Meta-analysis of tumor- and T cell-intrinsic mechanisms of sensitization to checkpoint inhibition

Interactions of Indoleamine 2,3-dioxygenase-expressing LAMP3+ dendritic cells with CD4+ regulatory T cells and CD8+ exhausted T cells: synergistically remodeling of the immunosuppressive microenvironment in cervical cancer and therapeutic implications

BACKGROUND

Cervical cancer (CC) is the fourth most common cancer in women worldwide. Although immunotherapy has been applied in clinical practice, its therapeutic efficacy remains far from satisfactory, necessitating further investigation of the mechanism of CC immune remodeling and exploration of novel treatment targets. This study aimed to investigate the mechanism of CC immune remodeling and explore potential therapeutic targets.

METHODS

We conducted single-cell RNA sequencing on a total of 17 clinical specimens, including normal cervical tissues, high-grade squamous intraepithelial lesions, and CC tissues. To validate our findings, we conducted multicolor immunohistochemical staining of CC tissues and constructed a subcutaneous tumorigenesis model in C57BL/6 mice using murine CC cell lines (TC1) to evaluate the effectiveness of combination therapy involving indoleamine 2,3-dioxygenase 1 (IDO1) inhibition and immune checkpoint blockade (ICB). We used the unpaired two-tailed Student's t-test, Mann-Whitney test, or Kruskal-Wallis test to compare continuous data between two groups and one-way ANOVA with Tukey's post hoc test to compare data between multiple groups.

RESULTS

Malignant cervical epithelial cells did not manifest noticeable signs of tumor escape, whereas lysosomal-associated membrane protein 3-positive (LAMP3+ ) dendritic cells (DCs) in a mature state with immunoregulatory roles were found to express IDO1 and affect tryptophan metabolism. These cells interacted with both tumor-reactive exhausted CD8+ T cells and CD4+ regulatory T cells, synergistically forming a vicious immunosuppressive cycle and mediating CC immune escape. Further validation through multicolor immunohistochemical staining showed co-localization of neoantigen-reactive T cells (CD3+ , CD4+ /CD8+ , and PD-1+ ) and LAMP3+ DCs (CD80+ and PD-L1+ ). Additionally, a combination of the IDO1 inhibitor with an ICB agent significantly reduced tumor volume in the mouse model of CC compared with an ICB agent alone.

CONCLUSIONS

Our study suggested that a combination treatment consisting of targeting IDO1 and ICB agent could improve the therapeutic efficacy of current CC immunotherapies. Additionally, our results provided crucial insights for designing drugs and conducting future clinical trials for CC.

Biomarker-Driven Personalization of Neoadjuvant Immunotherapy in Melanoma

The introduction of immunotherapy has ushered in a new era of anticancer therapy for many cancer types including melanoma. Given the increasing development of novel compounds and combinations and the investigation in earlier disease stages, the need grows for biomarker-based treatment personalization. Stage III melanoma is one of the front-runners in the neoadjuvant immunotherapy field, facilitating quick biomarker identification by its immunogenic capacity, homogeneous patient population, and reliable efficacy readout. In this review, we discuss potential biomarkers for response prediction to neoadjuvant immunotherapy, and how the neoadjuvant melanoma platform could pave the way for biomarker identification in other tumor types.

SIGNIFICANCE

In accordance with the increasing rate of therapy development, the need for biomarker-driven personalized treatments grows. The current landscape of neoadjuvant treatment and biomarker development in stage III melanoma can function as a poster child for these personalized treatments in other tumors, assisting in the development of new biomarker-based neoadjuvant trials. This will contribute to personalized benefit-risk predictions to identify the most beneficial treatment for each patient.

Prognostic Markers within the Tumour Microenvironment in Classical Hodgkin Lymphoma

Classical Hodgkin lymphoma (cHL) accounts for 0.4% of all new cancer cases globally. Despite high cure rates with standard treatment, approximately 15% of patients still experience relapsed or refractory (RR) disease, and many of these eventually die from lymphoma-related causes. Exciting new targeted agents such as anti-PD-1 agents and brentuximab vedotin have changed the therapeutic paradigm beyond chemotherapy and radiotherapy alone. Advances in understanding of the molecular biology are providing insights in the context of novel therapies. The signature histology of cHL requires the presence of scant malignant Hodgkin Reed-Sternberg cells (HRSCs) surrounded by a complex immune-rich tumour microenvironment (TME). The TME cellular composition strongly influences outcomes, yet knowledge of the precise characteristics of TME cells and their interactions with HRSCs is evolving. Novel high-throughput technologies and single-cell sequencing allow deeper analyses of the TME and mechanisms elicited by HRSCs to propagate growth and avoid immune response. In this review, we explore the evolution of knowledge on the prognostic role of immune cells within the TME and provide an up-to-date overview of emerging prognostic data on cHL from new technologies that are starting to unwind the complexity of the cHL TME and provide translational insights into how to improve therapy in the clinic.

Single-cell morphological and topological atlas reveals the ecosystem diversity of human breast cancer

Digital pathology allows computerized analysis of tumor ecosystem using whole slide images (WSIs). Here, we present single-cell morphological and topological profiling (sc-MTOP) to characterize tumor ecosystem by extracting the features of nuclear morphology and intercellular spatial relationship for individual cells. We construct a single-cell atlas comprising 410 million cells from 637 breast cancer WSIs and dissect the phenotypic diversity within tumor, inflammatory and stroma cells respectively. Spatially-resolved analysis identifies recurrent micro-ecological modules representing locoregional multicellular structures and reveals four breast cancer ecotypes correlating with distinct molecular features and patient prognosis. Further analysis with multiomics data uncovers clinically relevant ecosystem features. High abundance of locally-aggregated inflammatory cells indicates immune-activated tumor microenvironment and favorable immunotherapy response in triple-negative breast cancers. Morphological intratumor heterogeneity of tumor nuclei correlates with cell cycle pathway activation and CDK inhibitors responsiveness in hormone receptor-positive cases. sc-MTOP enables using WSIs to characterize tumor ecosystems at the single-cell level.

Heterozygote advantage at HLA class I and II loci and reduced risk of colorectal cancer

Objective

Reduced diversity at Human Leukocyte Antigen (HLA) loci may adversely affect the host's ability to recognize tumor neoantigens and subsequently increase disease burden. We hypothesized that increased heterozygosity at HLA loci is associated with a reduced risk of developing colorectal cancer (CRC).

Methods

We imputed HLA class I and II four-digit alleles using genotype data from a population-based study of 5,406 cases and 4,635 controls from the Molecular Epidemiology of Colorectal Cancer Study (MECC). Heterozygosity at each HLA locus and the number of heterozygous genotypes at HLA class -I (A, B, and C) and HLA class -II loci (DQB1, DRB1, and DPB1) were quantified. Logistic regression analysis was used to estimate the risk of CRC associated with HLA heterozygosity. Individuals with homozygous genotypes for all loci served as the reference category, and the analyses were adjusted for sex, age, genotyping platform, and ancestry. Further, we investigated associations between HLA diversity and tumor-associated T cell repertoire features, as measured by tumor infiltrating lymphocytes (TILs; N=2,839) and immunosequencing (N=2,357).

Results

Individuals with all heterozygous genotypes at all three class I genes had a reduced odds of CRC (OR: 0.74; 95% CI: 0.56-0.97, p= 0.031). A similar association was observed for class II loci, with an OR of 0.75 (95% CI: 0.60-0.95, p= 0.016). For class-I and class-II combined, individuals with all heterozygous genotypes had significantly lower odds of developing CRC (OR: 0.66, 95% CI: 0.49-0.87, p= 0.004) than those with 0 or one heterozygous genotype. HLA class I and/or II diversity was associated with higher T cell receptor (TCR) abundance and lower TCR clonality, but results were not statistically significant.

