analytes (such as tumour gene signatures, tumour antigen presentation or tumour microenvironment profiles) show a correlation with immune response, but equally, these demonstrate limited efficacy, as they represent a single time point and a single spatial assessment. Patient heterogeneity as well as inter- and intra-tumoural differences across different tissue sites and time points represent substantial challenges for static biomarkers. However, dynamic biomarkers such as longitudinal biopsies or novel, less-invasive markers such as blood-based biomarkers, radiomics and the gut microbiome show increasing potential for the dynamic identification of ICI response, and patient-tailored predictors identified through neoadjuvant trials or novel ex vivo tumour models can help to personalize treatment. In this Perspective, we critically assess the multiple new static, dynamic and patient-specific biomarkers, highlight the newest consortia and trial efforts, and provide recommendations for future clinical trials to make meaningful steps forwards in the field.

In Situ Synthesis of an Immune-Checkpoint Blocker from Engineered Bacteria Elicits a Potent Antitumor Response

Immune-checkpoint blockade (ICB) reinvigorates T cells from exhaustion and potentiates T-cell responses to tumors. However, most patients do not respond to ICB therapy, and only a limited response can be achieved in a "cold" tumor with few infiltrated lymphocytes. Synthetic biology can be used to engineer bacteria as controllable bioreactors to synthesize biotherapeutics in situ. We engineered attenuated Salmonella VNP20009 with synthetic gene circuits to produce PD-1 and Tim-3 scFv to block immunosuppressive receptors on exhausted T cells to reinvigorate their antitumor response. Secreted PD-1 and Tim-3 scFv bound PD-1+ Tim-3+ T cells through their targeting receptors in vitro and potentiated the T-cell secretion of IFN-γ. Engineered bacteria colonized the hypoxic core of the tumor and synthesized PD-1 and Tim-3 scFv in situ, reviving CD4+ T cells and CD8+ T cells to execute an antitumor response. The bacteria also triggered a strong innate immune response, which stimulated the expansion of IFN-γ+ CD4+ T cells within the tumors to induce direct and indirect antitumor immunity.

B cells and the coordination of immune checkpoint inhibitor response in patients with solid tumors

Immunotherapy profoundly changed the landscape of cancer therapy by providing long-lasting responses in subsets of patients and is now the standard of care in several solid tumor types. However, immunotherapy activity beyond conventional immune checkpoint inhibition is plateauing, and biomarkers are overall lacking to guide treatment selection. Most studies have focused on T cell engagement and response, but there is a growing evidence that B cells may be key players in the establishment of an organized immune response, notably through tertiary lymphoid structures. Mechanisms of B cell response include antibody-dependent cellular cytotoxicity and phagocytosis, promotion of CD4+ and CD8+ T cell activation, maintenance of antitumor immune memory. In several solid tumor types, higher levels of B cells, specific B cell subpopulations, or the presence of tertiary lymphoid structures have been associated with improved outcomes on immune checkpoint inhibitors. The fate of B cell subpopulations may be widely influenced by the cytokine milieu, with versatile roles for B-specific cytokines B cell activating factor and B cell attracting chemokine-1/CXCL13, and a master regulatory role for IL-10. Roles of B cell-specific immune checkpoints such as TIM-1 are emerging and could represent potential therapeutic targets. Overall, the expanding field of B cells in solid tumors of holds promise for the improvement of current immunotherapy strategies and patient selection.

CD4+ T cell activation distinguishes response to anti-PD-L1+anti-CTLA4 therapy from anti-PD-L1 monotherapy

Cancer patients often receive a combination of antibodies targeting programmed death-ligand 1 (PD-L1) and cytotoxic T lymphocyte antigen-4 (CTLA4). We conducted a window-of-opportunity study in head and neck squamous cell carcinoma (HNSCC) to examine the contribution of anti-CTLA4 to anti-PD-L1 therapy. Single-cell profiling of on- versus pre-treatment biopsies identified T cell expansion as an early response marker. In tumors, anti-PD-L1 triggered the expansion of mostly CD8+ T cells, whereas combination therapy expanded both CD4+ and CD8+ T cells. Such CD4+ T cells exhibited an activated T helper 1 (Th1) phenotype. CD4+ and CD8+ T cells co-localized with and were surrounded by dendritic cells expressing T cell homing factors or antibody-producing plasma cells. T cell receptor tracing suggests that anti-CTLA4, but not anti-PD-L1, triggers the trafficking of CD4+ naive/central-memory T cells from tumor-draining lymph nodes (tdLNs), via blood, to the tumor wherein T cells acquire a Th1 phenotype. Thus, CD4+ T cell activation and recruitment from tdLNs are hallmarks of early response to anti-PD-L1 plus anti-CTLA4 in HNSCC.

Comparison of Immunotherapy versus Targeted Therapy Effectiveness in BRAF-Mutant Melanoma Patients and Use of cGAS Expression and Aneuploidy as Potential Prognostic Biomarkers

BRAF-mutant melanoma patients can be treated with targeted therapy or immunotherapies, and it is not clear which should be provided first. Targeted treatments do not work in up to one-third of cases, while immunotherapies may only be effective in up to 60% and come with a high risk of immune-related side effects. Determining which treatment to provide first is thus of critical importance. Recent studies suggest that chromosomal instability and aneuploidy and cyclic GMP-AMP synthase (cGAS) can act as biomarkers for cancer severity and patient outcome. Neither potential biomarker has been extensively studied in melanoma. We examined 20 BRAF-mutant melanomas treated with immunotherapy or targeted therapy and measured chromosomal aneuploidy and cGAS expression levels. Treatment type, aneuploidy, and cGAS expression were correlated with progression-free survival (PFS) in these patients. Those treated with immunotherapy first had significantly better outcomes than those treated with targeted therapy, suggesting immunotherapy should be strongly considered as the first-line therapy for patients bearing BRAF-mutant melanoma. We found that there was no correlation of aneuploidy with outcome while there was some positive correlation of cGAS levels with PFS. Further studies are needed to confirm these findings and to test other potential biomarkers.