Conclusion

Our findings support a heterozygote advantage for the HLA class-I and -II loci, indicating an important role for HLA genetic variability in the etiology of CRC.

Multi-omics indicators of long-term survival benefits after immune checkpoint inhibitor therapy

Molecular indicators of long-term survival (LTS) in response to immune-checkpoint inhibitor (ICI) treatment have the potential to provide both mechanistic and therapeutic insights. In this study, we construct predictive models of LTS following ICI therapy based on data from 158 clinical trials involving 21,023 patients of 25 cancer types with available 1-year overall survival (OS) rates. We present evidence for the use of 1-year OS rate as a surrogate for LTS. Based on these and corresponding TCGA multi-omics data, total neoantigen, metabolism score, CD8+ T cell, and MHC_score were identified as predictive biomarkers. These were integrated into a Gaussian process regression model that estimates "long-term survival predictive score of immunotherapy" (iLSPS). We found that iLSPS outperformed the predictive capabilities of individual biomarkers and successfully predicted LTS of patient groups with melanoma and lung cancer. Our study explores the feasibility of modeling LTS based on multi-omics indicators and machine-learning methods.

An update on methods for detection of prognostic and predictive biomarkers in melanoma

The approval of immunotherapy for stage II-IV melanoma has underscored the need for improved immune-based predictive and prognostic biomarkers. For resectable stage II-III patients, adjuvant immunotherapy has proven clinical benefit, yet many patients experience significant adverse events and may not require therapy. In the metastatic setting, single agent immunotherapy cures many patients but, in some cases, more intensive combination therapies against specific molecular targets are required. Therefore, the establishment of additional biomarkers to determine a patient's disease outcome (i.e., prognostic) or response to treatment (i.e., predictive) is of utmost importance. Multiple methods ranging from gene expression profiling of bulk tissue, to spatial transcriptomics of single cells and artificial intelligence-based image analysis have been utilized to better characterize the immune microenvironment in melanoma to provide novel predictive and prognostic biomarkers. In this review, we will highlight the different techniques currently under investigation for the detection of prognostic and predictive immune biomarkers in melanoma.

A pan-cancer clinical platform to predict immunotherapy outcomes and prioritize immuno-oncology combinations in early-phase trials

BACKGROUND

Immunotherapy is effective, but current biomarkers for patient selection have proven modest sensitivity. Here, we developed VIGex, an optimized gene signature based on the expression level of 12 genes involved in immune response with RNA sequencing.

METHODS

We implemented VIGex using the nCounter platform (Nanostring) on a large clinical cohort encompassing 909 tumor samples across 45 tumor types. VIGex was developed as a continuous variable, with cutoffs selected to detect three main categories (hot, intermediate-cold and cold) based on the different inflammatory status of the tumor microenvironment.

FINDINGS

Hot tumors had the highest VIGex scores and exhibited an increased abundance of tumor-infiltrating lymphocytes as compared with the intermediate-cold and cold. VIGex scores varied depending on tumor origin and anatomic site of metastases, with liver metastases showing an immunosuppressive tumor microenvironment. The predictive power of VIGex-Hot was observed in a cohort of 98 refractory solid tumor from patients treated in early-phase immunotherapy trials and its clinical performance was confirmed through an extensive metanalysis across 13 clinically annotated gene expression datasets from 877 patients treated with immunotherapy agents. Last, we generated a pan-cancer biomarker platform that integrates VIGex categories with the expression levels of immunotherapy targets under development in early-phase clinical trials.

CONCLUSIONS

Our results support the clinical utility of VIGex as a tool to aid clinicians for patient selection and personalized immunotherapy interventions.

FUNDING

BBVA Foundation; 202-2021 Division of Medical Oncology and Hematology Fellowship award; Princess Margaret Cancer Center.

Cancer cell-intrinsic mechanisms driving acquired immune tolerance

Immune evasion is a hallmark of cancer, enabling tumors to survive contact with the host immune system and evade the cycle of immune recognition and destruction. Here, we review the current understanding of the cancer cell-intrinsic factors driving immune evasion. We focus on T cells as key effectors of anti-cancer immunity and argue that cancer cells evade immune destruction by gaining control over pathways that usually serve to maintain physiological tolerance to self. Using this framework, we place recent mechanistic advances in the understanding of cancer immune evasion into broad categories of control over T cell localization, antigen recognition, and acquisition of optimal effector function. We discuss the redundancy in the pathways involved and identify knowledge gaps that must be overcome to better target immune evasion, including the need for better, routinely available tools that incorporate the growing understanding of evasion mechanisms to stratify patients for therapy and trials.

Tertiary lymphoid structures and B cells: An intratumoral immunity cycle

The generation of anti-tumor immunity in the draining lymph nodes is known as the cancer immunity cycle. Accumulating evidence supports the occurrence of such a cycle at tumor sites in the context of chronic inflammation. Here, we review the role of tertiary lymphoid structures (TLS) in the generation of T and B cell immunities, focusing on the impact of B cells that undergo full maturation, resulting in the generation of plasma cells (PCs) producing high-affinity IgG and IgA antibodies. In this context, we propose that antibodies binding to tumor cells induce macrophage or natural killer (NK)-cell-dependent apoptosis. Subsequently, released antigen-antibody complexes are internalized and processed by dendritic cells (DCs), amplifying antigen presentation to T cells. Immune complexes may also be fixed by follicular DCs (FDCs) in TLS, thereby increasing memory B cell responses. This amplification loop creates an intra-tumoral immunity cycle, capable of increasing sensitivity of tumors to immunotherapy even in cancers with low mutational burden.

Dendritic Cell Vaccination in Non-Small Cell Lung Cancer: Remodeling the Tumor Immune Microenvironment

Non-small-cell lung cancer (NSCLC) remains one of the leading causes of death worldwide. While NSCLCs possess antigens that can potentially elicit T cell responses, defective tumor antigen presentation and T cell activation hinder host anti-tumor immune responses. The NSCLC tumor microenvironment (TME) is composed of cellular and soluble mediators that can promote or combat tumor growth. The composition of the TME plays a critical role in promoting tumorigenesis and dictating anti-tumor immune responses to immunotherapy. Dendritic cells (DCs) are critical immune cells that activate anti-tumor T cell responses and sustain effector responses. DC vaccination is a promising cellular immunotherapy that has the potential to facilitate anti-tumor immune responses and transform the composition of the NSCLC TME via tumor antigen presentation and cell-cell communication. Here, we will review the features of the NSCLC TME with an emphasis on the immune cell phenotypes that directly interact with DCs. Additionally, we will summarize the major preclinical and clinical approaches for DC vaccine generation and examine how effective DC vaccination can transform the NSCLC TME toward a state of sustained anti-tumor immune signaling.

Clinical-genomic determinants of immune checkpoint blockade response in head and neck squamous cell carcinoma

BACKGROUNDRecurrent and/or metastatic (R/M) head and neck squamous cell carcinoma (HNSCC) is generally an incurable disease, with patients experiencing median survival of under 10 months and significant morbidity. While immune checkpoint blockade (ICB) drugs are effective in approximately 20% of patients, the remaining experience limited clinical benefit and are exposed to potential adverse effects and financial costs. Clinically approved biomarkers, such as tumor mutational burden (TMB), have a modest predictive value in HNSCC.METHODSWe analyzed clinical and genomic features, generated using whole-exome sequencing, in 133 ICB-treated patients with R/M HNSCC, of whom 69 had virus-associated and 64 had non-virus-associated tumors.RESULTSHierarchical clustering of genomic data revealed 6 molecular subtypes characterized by a wide range of objective response rates and survival after ICB therapy. The prognostic importance of these 6 subtypes was validated in an external cohort. A random forest-based predictive model, using several clinical and genomic features, predicted progression-free survival (PFS), overall survival (OS), and response with greater accuracy than did a model based on TMB alone. Recursive partitioning analysis identified 3 features (systemic inflammatory response index, TMB, and smoking signature) that classified patients into risk groups with accurate discrimination of PFS and OS.CONCLUSIONThese findings shed light on the immunogenomic characteristics of HNSCC tumors that drive differential responses to ICB and identify a clinical-genomic classifier that outperformed the current clinically approved biomarker of TMB. This validated predictive tool may help with clinical risk stratification in patients with R/M HNSCC for whom ICB is being considered.FUNDINGFundación Alfonso Martín Escudero, NIH R01 DE027738, US Department of Defense CA210784, The Geoffrey Beene Cancer Research Center, The MSKCC Population Science Research Program, the Jayme Flowers Fund, the Sebastian Nativo Fund, and the NIH/NCI Cancer Center Support Grant P30 CA008748.

Mismatch repair deficiency is not sufficient to elicit tumor immunogenicity

DNA mismatch repair deficiency (MMRd) is associated with a high tumor mutational burden (TMB) and sensitivity to immune checkpoint blockade (ICB) therapy. Nevertheless, most MMRd tumors do not durably respond to ICB and critical questions remain about immunosurveillance and TMB in these tumors. In the present study, we developed autochthonous mouse models of MMRd lung and colon cancer. Surprisingly, these models did not display increased T cell infiltration or ICB response, which we showed to be the result of substantial intratumor heterogeneity of mutations. Furthermore, we found that immunosurveillance shapes the clonal architecture but not the overall burden of neoantigens, and T cell responses against subclonal neoantigens are blunted. Finally, we showed that clonal, but not subclonal, neoantigen burden predicts ICB response in clinical trials of MMRd gastric and colorectal cancer. These results provide important context for understanding immune evasion in cancers with a high TMB and have major implications for therapies aimed at increasing TMB.

Analysis of circulating tumor DNA during checkpoint inhibition in metastatic melanoma using a tumor-agnostic panel

Immunotherapy has revolutionized treatment of patients diagnosed with metastatic melanoma, where nearly half of patients receive clinical benefit. However, immunotherapy is also associated with immune-related adverse events, which may be severe and persistent. It is therefore important to identify patients that do not benefit from therapy early. Currently, regularly scheduled CT scans are used to investigate size changes in target lesions to evaluate progression and therapy response. This study aims to explore if panel-based analysis of circulating tumor DNA (ctDNA) taken at 3-week intervals may provide a window into the growing cancer, can be used to identify nonresponding patients early, and determine genomic alterations associated with acquired resistance to checkpoint immunotherapy without analysis of tumor tissue biopsies. We designed a gene panel for ctDNA analysis and sequenced 4-6 serial plasma samples from 24 patients with unresectable stage III or IV melanoma and treated with first-line checkpoint inhibitors enrolled at the Department of Oncology at Aarhus University Hospital, Denmark. TERT was the most mutated gene found in ctDNA and associated with a poor prognosis. We detected more ctDNA in patients with high metastatic load, which indicates that more aggressive tumors release more ctDNA into the bloodstream. Although we did not find evidence of specific mutations associated with acquired resistance, we did demonstrate in this limited cohort of 24 patients that untargeted, panel-based ctDNA analysis has the potential to be used as a minimally invasive tool in clinical practice to identify patients where the benefits of immunotherapy outweigh the drawbacks.

Immunotherapy for Advanced Hepatocellular Carcinoma-a Large Tertiary Center Experience

INTRODUCTION

Combination of immune-checkpoint inhibitor (ICI) and vascular endothelial growth factor (VEGF) antagonist has become the first line systemic treatment for advanced hepatocellular carcinoma (HCC). However, two-thirds of patients do not respond to ICI-based treatments and biomarkers for response remain elusive.

METHODS

Patients with advanced HCC who received Atezolizumab/Bevacizumab combination or Nivolumab during 2016-2022 were identified in our Liver Cancer Database. Retrospective review of their clinical data was performed to investigate parameters that could be predictive of immunotherapy response.

RESULTS

96 patients received Atezolizumab/Bevacizumab (n=60) or Nivolumab (n=36). Median age at diagnosis was 67.1 years. 70 patients had received treatment and 26 patients were treatment naïve before starting immunotherapy. Mean pre-treatment AFP was 9780.7 (±32035) ng/mL. Confirmed objective response (complete or partial) was seen in 29% of the population (n=27). Disease remained stable in 12% (n=11) and progressed in 60% (n=56). On univariate analysis, pre-treatment AFP>400 ng/mL was associated with objective response (OR=4.5, 95% CI:1.7-11.9, p=0.0015), while white race (OR=0.35, 95% CI:0.13-0.92, p=0.030) and prior radiotherapy (OR=0.14, 95% CI:0.01-1.1, p=0.033) or systemic therapy with TKIs (OR=0.25, 95% CI:0.08-0.81, p=0.017) were associated with poor response. On multivariate analysis only AFP>400 ng/mL remained associated with response (OR=3.7, 95% CI:1.3-10.5, p=0.014). Overall survival (OS) at one and three years was 86% and 43% in responders, and 45% and 29% in non-responders, respectively.

CONCLUSION

In our institutional experience, treatment naivety and pre-treatment AFP>400 ng/mL were associated with objective response. Prospective studies aimed at identifying factors associated with response to immunotherapy will aide patient selection.

FGF/FGFR genomic amplification as a predictive biomarker for immune checkpoint blockade resistance: a short report

A novel crosstalk between immunogenic and oncometabolic pathways triggered by T cell-released interferon-gamma (IFN-ɣ) has been recently identified. This IFN-ɣ-pyruvate kinase M2-β-catenin axis relies on fibroblast growth factor 2 (FGF2) signaling in tumor cells and leads to hyperprogressive disease on immune checkpoint blockade (ICB) in preclinical models. This result underlines how IFN-ɣ signaling may have distinct effects on tumor cells depending on their oncogenic and metabolic features. On the basis of these data, this study aims to explore the relationship between genomic tumor FGF2 or FGF/FGF receptor (FGFR) amplification and immunotherapy response in patients with metastatic solid cancers. We used a large genomic data set of 545 ICB-treated patients and compared outcomes between those with and without FGF2 genomic amplification. Patients with no FGF2 genomic amplification had significantly longer progression-free survival (PFS) (HR=0.55 (95% CI 0.4, 0.8); p value=0.005) and overall survival (OS) (HR=0.56 (0.3, 0.9); p value=0.02) than patients harboring an FGF2 amplification. We next questioned whether such an observation may extend to genomic amplification of the FGF/FGFR pathway. Similarly, patients with no FGF/FGFR genomic amplification had longer PFS (HR=0.71 (0.8, 0.9), p value=0.004) and OS (HR=0.77 (0.6, 1); p value=0.06). RNA sequencing analysis of tumors between the amplified and non-amplified populations showed distinct expression profiles concerning oncogenic pathways. Importantly, using a cohort of patients untreated with ICB from the The Cancer Genome Atlas, we show that FGF2 and FGF/FGFR genomic amplification were not associated with prognosis, thus demonstrating that we identified a predictive biomarker of immunotherapy resistance.

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.

The role of IFN-γ-signalling in response to immune checkpoint blockade therapy

Treatment with immune checkpoint inhibitors, widely known as immune checkpoint blockade therapy (ICBT), is now the fourth pillar in cancer treatment, offering the chance of durable remission for patients with advanced disease. However, ICBT fails to induce objective responses in most cancer patients with still others progressing after an initial response. It is necessary, therefore, to elucidate the primary and acquired resistance mechanisms to ICBT to improve its efficacy. Here, we highlight the paradoxical role of the cytokine interferon-γ (IFN-γ) in ICBT response: on the one hand induction of IFN-γ signalling in the tumour microenvironment correlates with good ICBT response as it drives the cellular immune responses required for tumour destruction; nonetheless, IFN-γ signalling is implicated in ICBT acquired resistance. We address the negative feedback and immunoregulatory effects of IFN-γ signalling that promote immune evasion and resistance to ICBT and discuss how these can be targeted pharmacologically to restore sensitivity or circumvent resistance.