Integrated germline and somatic features reveal divergent immune pathways driving ICB response

Immune Checkpoint Blockade (ICB) has revolutionized cancer treatment, however mechanisms determining patient response remain poorly understood. Here we used machine learning to predict ICB response from germline and somatic biomarkers and interpreted the learned model to uncover putative mechanisms driving superior outcomes. Patients with higher T follicular helper infiltrates were robust to defects in the class-I Major Histocompatibility Complex (MHC-I). Further investigation uncovered different ICB responses in MHC-I versus MHC-II neoantigen reliant tumors across patients. Despite similar response rates, MHC-II reliant responses were associated with significantly longer durable clinical benefit (Discovery: Median OS=63.6 vs. 34.5 months P=0.0074; Validation: Median OS=37.5 vs. 33.1 months, P=0.040). Characteristics of the tumor immune microenvironment reflected MHC neoantigen reliance, and analysis of immune checkpoints revealed LAG3 as a potential target in MHC-II but not MHC-I reliant responses. This study highlights the value of interpretable machine learning models in elucidating the biological basis of therapy responses.

Neutrophil-to-Lymphocyte Ratio (NLR) in NSCLC, Gastrointestinal, and Other Solid Tumors: Immunotherapy and Beyond

In the era of immunotherapy, identifying biomarkers of immune system activation has become a high-priority challenge. The blood neutrophil-to-lymphocyte ratio (NLR) has been largely investigated as a biomarker in several cancer types. NLR values have been shown to mirror the tumor-induced inflammatory status and have been demonstrated to be a reliable prognostic tool across stages of disease and therapeutic approaches. When integrated with other biomarkers of response to immunotherapy, such as PD-L1, tumor mutational burden, and tumor-associated immune cells, the NLR may allow to further stratify patients with different likelihoods of deriving a significant clinical benefit. However, despite its accessibility, low cost, and easy interpretation, the NLR is still poorly used as a prognostic tool in daily clinical practice. In this review, we analyze the role of the NLR in defining the relationship between cancer and the immune system, its usefulness in daily clinical practice, and its relationship with other established or emerging biomarkers of immunotherapy outcomes.

Progresses in biomarkers for cancer immunotherapy

Currently, checkpoint inhibitor-based immunotherapy has emerged as prevailing treatment modality for diverse cancers. However, immunotherapy as a first-line therapy has not consistently yielded durable responses. Moreover, the risk of immune-related adverse events increases with combination regimens. Thus, the development of predictive biomarkers is needed to optimize individuals benefit, minimize risk of toxicities, and guide combination approaches. The greatest focus has been on tumor programmed cell death-ligand 1 (PD-L1), microsatellite instability (MSI), and tumor mutational burden (TMB). However, there remains a subject of debate due to thresholds variability and significant heterogeneity. Major unmet challenges in immunotherapy are the discovery and validation of predictive biomarkers. Here, we show the status of tumor PD-L1, MSI, TMB, and emerging data on novel biomarker strategies with oncogenic signaling and epigenetic regulation. Considering the exploration of peripheral and intestinal immunity has served as noninvasive alternative in predicting immunotherapy, this review also summarizes current data in systemic immunity, encompassing solute PD-L1 and TMB, circulating tumor DNA and infiltrating lymphocytes, routine emerging inflammatory markers and cytokines, as well as gut microbiota. This review provides up-to-date information on the evolving field of currently available biomarkers in predicting immunotherapy. Future exploration of novel biomarkers is warranted.

Nanoparticle Delivery of Immunostimulatory Alu RNA for Cancer Immunotherapy

It was recently found that patients with relapsing remitting multiple sclerosis exhibit widespread loss of adenosine-to-inosine (A-to-I) RNA editing, which contributes to the accumulation of immunostimulatory double-stranded Alu RNA in circulating leukocytes and an attendant increase in levels of proinflammatory cytokines (e.g., type I IFNs). A specific Alu RNA (i.e., AluJb RNA) was implicated in activating multiple RNA-sensing pathways and found to be a potent innate immune agonist. Here, we have performed a bioinformatic analysis of A-to-I RNA editing in human melanoma samples and determined that pre-therapy levels of A-to-I RNA editing negatively correlate with survival times, suggesting that an accumulation of endogenous double-stranded Alu RNA might contribute to cancer patient survival. Furthermore, we demonstrated that immunostimulatory Alu RNA can be leveraged pharmacologically for cancer immunotherapy. AluJb RNA was in vitro transcribed and then formulated with endosome-destabilizing polymer nanoparticles to improve intracellular delivery of the RNA and enable activation of RNA-sensing pathways. AluJb RNA/polymer complexes (i.e., Alu-NPs) were engineered to form colloidally stable nanoparticles that exhibited immunostimulatory activity in vitro and in vivo. Finally, the therapeutic potential of Alu-NPs for the treatment of cancer was demonstrated by attenuated tumor growth and prolonged survival in the B16.F10 murine melanoma tumor model. Thus, these data collectively implicate intratumoral Alu RNA as a potentiator of antitumor innate immunity and identify AluJb RNA as a novel nucleic acid immunotherapeutic for cancer.

Significance

Loss of A-to-I editing leads to accumulation of unedited Alu RNAs that activate innate immunity via RNA-sensing pattern recognition receptors. When packaged into endosome-releasing polymer nanoparticles, AluJB RNA becomes highly immunostimulatory and can be used pharmacologically to inhibit tumor growth in mouse melanoma models. These findings identify Alu RNAs as a new class of nucleic acid innate immune agonists for cancer immunotherapy.

Primary tumour category, site of metastasis, and baseline serum S100B and LDH are independent prognostic factors for survival in metastatic melanoma patients treated with anti-PD-1

Background

Prognostic classification of metastatic melanoma patients treated with anti-PD-1 is of great interest to clinicians.

Objective

We aimed to determine the anti-PD-1 treatment related prognostic performance of demographics, clinical and histological prognostic markers and baseline serum S100B and LDH levels in advanced melanoma.