T-cell response to checkpoint blockade immunotherapies: from fundamental mechanisms to treatment signatures

Immune checkpoint immunotherapies act to block inhibitory receptors on the surface of T cells and other cells of the immune system. This can increase activation of immune cells and promote tumour clearance. Whilst this is very effective in some types of cancer, significant proportions of patients do not respond to single-agent immunotherapy. To improve patient outcomes, we must first mechanistically understand what drives therapy resistance. Many studies have utilised genetic, transcriptional, and histological signatures to find correlates of effective responses to treatment. It is key that we understand pretreatment predictors of response, but also to understand how the immune system becomes treatment resistant during therapy. Here, we review our understanding of the T-cell signatures that are critical for response, how these immune signatures change during treatment, and how this information can be used to rationally design therapeutic strategies. We highlight how chronic antigen recognition drives heterogeneous T-cell exhaustion and the role of T-cell receptor (TCR) signal strength in exhausted T-cell differentiation and molecular response to therapy. We explore how dynamic changes in negative feedback pathways can promote resistance to single-agent therapy. We speculate that this resistance may be circumvented in the future through identifying the most effective combinations of immunotherapies to promote sustained and durable antitumour responses.

Single-cell and bulk sequencing analyses reveal the immune suppressive role of PTPN6 in glioblastoma

Glioblastoma (GBM) is a highly malignant brain cancer with a poor prognosis despite standard treatments. This investigation aimed to explore the feasibility of PTPN6 to combat GBM with immunotherapy. Our study employed a comprehensive analysis of publicly available datasets and functional experiments to assess PTPN6 gene expression, prognostic value, and related immune characteristics in glioma. We evaluated the influence of PTPN6 expression on CD8+ T cell exhaustion, immune suppression, and tumor growth in human GBM samples and mouse models. Our findings demonstrated that PTPN6 overexpression played an oncogenic role in GBM and was associated with advanced tumor grades and unfavorable clinical outcomes. In human GBM samples, PTPN6 upregulation showed a strong association with immunosuppressive formation and CD8+ T cell dysfunction, whereas, in mice, it hindered CD8+ T cell infiltration. Moreover, PTPN6 facilitated cell cycle progression, inhibited apoptosis, and promoted glioma cell proliferation, tumor growth, and colony formation in mice. The outcomes of our study indicate that PTPN6 is a promising immunotherapeutic target for the treatment of GBM. Inhibition of PTPN6 could enhance CD8+ T cell infiltration and improve antitumor immune response, thus leading to better clinical outcomes for GBM patients.

The impact of mutational clonality in predicting the response to immune checkpoint inhibitors in advanced urothelial cancer

Immune checkpoint inhibitors (ICI) have revolutionized cancer treatment and can result in complete remissions even at advanced stages of the disease. However, only a small fraction of patients respond to the treatment. To better understand which factors drive clinical benefit, we have generated whole exome and RNA sequencing data from 27 advanced urothelial carcinoma patients treated with anti-PD-(L)1 monoclonal antibodies. We assessed the influence on the response of non-synonymous mutations (tumor mutational burden or TMB), clonal and subclonal mutations, neoantigen load and various gene expression markers. We found that although TMB is significantly associated with response, this effect can be mostly explained by clonal mutations, present in all cancer cells. This trend was validated in an additional cohort. Additionally, we found that responders with few clonal mutations had abnormally high levels of T and B cell immune markers, suggesting that a high immune cell infiltration signature could be a better predictive biomarker for this subset of patients. Our results support the idea that highly clonal cancers are more likely to respond to ICI and suggest that non-additive effects of different signatures should be considered for predictive models.

Long-course chemoradiation plus concurrent/sequential PD-1 blockade as neoadjuvant treatment for MMR-status-unscreened locally advanced rectal cancer: protocol of a multicentre, phase 2, randomised controlled trial (the POLAR-STAR trial)

INTRODUCTION

Recent preclinical studies have discovered unique synergism between radiotherapy and immune checkpoint inhibitors, which has already brought significant survival benefit in lung cancer. In locally advanced rectal cancer (LARC), neoadjuvant radiotherapy plus immune checkpoint inhibitors have also achieved surprisingly high pathological complete response (pCR) rates even in proficient mismatch-repair patients. As existing researches are all phase 2, single-cohort trials, we aim to conduct a randomised, controlled trial to further clarify the efficacy and safety of this novel combination therapy.

METHODS AND ANALYSIS

Eligible patients with LARC are randomised to three arms (two experiment arms, one control arm). Patients in all arms receive long-course radiotherapy plus concurrent capecitabine as neoadjuvant therapy, as well as radical surgery. Distinguishingly, patients in arm 1 also receive anti-PD-1 (Programmed Death 1) treatment starting at Day 8 of radiation (concurrent plan), and patients in arm 2 receive anti-PD-1 treatment starting 2 weeks after completion of radiation (sequential plan). Tislelizumab (anti-PD-1) is scheduled to be administered at 200 mg each time for three consecutive times, with 3-week intervals. Randomisation is stratified by different participating centres, with a block size of 6. The primary endpoint is pCR rate, and secondary endpoints include neoadjuvant-treatment-related adverse event rate, as well as disease-free and overall survival rates at 2, 3 and 5 years postoperation. Data will be analysed with an intention-to-treat approach.

ETHICS AND DISSEMINATION

This protocol has been approved by the institutional ethical committee of Beijing Friendship Hospital (the primary centre) with an identifying serial number of 2022-P2-050-01. Before publication to peer-reviewed journals, data of this research will be stored in a specially developed clinical trial database.

TRIAL REGISTRATION NUMBER

NCT05245474.

Transcriptional immunogenomic analysis reveals distinct immunological clusters in paediatric nervous system tumours

BACKGROUND

Cancer immunotherapies including immune checkpoint inhibitors and Chimeric Antigen Receptor (CAR) T-cell therapy have shown variable response rates in paediatric patients highlighting the need to establish robust biomarkers for patient selection. While the tumour microenvironment in adults has been widely studied to delineate determinants of immune response, the immune composition of paediatric solid tumours remains relatively uncharacterized calling for investigations to identify potential immune biomarkers.

METHODS

To inform immunotherapy approaches in paediatric cancers with embryonal origin, we performed an immunogenomic analysis of RNA-seq data from 925 treatment-naïve paediatric nervous system tumours (pedNST) spanning 12 cancer types from three publicly available data sets.

RESULTS

Within pedNST, we uncovered four broad immune clusters: Paediatric Inflamed (10%), Myeloid Predominant (30%), Immune Neutral (43%) and Immune Desert (17%). We validated these clusters using immunohistochemistry, methylation immune inference and segmentation analysis of tissue images. We report shared biology of these immune clusters within and across cancer types, and characterization of specific immune cell frequencies as well as T- and B-cell repertoires. We found no associations between immune infiltration levels and tumour mutational burden, although molecular cancer entities were enriched within specific immune clusters.

CONCLUSIONS

Given the heterogeneity of immune infiltration within pedNST, our findings suggest personalized immunogenomic profiling is needed to guide selection of immunotherapeutic strategies.