Methods

A total of 200 patients with unresectable metastatic melanoma were included in this retrospective study. 34.5% had stage M1c disease and 11.5% had stage M1d disease at the start of therapy. 30% had pT4b primary melanoma. 55.5% had elevated baseline serum S100B levels and 62.5% had elevated baseline serum LDH levels. We analysed the risk of death using univariate and multivariate Cox proportional-hazards models and the median overall (OS) and progression-free (PFS) survival using the Kaplan-Meier estimator.

Results

The median follow-up time from the start of anti-PD-1 treatment in patients who were alive at the end of the study (N=81) was 37 months (range: 6.1-95.9). The multivariate Cox regression analysis showed that M1c stage (vs. M1a, p=0.005) or M1d stage at the start of therapy (vs. M1a, p=0.001), pT4b category (vs. pT1a, p=0.036), elevated baseline serum S100B levels (vs. normal S100B, p=0.008) and elevated LDH levels (vs. normal LDH, p=0.049) were independently associated with poor survival. The combination of M1d stage, elevated baseline serum S100B and LDH levels and pT4b category was associated with a very high risk of death (HR 4.72 [1.81; 12.33]). In the subgroup of patients with pT4b primary melanoma, the median OS of patients with normal serum S100B levels was 37.25 months [95% CI 11.04; 63.46]), while the median OS of patients with elevated serum S100B levels was 8.00 months [95% CI 3.49; 12.51]) (p<0.001); the median OS of patients with normal serum LDH levels was 41.82 months [95% CI 11.33; 72.32]), while the median OS of patients with elevated serum LDH levels was 12.29 months [95% CI 4.35; 20.23]) (p=0.002).

Conclusion

Our real-world study indicates that the prognostic role of primary melanoma parameters is preserved in anti-PD-1 treated stage IV patients. Furthermore, there seems to be perspective in combining clinical, histological and serum prognostic markers in a prognostic model.

Intratumoral T-cell and B-cell receptor architecture associates with distinct immune tumor microenvironment features and clinical outcomes of anti-PD-1/L1 immunotherapy

BACKGROUND

Effective cooperation between B-cells and T-cells within the tumor microenvironment may lead to the regression of established tumors. B-cells and T-cells can recognize tumor antigens with exquisite specificity via their receptor complexes. Nevertheless, whether a diverse intratumoral B-cells and T-cell receptor (BCR, TCR) repertoire affects the tumor immune microenvironment (TIME) and clinical outcomes in patients treated with immunotherapy is unclear.

METHODS

We extracted information on BCR and TCR repertoire diversity from large clinical datasets and measured the association between immune receptor diversity features, the TIME, and clinical outcomes of patients treated with anti-PD-1/PD-L1 immunotherapy.

RESULTS

In multiple tumor types, an increasingly diverse TCR repertoire was strongly associated with a highly activated TIME, while BCR diversity was more associated with antibody responses but not with the overall B-cell infiltration nor with measures related to intratumoral CD8+T cell activity. Neither TCR nor BCR diversity was independent prognostic biomarkers of survival across multiple cancer types. However, both TCR and BCR diversity improved the performance of predictive models combined with established biomarkers of response to immunotherapy.

CONCLUSION

Overall, these data indicate a currently unexplored immunological role of intratumoral B-cells associated with BCR diversity and antibody responses but independent of classical anticancer T-cells intratumoral activities.

Pathology of Immunotherapy-induced Responses in Cutaneous Melanoma: Current Evidences and Future Perspectives

Over the last years, immune checkpoint inhibitors (ICIs) have demonstrated remarkable anti-tumor activity and beneficial effects in patients with early and advanced melanoma. However, ICIs provide clinical benefit only in a minority of patients due to primary and/or acquired resistance mechanisms. Immunotherapy resistance is a complex phenomenon relying on genetic and epigenetic factors, which ultimately influence the interplay between cancer cells and the tumor microenvironment. Information is accumulating on the cellular and molecular mechanisms underlying the production of resistance and the resulting diminished therapeutic efficacy. In addition, current knowledge on predictors of response and toxicity to immunotherapy and on biomarkers that reliably identify resistant patients is in progress. In this review, we will focus on the tumor microenvironment changes induced by ICIs in melanoma, summarizing the available evidence of clinical trials in the neoadjuvant and metastatic setting. We will also overview the role of potential biomarkers in predicting disease response to ICIs, providing insight into current and future research in this field.

The therapeutic potential of targeting minimal residual disease in melanoma

Background

Cutaneous melanoma is a lethal form of skin cancer with morbidity and mortality rates highest amongst European, North American and Australasian populations. The developments of targeted therapies (TTs) directed at the oncogene BRAF and its downstream mediator MEK, and immune checkpoint inhibitors (ICI), have revolutionized the treatment of metastatic melanoma, improving patient outcomes. However, both TT and ICI have their limitations. Although TTs are associated with high initial response rates, these are typically short‐lived due to resistance. Conversely, although ICIs provide more durable responses, they have lower initial response rates. Due to these distinct yet complementary response profiles, it has been proposed that sequencing ICI with TT could lead to a high frequency of durable responses whilst circumventing the toxicity associated with combined ICI + TT treatment. However, several questions remain unanswered, including the mechanisms underpinning this synergy and the optimal sequencing strategy. The key to determining this is to uncover the biology of each phase of the therapeutic response.

Aims and methods

In this review, we show that melanoma responds to TT and ICI in three phases: early response, minimal residual disease (MRD) and disease progression. We explore the effects of ICI and TT on melanoma cells and the tumour immune microenvironment, with a particular focus on MRD which is predicted to underpin the development of acquired resistance in the third phase of response.

Conclusion

In doing so, we provide a new framework which may inform novel therapeutic approaches for melanoma, including optimal sequencing strategies and agents that target MRD, thereby ultimately improving clinical outcomes for patients.

Roles and mechanisms of tumour-infiltrating B cells in human cancer: a new force in immunotherapy

Immune checkpoint inhibitors (ICIs) targeting PD-1 or PD-L1 have emerged as a revolutionary treatment strategy for human cancer patients. However, as the response rate to ICI therapy varies widely among different types of tumours, we are beginning to gain insight into the mechanisms as well as biomarkers of therapeutic response and resistance. Numerous studies have highlighted the dominant role of cytotoxic T cells in determining the treatment response to ICIs. Empowered by recent technical advances, such as single-cell sequencing, tumour-infiltrating B cells have been identified as a key regulator in several solid tumours by affecting tumour progression and the response to ICIs. In the current review, we summarized recent advances regarding the role and underlying mechanisms of B cells in human cancer and therapy. Some studies have shown that B-cell abundance in cancer is positively associated with favourable clinical outcomes, while others have indicated that they are tumour-promoting, implying that the biological function of B cells is a complex landscape. The molecular mechanisms involved multiple aspects of the functions of B cells, including the activation of CD8+ T cells, the secretion of antibodies and cytokines, and the facilitation of the antigen presentation process. In addition, other crucial mechanisms, such as the functions of regulatory B cells (Bregs) and plasma cells, are discussed. Here, by summarizing the advances and dilemmas of recent studies, we depicted the current landscape of B cells in cancers and paved the way for future research in this field.

Combinatorial biomarker for predicting outcomes to anti-PD-1 therapy in patients with metastatic clear cell renal cell carcinoma

With a rapidly developing immunotherapeutic landscape for patients with metastatic clear cell renal cell carcinoma, biomarkers of efficacy are highly desirable to guide treatment strategy. Hematoxylin and eosin (H&E)-stained slides are inexpensive and widely available in pathology laboratories, including in resource-poor settings. Here, H&E scoring of tumor-infiltrating immune cells (TILplus) in pre-treatment tumor specimens using light microscopy is associated with improved overall survival (OS) in three independent cohorts of patients receiving immune checkpoint blockade. Necrosis score alone does not associate with OS; however, necrosis modifies the predictive effect of TILplus, a finding that has broad translational relevance for tissue-based biomarker development. PBRM1 mutational status is combined with H&E scores to further refine outcome predictions (OS, p = 0.007, and objective response, p = 0.04). These findings bring H&E assessment to the fore for biomarker development in future prospective, randomized trials, and emerging multi-omics classifiers.

Persistent mutation burden drives sustained anti-tumor immune responses

Tumor mutation burden is an imperfect proxy of tumor foreignness and has therefore failed to consistently demonstrate clinical utility in predicting responses in the context of immunotherapy. We evaluated mutations in regions of the genome that are unlikely to undergo loss in a pan-cancer analysis across 31 tumor types (n = 9,242) and eight immunotherapy-treated cohorts of patients with non-small-cell lung cancer, melanoma, mesothelioma, and head and neck cancer (n = 524). We discovered that mutations in single-copy regions and those present in multiple copies per cell constitute a persistent tumor mutation burden (pTMB) which is linked with therapeutic response to immune checkpoint blockade. Persistent mutations were retained in the context of tumor evolution under selective pressure of immunotherapy and tumors with a high pTMB content were characterized by a more inflamed tumor microenvironment. pTMB imposes an evolutionary bottleneck that cancer cells cannot overcome and may thus drive sustained immunologic tumor control in the context of immunotherapy.

MHC II immunogenicity shapes the neoepitope landscape in human tumors

Despite advances in predicting physical peptide-major histocompatibility complex I (pMHC I) binding, it remains challenging to identify functionally immunogenic neoepitopes, especially for MHC II. By using the results of >36,000 immunogenicity assay, we developed a method to identify pMHC whose structural alignment facilitates T cell reaction. Our method predicted neoepitopes for MHC II and MHC I that were responsive to checkpoint blockade when applied to >1,200 samples of various tumor types. To investigate selection by spontaneous immunity at the single epitope level, we analyzed the frequency spectrum of >25 million mutations in >9,000 treatment-naive tumors with >100 immune phenotypes. MHC II immunogenicity specifically lowered variant frequencies in tumors under high immune pressure, particularly with high TCR clonality and MHC II expression. A similar trend was shown for MHC I neoepitopes, but only in particular tissue types. In summary, we report immune selection imposed by MHC II-restricted natural or therapeutic T cell reactivity.

Thiopurine 6TG treatment increases tumor immunogenicity and response to immune checkpoint blockade

Immune-checkpoint inhibitors (ICI) are highly effective in reinvigorating T cells to attack cancer. Nevertheless, a large subset of patients fails to benefit from ICI, partly due to lack of the cancer neoepitopes necessary to trigger an immune response. In this study, we used the thiopurine 6-thioguanine (6TG) to induce random mutations and thus increase the level of neoepitopes presented by tumor cells. Thiopurines are prodrugs which are converted into thioguanine nucleotides that are incorporated into DNA (DNA-TG), where they can induce mutation through single nucleotide mismatching. In a pre-clinical mouse model of a mutation-low melanoma cell line, we demonstrated that 6TG induced clinical-grade DNA-TG integration resulting in an improved tumor control that was strongly T cell dependent. 6TG exposure increased the tumor mutational burden, without affecting tumor cell proliferation and cell death. Moreover, 6TG treatment re-shaped the tumor microenvironment by increasing T and NK immune cells, making the tumors more responsive to immune-checkpoint blockade. We further validated that 6TG exposure improved tumor control in additional mouse models of melanoma. These findings have paved the way for a phase I/II clinical trial that explores whether treatment with thiopurines can increase the proportion of otherwise treatment-resistant cancer patients who may benefit from ICI therapy (NCT05276284).