Plasma YKL-40 is associated with prognosis in patients with metastatic pancreatic cancer receiving immune checkpoint inhibitors in combination with radiotherapy

Background

YKL-40, also known as chitinase-3-like protein 1 (CHI3L1), is a secreted glycoprotein produced by various cell types including stromal, immune, and cancer cells. It contributes to cancer progression through tumor-promoting inflammation and has been shown to inhibit the cytotoxicity of T and NK lymphocytes. In vivo studies have demonstrated synergistic anti-cancer effects of blocking YKL-40 in combination with immune checkpoint inhibitors (ICIs). Biomarkers for the prediction of the response to ICIs are highly needed. We investigated the association between plasma YKL-40 and clinical benefit and survival in patients with metastatic pancreatic cancer (mPC) receiving ICIs and stereotactic body radiotherapy (SBRT).

Methods

Blood samples were collected from 84 patients with mPC who participated in the randomized phase II CheckPAC study, in which patients received nivolumab with or without ipilimumab combined with a single fraction of SBRT. Plasma YKL-40 was measured using a commercial ELISA kit.

Results

Elevated baseline plasma YKL-40 was an independent predictor of shorter overall survival (OS) (HR 2.19, 95% CI 1.21-3.95). A ≥ 40% decrease in plasma YKL-40 during treatment was associated with longer progression-free survival (p = 0.009) and OS (p = 0.0028). There was no correlation between plasma YKL-40 and the tumor burden marker CA19-9 at baseline or during treatment.

Conclusion

This study contributes new knowledge regarding YKL-40 as a predictor of clinical benefit from ICIs and radiotherapy. These exploratory results warrant further investigation of YKL-40 as a biomarker for patients treated with immunotherapies.

Clinical trial registration

Clinicaltrials.gov, identifier NCT02866383.

So Grateful for My X: Sex Chromosomes Drive Differences in Glioblastoma Immunity

SUMMARY

Males are at a greater risk of developing glioblastoma and face poorer prognoses compared with their female counterparts for reasons that are not well understood. Lee and colleagues uncover a role for sex-based differences in CD8+ T-cell function, which adds another layer to our growing understanding that antitumor immunity is not generated equivalently between males and females. See related article by Lee et al., p. 2090 (5).

CCL21-DC in situ vaccination in murine NSCLC overcomes resistance to immunotherapy and generates systemic tumor-specific immunity

BACKGROUND

Despite recent advances in immunotherapy, many patients with non-small cell lung cancer (NSCLC) do not respond to immune checkpoint inhibitors (ICI). Resistance to ICI may be driven by suboptimal priming of antitumor T lymphocytes due to poor antigen presentation as well as their exclusion and impairment by the immunosuppressive tumor microenvironment (TME). In a recent phase I trial in patients with NSCLC, in situ vaccination (ISV) with dendritic cells engineered to secrete CCL21 (CCL21-DC), a chemokine that facilitates the recruitment of T cells and DC, promoted T lymphocyte tumor infiltration and PD-L1 upregulation.

METHODS

Murine models of NSCLC with distinct driver mutations (KrasG12D/P53+/-/Lkb1-/- (KPL); KrasG12D/P53+/- (KP); and KrasG12D (K)) and varying tumor mutational burden were used to evaluate the efficacy of combination therapy with CCL21-DC ISV plus ICI. Comprehensive analyses of longitudinal preclinical samples by flow cytometry, single cell RNA-sequencing (scRNA-seq) and whole-exome sequencing were performed to assess mechanisms of combination therapy.

RESULTS

ISV with CCL21-DC sensitized immune-resistant murine NSCLCs to ICI and led to the establishment of tumor-specific immune memory. Immunophenotyping revealed that CCL21-DC obliterated tumor-promoting neutrophils, promoted sustained infiltration of CD8 cytolytic and CD4 Th1 lymphocytes and enriched progenitor T cells in the TME. Addition of ICI to CCL21-DC further enhanced the expansion and effector function of T cells both locally and systemically. Longitudinal evaluation of tumor mutation profiles revealed that CCL21-DC plus ICI induced immunoediting of tumor subclones, consistent with the broadening of tumor-specific T cell responses.

CONCLUSIONS

CCL21-DC ISV synergizes with anti-PD-1 to eradicate murine NSCLC. Our data support the clinical application of CCL21-DC ISV in combination with checkpoint inhibition for patients with NSCLC.

Germline mechanisms of immunotherapy toxicities in the era of genome-wide association studies

Cancer immunotherapy has revolutionized the treatment of advanced cancers and is quickly becoming an option for early-stage disease. By reactivating the host immune system, immunotherapy harnesses patients' innate defenses to eradicate the tumor. By putatively similar mechanisms, immunotherapy can also substantially increase the risk of toxicities or immune-related adverse events (irAEs). Severe irAEs can lead to hospitalization, treatment discontinuation, lifelong immune complications, or even death. Many irAEs present with similar symptoms to heritable autoimmune diseases, suggesting that germline genetics may contribute to their onset. Recently, genome-wide association studies (GWAS) of irAEs have identified common germline associations and putative mechanisms, lending support to this hypothesis. A wide range of well-established GWAS methods can potentially be harnessed to understand the etiology of irAEs specifically and immunotherapy outcomes broadly. This review summarizes current findings regarding germline effects on immunotherapy outcomes and discusses opportunities and challenges for leveraging germline genetics to understand, predict, and treat irAEs.

Single-cell transcriptomics identify TNFRSF1B as a novel T-cell exhaustion marker for ovarian cancer

BACKGROUND

Ovarian cancer (OC) patients routinely show poor immunotherapeutic response due to the complex tumour microenvironment (TME). It is urgent to explore new immunotherapeutic markers.

METHODS

Through the single-cell RNA sequencing (scRNA-seq) analyses on high-grade serous OC (HGSOC), moderate severity borderline tumour and matched normal ovary, we identified a novel exhausted T cells subpopulation that related to poor prognosis in OC. Histological staining, multiple immunofluorescences, and flow cytometry were applied to validate some results from scRNA-seq. Furthermore, a tumour-bearing mice model was constructed to investigate the effects of TNFRSF1B treatment on tumour growth in vivo.

RESULTS

Highly immunosuppressive TME in HGSOC is displayed compared to moderate severity borderline tumour and matched normal ovary. Subsequently, a novel exhausted subpopulation of CD8+ TNFRSF1B+ T cells is identified, which is associated with poor survival. In vitro experiments demonstrate that TNFRSF1B is specifically upregulated on activated CD8+ T cells and suppressed interferon-γ secretion. The expression of TNFRSF1B on CD8+ T cells is closely related to OC clinical malignancy and is a marker of poor prognosis through 140 OC patients' verification. In addition, the blockade of TNFRSF1B inhibits tumour growth via profoundly remodeling the immune microenvironment in the OC mouse model.

CONCLUSIONS

Our transcriptomic results analyzed by scRNA-seq delineate a high-resolution snapshot of the entire tumour ecosystem of OC TME. The major applications of our findings were an exhausted subpopulation of CD8+ TNFRSF1B+ T cells for predicting OC patient prognosis and the potential therapeutic value of TNFRSF1B. These findings demonstrated the clinical value of TNFRSF1B as a potential immunotherapy target and extended our understanding of factors contributing to immunotherapy failure in OC.

Antigen presentation in cancer - mechanisms and clinical implications for immunotherapy

Over the past decade, the emergence of effective immunotherapies has revolutionized the clinical management of many types of cancers. However, long-term durable tumour control is only achieved in a fraction of patients who receive these therapies. Understanding the mechanisms underlying clinical response and resistance to treatment is therefore essential to expanding the level of clinical benefit obtained from immunotherapies. In this Review, we describe the molecular mechanisms of antigen processing and presentation in tumours and their clinical consequences. We examine how various aspects of the antigen-presentation machinery (APM) shape tumour immunity. In particular, we discuss genomic variants in HLA alleles and other APM components, highlighting their influence on the immunopeptidomes of both malignant cells and immune cells. Understanding the APM, how it is regulated and how it changes in tumour cells is crucial for determining which patients will respond to immunotherapy and why some patients develop resistance. We focus on recently discovered molecular and genomic alterations that drive the clinical outcomes of patients receiving immune-checkpoint inhibitors. An improved understanding of how these variables mediate tumour-immune interactions is expected to guide the more precise administration of immunotherapies and reveal potentially promising directions for the development of new immunotherapeutic approaches.