Translating the evolving molecular landscape of tumors to biomarkers of response for cancer immunotherapy

Immune checkpoint inhibitors (ICIs) have revolutionized cancer therapeutics, triggering studies to understand the molecular and cellular wiring of response and resistance. Our increased understanding of the underlying biology of response to ICI has enabled the investigation of tumor-intrinsic and -extrinsic features that may predict therapeutic outcomes. In parallel, liquid biopsy measurements of circulating tumor DNA (ctDNA) can be used to assess real-time molecular responses and guide clinical decisions during ICI. The combination of these approaches provides a deeper understanding of cancer biology, immunoediting, and evolution during ICI and promise to extend the utility of immunotherapies for patients with cancer.

Systematic assessment and optimizing algorithm of tumor mutational burden calculation and their implications in clinical decision-making

Tumor mutation burden (TMB) has been validated as a biomarker to predict the response of immune checkpoint inhibitors (ICIs) treatment in various cancers. However, the effects of different sequencing platforms, cancer types, and calculation algorithms on TMB as well as its cut-off value for predicting immunotherapy efficacy in the East Asian population still need to be further investigated. In this study, the data of 4126 samples generated by targeted panel sequencing or whole-exome sequencing (WES) in different platforms and public sequencing data from 3680 samples that contained targeted panel sequencing, WES and whole-genome sequencing (WGS) were obtained. The impact of different sequencing platforms and methods on TMB calculation was assessed. No significant bias was found in TMB calculated by different platforms. However, TMB calculated from WGS was significantly lower than those calculated from targeted panel sequencing and WES. The distribution of TMB at different sequencing depths and tumor purity were analyzed. There was no significant difference in the distribution of TMB when the sequencing depth was greater than 500, the tumor purity estimated by hematoxylin-eosin (HE) staining was between 0.1-1.0 or estimated by next-generation sequencing (NGS) was greater than 0.4. In addition, the somatic-germline-zygosity (SGZ) algorithm was optimized to calculate TMB from tumor-only sequencing samples in the East Asian population. The correlation coefficient of TMB calculated with the optimized SGZ algorithm and paired normal-tumor sequencing is 0.951. Furthermore, the optimal cut-off value of TMB in East Asian lung cancer patients treated with ICIs was determined to be 7 mut/Mb instead of 10 mut/Mb through the ROC curve and Log-rank analysis in the training cohort and validated in the test cohort. Patients with TMB ≥ 7 mut/Mb had better outcomes than patients with TMB<7 mut/Mb. In conclusion, this study systematically analyzed the factors that influenced the TMB calculation and optimized the SGZ algorithm to calculate TMB from tumor-only sequencing samples in the East Asian population. More importantly, the cut-off value of TMB for predicting immunotherapy efficacy was determined to be 7 mut/Mb instead of 10 mut/Mb in East Asian lung cancer patients, which can help in clinical decision-making.

Genomic landscape of the immunogenicity regulation in skin melanomas with diverse tumor mutation burden

Skin melanoma cells are tightly interconnected with their tumor microenvironment (TME), which influences their initiation, progression, and sensitivity/resistance to therapeutic interventions. An immune-active TME favors patient response to immune checkpoint inhibition (ICI), but not all patients respond to therapy. Here, we assessed differential gene expression in primary and metastatic tumors from the TCGA-SKCM dataset, compared to normal skin samples from the GTEx project and validated key findings across 4 independent GEO datasets, as well as using immunohistochemistry in independent patient cohorts. We focused our attention on examining the expression of various immune receptors, immune-cell fractions, immune-related signatures and mutational signatures across cutaneous melanomas with diverse tumor mutation burdens (TMB). Globally, the expression of most immunoreceptors correlated with patient survival, but did not differ between TMBhigh and TMBlow tumors. Melanomas were enriched in "naive T-cell", "effector memory T-cell", "exhausted T-cell", "resting Treg T-cell" and "Th1-like" signatures, irrespective of their BRAF, NF1 or RAS mutational status. Somatic mutations in IDO1 and HLA-DRA were frequent and could be involved in hindering patient response to ICI therapies. We finally analyzed transcriptome profiles of ICI-treated patients and associated their response with high levels of IFNγ, Merck18, CD274, CD8, and low levels of myeloid-derived suppressor cells (MDSCs), cancer-associated fibroblasts (CAFs) and M2 macrophages, irrespective of their TMB status. Overall, our findings highlight the importance of pre-existing T-cell immunity in ICI therapeutic outcomes in skin melanoma and suggest that TMBlow patients could also benefit from such therapies.

Changes in the Immune Cell Repertoire for the Treatment of Malignant Melanoma

Immune checkpoint inhibitors (ICIs) have been used for the treatment of various types of cancers, including malignant melanoma. Mechanistic exploration of tumor immune responses is essential to improve the therapeutic efficacy of ICIs. Since tumor immune responses are based on antigen-specific immune responses, investigators have focused on T cell receptors (TCRs) and have analyzed changes in the TCR repertoire. The proliferation of T cell clones against tumor antigens is detected in patients who respond to treatment with ICIs. The proliferation of these T cell clones is observed within tumors as well as in the peripheral blood. Clonal proliferation has been detected not only in CD8-positive T cells but also in CD4-positive T cells, resident memory T cells, and B cells. Moreover, changes in the repertoire at an early stage of treatment seem to be useful for predicting the therapeutic efficacy of ICIs. Further analyses of the repertoire of immune cells are desirable to improve and predict the therapeutic efficacy of ICIs.

Multi-omics analysis: Paving the path toward achieving precision medicine in cancer treatment and immuno-oncology

The acceleration of large-scale sequencing and the progress in high-throughput computational analyses, defined as omics, was a hallmark for the comprehension of the biological processes in human health and diseases. In cancerology, the omics approach, initiated by genomics and transcriptomics studies, has revealed an incredible complexity with unsuspected molecular diversity within a same tumor type as well as spatial and temporal heterogeneity of tumors. The integration of multiple biological layers of omics studies brought oncology to a new paradigm, from tumor site classification to pan-cancer molecular classification, offering new therapeutic opportunities for precision medicine. In this review, we will provide a comprehensive overview of the latest innovations for multi-omics integration in oncology and summarize the largest multi-omics dataset available for adult and pediatric cancers. We will present multi-omics techniques for characterizing cancer biology and show how multi-omics data can be combined with clinical data for the identification of prognostic and treatment-specific biomarkers, opening the way to personalized therapy. To conclude, we will detail the newest strategies for dissecting the tumor immune environment and host–tumor interaction. We will explore the advances in immunomics and microbiomics for biomarker identification to guide therapeutic decision in immuno-oncology.