Rheumatic complications of checkpoint inhibitors: Lessons from autoimmunity

Immune checkpoint inhibitors are now an established treatment in the management of a range of cancers. Their success means that their use is likely to increase in future in terms of the numbers of patients treated, the indications and the range of immune checkpoints targeted. They function by counteracting immune evasion by the tumor but, as a consequence, can breach self-tolerance at other sites leading to a range of immune-related adverse events. Included among these complications are a range of rheumatologic complications, including inflammatory arthritis and keratoconjunctivitis sicca. These superficially resemble immune-mediated rheumatic diseases (IMRDs) such as rheumatoid arthritis and Sjogren's disease but preliminary studies suggest they are clinically and immunologically distinct entities. However, there appear to be common processes that predispose to the development of both that may inform preventative interventions and predictive tools. Both groups of conditions highlight the centrality of immune checkpoints in controlling tolerance and how it can be restored. Here we will discuss some of these commonalities and differences between rheumatic irAEs and IMRDs.

Predictive biomarkers of immunotherapy response with pharmacological applications in solid tumors

Immune-checkpoint inhibitors show promising effects in the treatment of multiple tumor types. Biomarkers are biological indicators used to select patients for a systemic anticancer treatment, but there are only a few clinically useful biomarkers such as PD-L1 expression and tumor mutational burden, which can be used to predict immunotherapy response. In this study, we established a database consisting of both gene expression and clinical data to identify biomarkers of response to anti-PD-1, anti-PD-L1, and anti-CTLA-4 immunotherapies. A GEO screening was executed to identify datasets with simultaneously available clinical response and transcriptomic data regardless of cancer type. The screening was restricted to the studies involving administration of anti-PD-1 (nivolumab, pembrolizumab), anti-PD-L1 (atezolizumab, durvalumab) or anti-CTLA-4 (ipilimumab) agents. Receiver operating characteristic (ROC) analysis and Mann-Whitney test were executed across all genes to identify features related to therapy response. The database consisted of 1434 tumor tissue samples from 19 datasets with esophageal, gastric, head and neck, lung, and urothelial cancers, plus melanoma. The strongest druggable gene candidates linked to anti-PD-1 resistance were SPIN1 (AUC = 0.682, P = 9.1E-12), SRC (AUC = 0.667, P = 5.9E-10), SETD7 (AUC = 0.663, P = 1.0E-09), FGFR3 (AUC = 0.657, P = 3.7E-09), YAP1 (AUC = 0.655, P = 6.0E-09), TEAD3 (AUC = 0.649, P = 4.1E-08) and BCL2 (AUC = 0.634, P = 9.7E-08). In the anti-CTLA-4 treatment cohort, BLCAP (AUC = 0.735, P = 2.1E-06) was the most promising gene candidate. No therapeutically relevant target was found to be predictive in the anti-PD-L1 cohort. In the anti-PD-1 group, we were able to confirm the significant correlation with survival for the mismatch-repair genes MLH1 and MSH6. A web platform for further analysis and validation of new biomarker candidates was set up and available at https://www.rocplot.com/immune . In summary, a database and a web platform were established to investigate biomarkers of immunotherapy response in a large cohort of solid tumor samples. Our results could help to identify new patient cohorts eligible for immunotherapy.

CRISPR-Cas9 screening identifies an IRF1-SOCS1-mediated negative feedback loop that limits CXCL9 expression and antitumor immunity

CXCL9 expression is a strong predictor of response to immune checkpoint blockade therapy. Accordingly, we sought to develop therapeutic strategies to enhance the expression of CXCL9 and augment antitumor immunity. To perform whole-genome CRISPR-Cas9 screening for regulators of CXCL9 expression, a CXCL9-GFP reporter line is generated using a CRISPR knockin strategy. This approach finds that IRF1 limits CXCL9 expression in both tumor cells and primary myeloid cells through induction of SOCS1, which subsequently limits STAT1 signaling. Thus, we identify a subset of STAT1-dependent genes that do not require IRF1 for their transcription, including CXCL9. Targeting of either IRF1 or SOCS1 potently enhances CXCL9 expression by intratumoral macrophages, which is further enhanced in the context of immune checkpoint blockade therapy. We hence show a non-canonical role for IRF1 in limiting the expression of a subset of STAT1-dependent genes through induction of SOCS1.

Genome-guided discovery of cancer therapeutic targets

The success of precision oncology-which aims to match the right therapies to the right patients based on molecular status-is predicated on a robust pipeline of molecular targets against which therapies can be developed. Recent advances in genomics and functional genetics have enabled the unbiased discovery of novel molecular targets at scale. We summarize the promise and challenges in integrating genomic and functional genetic landscapes of cancer to establish the next generation of cancer targets.

Amphiregulin couples IL1RL1+ regulatory T cells and cancer-associated fibroblasts to impede antitumor immunity

Regulatory T (Treg) cells and cancer-associated fibroblasts (CAFs) jointly promote tumor immune tolerance and tumorigenesis. The molecular apparatus that drives Treg cell and CAF coordination in the tumor microenvironment (TME) remains elusive. Interleukin 33 (IL-33) has been shown to enhance fibrosis and IL1RL1+ Treg cell accumulation during tumorigenesis and tissue repair. We demonstrated that IL1RL1 signaling in Treg cells greatly dampened the antitumor activity of both IL-33 and PD-1 blockade. Whole tumor single-cell RNA sequencing (scRNA-seq) analysis and blockade experiments revealed that the amphiregulin (AREG)-epidermal growth factor receptor (EGFR) axis mediated cross-talk between IL1RL1+ Treg cells and CAFs. We further demonstrated that the AREG/EGFR axis enables Treg cells to promote a profibrotic and immunosuppressive functional state of CAFs. Moreover, AREG mAbs and IL-33 concertedly inhibited tumor growth. Our study reveals a previously unidentified AREG/EGFR-mediated Treg/CAF coupling that controls the bifurcation of fibroblast functional states and is a critical barrier for cancer immunotherapy.

T-cell priming transcriptomic markers: implications of immunome heterogeneity for precision immunotherapy

Immune checkpoint blockade is effective for only a subset of cancers. Targeting T-cell priming markers (TPMs) may enhance activity, but proper application of these agents in the clinic is challenging due to immune complexity and heterogeneity. We interrogated transcriptomics of 15 TPMs (CD137, CD27, CD28, CD80, CD86, CD40, CD40LG, GITR, ICOS, ICOSLG, OX40, OX40LG, GZMB, IFNG, and TBX21) in a pan-cancer cohort (N = 514 patients, 30 types of cancer). TPM expression was analyzed for correlation with histological type, microsatellite instability high (MSI-H), tumor mutational burden (TMB), and programmed death-ligand 1 (PD-L1) expression. Among 514 patients, the most common histological types were colorectal (27%), pancreatic (11%), and breast cancer (10%). No statistically significant association between histological type and TPM expression was seen. In contrast, expression of GZMB (granzyme B, a serine protease stored in activated T and NK cells that induces cancer cell apoptosis) and IFNG (activates cytotoxic T cells) were significantly higher in tumors with MSI-H, TMB ≥ 10 mutations/mb and PD-L1 ≥ 1%. PD-L1 ≥ 1% was also associated with significantly higher CD137, GITR, and ICOS expression. Patients' tumors were classified into "Hot", "Mixed", or "Cold" clusters based on TPM expression using hierarchical clustering. The cold cluster showed a significantly lower proportion of tumors with PD-L1 ≥ 1%. Overall, 502 patients (98%) had individually distinct patterns of TPM expression. Diverse expression patterns of TPMs independent of histological type but correlating with other immunotherapy biomarkers (PD-L1 ≥ 1%, MSI-H and TMB ≥ 10 mutations/mb) were observed. Individualized selection of patients based on TPM immunomic profiles may potentially help with immunotherapy optimization.