Causes, consequences and clinical significance of aneuploidy across melanoma subtypes

Aneuploidy, the state of the cell in which the number of whole chromosomes or chromosome arms becomes imbalanced, has been recognized as playing a pivotal role in tumor evolution for over 100 years. In melanoma, the extent of aneuploidy, as well as the chromosomal regions that are affected differ across subtypes, indicative of distinct drivers of disease. Multiple studies have suggested a role for aneuploidy in diagnosis and prognosis of melanomas, as well as in the context of immunotherapy response. A number of key constituents of the cell cycle have been implicated in aneuploidy acquisition in melanoma, including several driver mutations. Here, we review the state of the art on aneuploidy in different melanoma subtypes, discuss the potential drivers, mechanisms underlying aneuploidy acquisition as well as its value in patient diagnosis, prognosis and response to immunotherapy treatment.

Deep learning reveals predictive sequence concepts within immune repertoires to immunotherapy

T cell receptor (TCR) sequencing has been used to characterize the immune response to cancer. However, most analyses have been restricted to quantitative measures such as clonality that do not leverage the complementarity-determining region 3 (CDR3) sequence. We use DeepTCR, a framework of deep learning algorithms, to reveal sequence concepts that are predictive of response to immunotherapy. We demonstrate that DeepTCR can predict response and use the model to infer the antigenic specificities of the predictive signature and their unique dynamics during therapy. The predictive signature of nonresponse is associated with high frequencies of TCRs predicted to recognize tumor-specific antigens, and these tumor-specific TCRs undergo a higher degree of dynamic changes on therapy in nonresponders versus responders. These results are consistent with a biological model where the hallmark of nonresponders is an accumulation of tumor-specific T cells that undergo turnover on therapy, possibly because of the dysfunctional state of these T cells in nonresponders.

HLA class II immunogenic mutation burden predicts response to immune checkpoint blockade

BACKGROUND

Whereas human leukocyte antigen (HLA) class I mutation-associated neoantigen burden has been linked with response to immune checkpoint blockade (ICB), the role of HLA class II-restricted neoantigens in clinical responses to ICB is less studied. We used computational approaches to assess HLA class II immunogenic mutation (IMM) burden in patients with melanoma and lung cancer treated with ICB.

PATIENTS AND METHODS

We analyzed whole-exome sequence data from four cohorts of ICB-treated patients with melanoma (n = 110) and non-small-cell lung cancer (NSCLC) (n = 123). MHCnuggets, a neural network-based model, was applied to estimate HLA class II IMM burdens and cellular fractions of IMMs were calculated to assess mutation clonality. We evaluated the combined impact of HLA class II germline genetic variation and class II IMM burden on clinical outcomes. Correlations between HLA class II IMM burden and density of tumor-infiltrating lymphocytes were computed from expression data.

RESULTS

Responding tumors harbored a significantly higher HLA class II IMM burden for both melanoma and NSCLC (P ≤ 9.6e-3). HLA class II IMM burden was correlated with longer survival, particularly in the NSCLC cohort and in the context of low intratumoral IMM heterogeneity (P < 0.001). HLA class I and II IMM landscapes were largely distinct suggesting a complementary role for class II IMMs in tumor rejection. A higher HLA class II IMM burden was associated with CD4+ T-cell infiltration and programmed death-ligand 1 expression. Transcriptomic analyses revealed an inflamed tumor microenvironment for tumors harboring a high HLA class II IMM burden.

CONCLUSIONS

HLA class II IMM burden identified patients with NSCLC and melanoma that attained longer survival after ICB treatment. Our findings suggest that HLA class II IMMs may impact responses to ICB in a manner that is distinct and complementary to HLA class I-mediated responses.

Melanoma: An immunotherapy journey from bench to bedside

Melanoma gave science a window into the role immune evasion plays in the development of malignancy. The entire spectrum of immune focused anti-cancer therapies has been subjected to clinical trials in this disease, with limited success until the immune checkpoint blockade era. That revolution launched first in melanoma, heralded a landscape change throughout cancer that continues to reverberate today.

Landscape of helper and regulatory antitumour CD4+ T cells in melanoma

Within the tumour microenvironment, CD4+ T cells can promote or suppress antitumour responses through the recognition of antigens presented by human leukocyte antigen (HLA) class II molecules1,2, but how cancers co-opt these physiologic processes to achieve immune evasion remains incompletely understood. Here we performed in-depth analysis of the phenotype and tumour specificity of CD4+ T cells infiltrating human melanoma specimens, finding that exhausted cytotoxic CD4+ T cells could be directly induced by melanoma cells through recognition of HLA class II-restricted neoantigens, and also HLA class I-restricted tumour-associated antigens. CD4+ T regulatory (TReg) cells could be indirectly elicited through presentation of tumour antigens via antigen-presenting cells. Notably, numerous tumour-reactive CD4+ TReg clones were stimulated directly by HLA class II-positive melanoma and demonstrated specificity for melanoma neoantigens. This phenomenon was observed in the presence of an extremely high tumour neoantigen load, which we confirmed to be associated with HLA class II positivity through the analysis of 116 melanoma specimens. Our data reveal the landscape of infiltrating CD4+ T cells in melanoma and point to the presentation of HLA class II-restricted neoantigens and direct engagement of immunosuppressive CD4+ TReg cells as a mechanism of immune evasion that is favoured in HLA class II-positive melanoma.

Combined tumor and immune signals from genomes or transcriptomes predict outcomes of checkpoint inhibition in melanoma

Immune checkpoint blockade (CPB) improves melanoma outcomes, but many patients still do not respond. Tumor mutational burden (TMB) and tumor-infiltrating T cells are associated with response, and integrative models improve survival prediction. However, integrating immune/tumor-intrinsic features using data from a single assay (DNA/RNA) remains underexplored. Here, we analyze whole-exome and bulk RNA sequencing of tumors from new and published cohorts of 189 and 178 patients with melanoma receiving CPB, respectively. Using DNA, we calculate T cell and B cell burdens (TCB/BCB) from rearranged TCR/Ig sequences and find that patients with TMBhigh and TCBhigh or BCBhigh have improved outcomes compared to other patients. By combining pairs of immune- and tumor-expressed genes, we identify three gene pairs associated with response and survival, which validate in independent cohorts. The top model includes lymphocyte-expressed MAP4K1 and tumor-expressed TBX3. Overall, RNA or DNA-based models combining immune and tumor measures improve predictions of melanoma CPB outcomes.

Multiomic profiling of checkpoint inhibitor-treated melanoma: Identifying predictors of response and resistance, and markers of biological discordance

We concurrently examine the whole genome, transcriptome, methylome, and immune cell infiltrates in baseline tumors from 77 patients with advanced cutaneous melanoma treated with anti-PD-1 with or without anti-CTLA-4. We show that high tumor mutation burden (TMB), neoantigen load, expression of IFNγ-related genes, programmed death ligand expression, low PSMB8 methylation (therefore high expression), and T cells in the tumor microenvironment are associated with response to immunotherapy. No specific mutation correlates with therapy response. A multivariable model combining the TMB and IFNγ-related gene expression robustly predicts response (89% sensitivity, 53% specificity, area under the curve [AUC], 0.84); tumors with high TMB and a high IFNγ signature show the best response to immunotherapy. This model validates in an independent cohort (80% sensitivity, 59% specificity, AUC, 0.79). Except for a JAK3 loss-of-function mutation, for patients who did not respond as predicted there is no obvious biological mechanism that clearly explained their outlier status, consistent with intratumor and intertumor heterogeneity in response to immunotherapy.

Durvalumab with platinum-pemetrexed for unresectable pleural mesothelioma: survival, genomic and immunologic analyses from the phase 2 PrE0505 trial

Mesothelioma is a rare and fatal cancer with limited therapeutic options until the recent approval of combination immune checkpoint blockade. Here we report the results of the phase 2 PrE0505 trial (NCT02899195) of the anti-PD-L1 antibody durvalumab plus platinum-pemetrexed chemotherapy for 55 patients with previously untreated, unresectable pleural mesothelioma. The primary endpoint was overall survival compared to historical control with cisplatin and pemetrexed chemotherapy; secondary and exploratory endpoints included safety, progression-free survival and biomarkers of response. The combination of durvalumab with chemotherapy met the pre-specified primary endpoint, reaching a median survival of 20.4 months versus 12.1 months with historical control. Treatment-emergent adverse events were consistent with known side effects of chemotherapy, and all adverse events due to immunotherapy were grade 2 or lower. Integrated genomic and immune cell repertoire analyses revealed that a higher immunogenic mutation burden coupled with a more diverse T cell repertoire was linked to favorable clinical outcome. Structural genome-wide analyses showed a higher degree of genomic instability in responding tumors of epithelioid histology. Patients with germline alterations in cancer predisposing genes, especially those involved in DNA repair, were more likely to achieve long-term survival. Our findings indicate that concurrent durvalumab with platinum-based chemotherapy has promising clinical activity and that responses are driven by the complex genomic background of malignant pleural mesothelioma.

In a phase 2 trial, the combination of chemotherapy with durvalumab, an anti-PD-L1 antibody, exhibited promising clinical activity in patients with previously untreated, unresectable mesothelioma, with additional analyses providing insights into genomic and immunologic features potentially associated with response.

Soluble Biomarkers with Prognostic and Predictive Value in Advanced Non-Small Cell Lung Cancer Treated with Immunotherapy

Simple Summary

Immunotherapy, most notably immune checkpoint inhibitors (ICIs), has revolutionized the treatment of advanced non-small cell lung cancer (NSCLC). Although some patients respond well to ICIs, many patients do not benefit from ICIs, leading to disease progression and/or immune-related adverse events. Biological markers can help to improve patient selection. However, currently available markers such as PD-1 and its ligand (PD-L1) have important limitations. For this reason, new biomarkers obtained by non-invasive methods are urgently needed. In the present review, we describe recent advances in the development of novel soluble biological markers (e.g., circulating immune cells, TMB, circulating tumor cells, circulating tumor DNA, soluble factor PD-L1, tumor necrosis factor, etc.) for patients with NSCLC treated with immunotherapy.

Abstract

Numerous targeted therapies have been evaluated for the treatment of non-small cell lung cancer (NSCLC). To date, however, only a few agents have shown promising results. Recent advances in cancer immunotherapy, most notably immune checkpoint inhibitors (ICI), have transformed the treatment scenario for these patients. Although some patients respond well to ICIs, many patients do not benefit from ICIs, leading to disease progression and/or immune-related adverse events. New biomarkers capable of reliably predicting response to ICIs are urgently needed to improve patient selection. Currently available biomarkers—including programmed death protein 1 (PD-1) and its ligand (PD-L1), and tumor mutational burden (TMB)—have major limitations. At present, no well-validated, reliable biomarkers are available. Ideally, these biomarkers would be obtained through less invasive methods such as plasma determination or liquid biopsy. In the present review, we describe recent advances in the development of novel soluble biomarkers (e.g., circulating immune cells, TMB, circulating tumor cells, circulating tumor DNA, soluble factor PD-L1, tumor necrosis factor, etc.) for patients with NSCLC treated with ICIs. We also describe the potential use of these biomarkers as prognostic indicators of treatment response and toxicity.