Proteogenomic analysis reveals RNA as a source for tumor-agnostic neoantigen identification

Systemic pan-tumor analyses may reveal the significance of common features implicated in cancer immunogenicity and patient survival. Here, we provide a comprehensive multi-omics data set for 32 patients across 25 tumor types for proteogenomic-based discovery of neoantigens. By using an optimized computational approach, we discover a large number of tumor-specific and tumor-associated antigens. To create a pipeline for the identification of neoantigens in our cohort, we combine DNA and RNA sequencing with MS-based immunopeptidomics of tumor specimens, followed by the assessment of their immunogenicity and an in-depth validation process. We detect a broad variety of non-canonical HLA-binding peptides in the majority of patients demonstrating partially immunogenicity. Our validation process allows for the selection of 32 potential neoantigen candidates. The majority of neoantigen candidates originates from variants identified in the RNA data set, illustrating the relevance of RNA as a still understudied source of cancer antigens. This study underlines the importance of RNA-centered variant detection for the identification of shared biomarkers and potentially relevant neoantigen candidates.

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.

Multimodal molecular landscape of response to Y90-resin microsphere radioembolization followed by nivolumab for advanced hepatocellular carcinoma

BACKGROUND

Combination therapy with radioembolization (yttrium-90)-resin microspheres) followed by nivolumab has shown a promising response rate of 30.6% in a Phase II trial (CA209-678) for advanced hepatocellular carcinoma (HCC); however, the response mechanisms and relevant biomarkers remain unknown.

METHODS

By collecting both pretreatment and on-treatment samples, we performed multimodal profiling of tissue and blood samples and investigated molecular changes associated with favorable responses in 33 patients from the trial.

RESULTS

We found that higher tumor mutation burden, NCOR1 mutations and higher expression of interferon gamma pathways occurred more frequently in responders. Meanwhile, non-responders tended to be enriched for a novel Asian-specific transcriptomic subtype (Kaya_P2) with a high frequency of chromosome 16 deletions and upregulated cell cycle pathways. Strikingly, unlike other cancer types, we did not observe any association between T-cell populations and treatment response, but tumors from responders had a higher proportion of CXCL9+/CXCR3+ macrophages. Moreover, biomarkers discovered in previous immunotherapy trials were not predictive in the current cohort, suggesting a distinctive molecular landscape associated with differential responses to the combination therapy.

CONCLUSIONS

This study unraveled extensive molecular changes underlying distinctive responses to the novel treatment and pinpointed new directions for harnessing combination therapy in patients with advanced HCC.

Prediction of response to immune checkpoint blockade in patients with metastatic colorectal cancer with microsatellite instability

BACKGROUND

Mismatch repair-deficient (dMMR) tumors displaying microsatellite instability (MSI) represent a paradigm for the success of immune checkpoint inhibitor (ICI)-based immunotherapy, particularly in patients with metastatic colorectal cancer (mCRC). However, a proportion of patients with dMMR/MSI mCRC exhibit resistance to ICI. Identification of tools predicting MSI mCRC patient response to ICI is required for the design of future strategies further improving this therapy.

PATIENTS AND METHODS

We combined high-throughput DNA and RNA sequencing of tumors from 116 patients with MSI mCRC treated with anti-programmed cell death protein 1 ± anti-cytotoxic T-lymphocyte-associated protein 4 of the NIPICOL phase II trial (C1, NCT03350126, discovery set) and the ImmunoMSI prospective cohort (C2, validation set). The DNA/RNA predictors whose status was significantly associated with ICI status of response in C1 were subsequently validated in C2. Primary endpoint was progression-free survival by immune RECIST (iRECIST) (iPFS).

RESULTS

Analyses showed no impact of previously suggested DNA/RNA indicators of resistance to ICI, e.g. MSIsensor score, tumor mutational burden, or specific cellular and molecular tumoral contingents. By contrast, iPFS under ICI was shown in C1 and C2 to depend both on a multiplex MSI signature involving the mutations of 19 microsatellites hazard ratio cohort C2 (HRC2) = 3.63; 95% confidence interval (CI) 1.65-7.99; P = 1.4 × 10-3] and the expression of a set of 182 RNA markers with a non-epithelial transforming growth factor beta (TGFB)-related desmoplastic orientation (HRC2 = 1.75; 95% CI 1.03-2.98; P = 0.035). Both DNA and RNA signatures were independently predictive of iPFS.

CONCLUSIONS

iPFS in patients with MSI mCRC can be predicted by simply analyzing the mutational status of DNA microsatellite-containing genes in epithelial tumor cells together with non-epithelial TGFB-related desmoplastic RNA markers.

Targeting CXCL9/10/11-CXCR3 axis: an important component of tumor-promoting and antitumor immunity

Chemokines are chemotactic-competent molecules composed of a family of small cytokines, playing a key role in regulating tumor progression. The roles of chemokines in antitumor immune responses are of great interest. CXCL9, CXCL10, and CXCL11 are important members of chemokines. It has been widely investigated that these three chemokines can bind to their common receptor CXCR3 and regulate the differentiation, migration, and tumor infiltration of immune cells, directly or indirectly affecting tumor growth and metastasis. Here, we summarize the mechanism of how the CXCL9/10/11-CXCR3 axis affects the tumor microenvironment, and list the latest researches to find out how this axis predicts the prognosis of different cancers. In addition, immunotherapy improves the survival of tumor patients, but some patients show drug resistance. Studies have found that the regulation of CXCL9/10/11-CXCR3 on the tumor microenvironment is involved in the process of changing immunotherapy resistance. Here we also describe new approaches to restoring sensitivity to immune checkpoint inhibitors through the CXCL9/10/11-CXCR3 axis.

Biomarkers for Immune Checkpoint Inhibitors in Renal Cell Carcinoma

Immune checkpoint inhibitor (ICI) therapy has revolutionized renal cell carcinoma treatment. Patients previously thought to be palliative now occasionally achieve complete cures from ICI. However, since immunotherapies stimulate the immune system to induce anti-tumor immunity, they often lead to adverse autoimmunity. Furthermore, some patients receive no benefit from ICI, thereby unnecessarily risking adverse events. In many tumor types, PD-L1 expression levels, immune infiltration, and tumor mutation burden predict the response to ICI and help inform clinical decision making to better target ICI to patients most likely to experience benefits. Unfortunately, renal cell carcinoma is an outlier, as these biomarkers fail to discriminate between positive and negative responses to ICI therapy. Emerging biomarkers such as gene expression profiles and the loss of pro-angiogenic proteins VHL and PBRM-1 show promise for identifying renal cell carcinoma cases likely to respond to ICI. This review provides an overview of the mechanistic underpinnings of different biomarkers and describes the theoretical rationale for their use. We discuss the effectiveness of each biomarker in renal cell carcinoma and other cancer types, and we introduce novel biomarkers that have demonstrated some promise in clinical trials.