Neoantigen Controversies

Next-generation sequencing technologies have revolutionized our ability to catalog the landscape of somatic mutations in tumor genomes. These mutations can sometimes create so-called neoantigens, which allow the immune system to detect and eliminate tumor cells. However, efforts that stimulate the immune system to eliminate tumors based on their molecular differences have had less success than has been hoped for, and there are conflicting reports about the role of neoantigens in the success of this approach. Here we review some of the conflicting evidence in the literature and highlight key aspects of the tumor-immune interface that are emerging as major determinants of whether mutation-derived neoantigens will contribute to an immunotherapy response. Accounting for these factors is expected to improve success rates of future immunotherapy approaches.

Enhanced Antitumor Response to Immune Checkpoint Blockade Exerted by Cisplatin-Induced Mutagenesis in a Murine Melanoma Model

Sequencing data from different types of cancers including melanomas demonstrate that tumors with high mutational loads are more likely to respond to immune checkpoint blockade (ICB) therapies. We have previously shown that low-dose intratumoral injection of the chemotherapeutic DNA damaging drug cisplatin activates intrinsic mutagenic DNA damage tolerance pathway, and when combined with ICB regimen leads to tumor regression in the mouse YUMM1.7 melanoma model. We now report that tumors generated with an in vitro cisplatin-mutagenized YUMM1.7 clone (YUMM1.7-CM) regress in response to ICB, while an identical ICB regimen alone fails to suppress growth of tumors generated with the parental YUMM1.7 cells. Regressing YUMM1.7-CM tumors show greater infiltration of CD8 T lymphocytes, higher granzyme B expression, and higher tumoral cell death. Similarly, ex-vivo, immune cells isolated from YUMM1.7-CM tumors-draining lymph nodes (TDLNs) co-incubated with cultured YUMM1.7-CM cells, eliminate the tumor cells more efficiently than immune cells isolated from TDLNs of YUMM1.7 tumor-bearing mice. Collectively, our findings show that in vitro induced cisplatin mutations potentiate the antitumor immune response and ICB efficacy, akin to tumor regression achieved in the parental YUMM1.7 model by ICB administered in conjunction with intratumoral cisplatin injection. Hence, our data uphold the role of tumoral mutation burden in improving immune surveillance and response to ICB, suggesting a path for expanding the range of patients benefiting from ICB therapy.

The Comprehensive "Omics" Approach from Metabolomics to Advanced Omics for Development of Immune Checkpoint Inhibitors: Potential Strategies for Next Generation of Cancer Immunotherapy

In the past decade, immunotherapies have been emerging as an effective way to treat cancer. Among several categories of immunotherapies, immune checkpoint inhibitors (ICIs) are the most well-known and widely used options for cancer treatment. Although several studies continue, this treatment option has yet to be developed into a precise application in the clinical setting. Recently, omics as a high-throughput technique for understanding the genome, transcriptome, proteome, and metabolome has revolutionized medical research and led to integrative interpretation to advance our understanding of biological systems. Advanced omics techniques, such as multi-omics, single-cell omics, and typical omics approaches, have been adopted to investigate various cancer immunotherapies. In this review, we highlight metabolomic studies regarding the development of ICIs involved in the discovery of targets or mechanisms of action and assessment of clinical outcomes, including drug response and resistance and propose biomarkers. Furthermore, we also discuss the genomics, proteomics, and advanced omics studies providing insights and comprehensive or novel approaches for ICI development. The overview of ICI studies suggests potential strategies for the development of other cancer immunotherapies using omics techniques in future studies.

[Predictive diagnostics for checkpoint inhibitors]

Checkpoint inhibitors have revolutionized oncological treatment in many cancers and added a new immuno-oncological treatment pillar to the medicinal arsenal of conventional and molecularly targeted therapies. In monotherapy and in combination therapies, however, not all patients respond equally well, even in generally responsive tumor entities. Therefore, since the introduction of these therapies, a major focus has been the research on and implementation of predictive markers for patient selection. The first established biomarker, the expression of the target molecule PD-L1, has found its way into routine diagnostics in a large number of unfortunately very divergent diagnostic constellations in multiple entities. In addition, some molecular predictors, including the measurement of microsatellite instability and tumor mutational burden, have also been suggested and in some cases are already implemented into routine diagnostics. Additional molecular parameters have been proposed but most of them have not yet found their way into routine patient care. This review article discusses the current status and recent developments in the field of diagnostic response predictors in the context of an immune checkpoint blockade.

Involvement of mutant and wild-type CYSLTR2 in the development and progression of uveal nevi and melanoma

Background

Activating Gα_q signalling mutations are considered an early event in the development of uveal melanoma. Whereas most tumours harbour a mutation in GNAQ or GNA11, CYSLTR2 (encoding G-protein coupled receptor CysLT₂R) forms a rare alternative. The role of wild-type CysLT₂R in uveal melanoma remains unknown.

Methods

We performed a digital PCR-based molecular analysis of benign choroidal nevi and primary uveal melanomas. Publicly available bulk and single cell sequencing data were mined to further study mutant and wild-type CYSLTR2 in primary and metastatic uveal melanoma.

Results

1/16 nevi and 2/120 melanomas carried the CYSLTR2 mutation. The mutation was found in a subpopulation of the nevus, while being clonal in both melanomas. In the melanomas, secondary, subclonal CYSLTR2 alterations shifted the allelic balance towards the mutant. The resulting genetic heterogeneity was confirmed in distinct areas of both tumours. At the RNA level, further silencing of wild-type and preferential expression of mutant CYSLTR2 was identified, which was also observed in two CYSLTR2 mutant primary melanomas and one metastatic lesion from other cohorts. In CYSLTR2 wild-type melanomas, high expression of CYSLTR2 correlated to tumour inflammation, but expression originated from melanoma cells specifically.

Conclusions

Our findings suggest that CYSLTR2 is involved in both early and late development of uveal melanoma. Whereas the CYSLTR2 p.L129Q mutation is likely to be the initiating oncogenic event, various mechanisms further increase the mutant allele abundance during tumour progression. This makes mutant CysLT₂R an attractive therapeutic target in uveal melanoma.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-07865-x.