Leveraging high-resolution omics data for predicting responses and adverse events to immune checkpoint inhibitors

A long-standing goal of personalized and precision medicine is to enable accurate prediction of the outcomes of a given treatment regimen for patients harboring a disease. Currently, many clinical trials fail to meet their endpoints due to underlying factors in the patient population that contribute to either poor responses to the drug of interest or to treatment-related adverse events. Identifying these factors beforehand and correcting for them can lead to an increased success of clinical trials. Comprehensive and large-scale data gathering efforts in biomedicine by omics profiling of the healthy and diseased individuals has led to a treasure-trove of host, disease and environmental factors that contribute to the effectiveness of drugs aiming to treat disease. With increasing omics data, artificial intelligence allows an in-depth analysis of big data and offers a wide range of applications for real-world clinical use, including improved patient selection and identification of actionable targets for companion therapeutics for improved translatability across more patients. As a blueprint for complex drug-disease-host interactions, we here discuss the challenges of utilizing omics data for predicting responses and adverse events in cancer immunotherapy with immune checkpoint inhibitors (ICIs). The omics-based methodologies for improving patient outcomes as in the ICI case have also been applied across a wide-range of complex disease settings, exemplifying the use of omics for in-depth disease profiling and clinical use.

The expression profiles of signature genes from CD103+LAG3+ tumour-infiltrating lymphocyte subsets predict breast cancer survival

BACKGROUND

Tumour-infiltrating lymphocytes (TILs), including T and B cells, have been demonstrated to be associated with tumour progression. However, the different subpopulations of TILs and their roles in breast cancer remain poorly understood. Large-scale analysis using multiomics data could uncover potential mechanisms and provide promising biomarkers for predicting immunotherapy response.

METHODS

Single-cell transcriptome data for breast cancer samples were analysed to identify unique TIL subsets. Based on the expression profiles of marker genes in these subsets, a TIL-related prognostic model was developed by univariate and multivariate Cox analyses and LASSO regression for the TCGA training cohort containing 1089 breast cancer patients. Multiplex immunohistochemistry was used to confirm the presence of TIL subsets in breast cancer samples. The model was validated with a large-scale transcriptomic dataset for 3619 breast cancer patients, including the METABRIC cohort, six chemotherapy transcriptomic cohorts, and two immunotherapy transcriptomic cohorts.

RESULTS

We identified two TIL subsets with high expression of CD103 and LAG3 (CD103+LAG3+), including a CD8+ T-cell subset and a B-cell subset. Based on the expression profiles of marker genes in these two subpopulations, we further developed a CD103+LAG3+ TIL-related prognostic model (CLTRP) based on CXCL13 and BIRC3 genes for predicting the prognosis of breast cancer patients. CLTRP-low patients had a better prognosis than CLTRP-high patients. The comprehensive results showed that a low CLTRP score was associated with a high TP53 mutation rate, high infiltration of CD8 T cells, helper T cells, and CD4 T cells, high sensitivity to chemotherapeutic drugs, and a good response to immunotherapy. In contrast, a high CLTRP score was correlated with a low TP53 mutation rate, high infiltration of M0 and M2 macrophages, low sensitivity to chemotherapeutic drugs, and a poor response to immunotherapy.

CONCLUSIONS

Our present study showed that the CLTRP score is a promising biomarker for distinguishing prognosis, drug sensitivity, molecular and immune characteristics, and immunotherapy outcomes in breast cancer patients. The CLTRP could serve as a valuable tool for clinical decision making regarding immunotherapy.

Predicting Outcomes of Atezolizumab and Bevacizumab Treatment in Patients with Hepatocellular Carcinoma

A combination of atezolizumab with bevacizumab (AB) is the first regimen that has shown superiority compared to sorafenib and is now being used as the systemic treatment of choice for hepatocellular carcinoma (HCC) patients with Barcelona Liver Cancer Clinic stage C. However, a considerable number of patients do not achieve survival or significant responses, indicating the need to identify predictive biomarkers for initial and on-treatment decisions in HCC patients receiving AB. In this manuscript, we summarized the current data from both experimental and clinical studies. This review will be beneficial for both clinicians and researchers in clinical practice as well as those designing experimental, translational, or clinical studies.

Perspectives in Immunotherapy: meeting report from Immunotherapy Bridge (Naples, November 30th-December 1st, 2022)

The discovery and development of novel treatments that harness the patient's immune system and prevent immune escape has dramatically improved outcomes for patients across cancer types. However, not all patients respond to immunotherapy, acquired resistance remains a challenge, and responses are poor in certain tumors which are considered to be immunologically cold. This has led to the need for new immunotherapy-based approaches, including adoptive cell transfer (ACT), therapeutic vaccines, and novel immune checkpoint inhibitors. These new approaches are focused on patients with an inadequate response to current treatments, with emerging evidence of improved responses in various cancers with new immunotherapy agents, often in combinations with existing agents. The use of cell therapies, drivers of immune response, and trends in immunotherapy were the focus of the Immunotherapy Bridge (November 30th-December 1st, 2022), organized by the Fondazione Melanoma Onlus, Naples, Italy, in collaboration with the Society for Immunotherapy of Cancer.

Immune Checkpoint Inhibitors, Small-Molecule Immunotherapies and the Emerging Role of Neutrophil Extracellular Traps in Therapeutic Strategies for Head and Neck Cancer

Immune checkpoint inhibitor (ICI) therapy has revolutionized the treatment of many cancer types, including head and neck cancers (HNC). When checkpoint and partner proteins bind, these send an "off" signal to T cells, which prevents the immune system from destroying tumor cells. However, in HNC, and indeed many other cancers, more people do not respond and/or suffer from toxic effects than those who do respond. Hence, newer, more effective approaches are needed. The challenge to durable therapy lies in a deeper understanding of the complex interactions between immune cells, tumor cells and the tumor microenvironment. This will help develop therapies that promote lasting tumorlysis by overcoming T-cell exhaustion. Here we explore the strengths and limitations of current ICI therapy in head and neck squamous cell carcinoma (HNSCC). We also review emerging small-molecule immunotherapies and the growing promise of neutrophil extracellular traps in controlling tumor progression and metastasis.

Development and validation of a copper-related gene prognostic signature in hepatocellular carcinoma

Introduction: Reliable biomarkers are in need to predict the prognosis of hepatocellular carcinoma (HCC). Whilst recent evidence has established the critical role of copper homeostasis in tumor growth and progression, no previous studies have dealt with the copper-related genes (CRGs) signature with prognostic potential in HCC. Methods: To develop and validate a CRGs prognostic signature for HCC, we retrospectively included 353 and 142 patients as the development and validation cohort, respectively. Copper-related Prognostic Signature (Copper-PSHC) was developed using differentially expressed CRGs with prognostic value. The hazard ratio (HR) and the area under the time-dependent receiver operating characteristic curve (AUC) during 3-year follow-up were utilized to evaluate the performance. Additionally, the Copper-PSHC was combined with age, sex, and cancer stage to construct a Copper-clinical-related Prognostic Signature (Copper-CPSHC), by multivariate Cox regression. We further explored the underlying mechanism of Copper-PSHC by analyzing the somatic mutation, functional enrichment, and tumor microenvironment. Potential drugs for the high-risk group were screened. Results: The Copper-PSHC was constructed with nine CRGs. Patients in the high-risk group demonstrated a significantly reduced overall survival (OS) (adjusted HR, 2.65 [95% CI, 1.83-3.84] and 3.30, [95% CI, 1.27-8.60] in the development and validation cohort, respectively). The Copper-PSHC achieved a 3-year AUC of 0.74 [95% CI, 0.67-0.82] and 0.71 [95% CI, 0.56-0.86] for OS in the development and validation cohort, respectively. Copper-CPSHC yield a 3-year AUC of 0.73 [95% CI, 0.66-0.80] and 0.72 [95% CI, 0.56-0.87] for OS in the development and validation cohort, respectively. Higher tumor mutation burden, downregulated metabolic processes, hypoxia status and infiltrated stroma cells were found for the high-risk group. Six small molecular drugs were screened for the treatment of the high-risk group. Conclusion: Copper-PSHC services as a promising tool to identify HCC with poor prognosis and to improve disease outcomes by providing potential clinical decision support in treatment.