Pan-cancer analysis of longitudinal metastatic tumors reveals genomic alterations and immune landscape dynamics associated with pembrolizumab sensitivity

Early Changes in Tumor-Naive Cell-Free Methylomes and Fragmentomes Predict Outcomes in Pembrolizumab-Treated Solid Tumors

Early kinetics of circulating tumor DNA (ctDNA) in plasma predict response to pembrolizumab but typically requires sequencing of matched tumor tissue or fixed gene panels. We analyzed genome-wide methylation and fragment-length profiles using cell-free methylated DNA immunoprecipitation and sequencing (cfMeDIP-seq) in 204 plasma samples from 87 patients before and during treatment with pembrolizumab from a pan-cancer phase II investigator-initiated trial (INSPIRE). We trained a pan-cancer methylation signature using independent methylation array data from The Cancer Genome Atlas to quantify cancer-specific methylation (CSM) and fragment-length score (FLS) for each sample. CSM and FLS are strongly correlated with tumor-informed ctDNA levels. Early kinetics of CSM predict overall survival and progression-free survival, independently of tumor type, PD-L1, and tumor mutation burden. Early kinetics of FLS are associated with overall survival independently of CSM. Our tumor-naïve mutation-agnostic ctDNA approach integrating methylomics and fragmentomics could predict outcomes in patients treated with pembrolizumab.

SIGNIFICANCE

Analysis of methylation and fragment length in plasma using cfMeDIP-seq provides a tumor-naive approach to measure ctDNA with results comparable with a tumor-informed bespoke ctDNA. Early kinetics within the first weeks of treatment in methylation and fragment quantity can predict outcomes with pembrolizumab in patients with various advanced solid tumors. This article is featured in Selected Articles from This Issue, p. 897.

Targeting LTA4H facilitates the reshaping of the immune microenvironment mediated by CCL5 and sensitizes ovarian cancer to Cisplatin

Ovarian cancer is the most lethal and aggressive gynecological cancer with a high recurrence rate and is often diagnosed late. In ovarian cancer, multiple metabolic enzymes of lipid metabolism are abnormally expressed, resulting in metabolism disorder. As a characteristic pathway in polyunsaturated fatty acid (PUFA) metabolism, arachidonic acid (AA) metabolism is disturbed in ovarian cancer. Therefore, we established a 10-gene signature model to evaluate the prognostic risk of PUFA-related genes. This 10-gene signature has strong robustness and can play a stable predictive role in datasets of various platforms (TCGA, ICGC, and GSE17260). The high association between the risk subgroups and clinical characteristics indicated a good performance of the model. Our data further indicated that the high expression of LTA4H was positively correlated with poor prognosis in ovarian cancer. Deficiency of LTA4H enhanced sensitivity to Cisplatin and modified the characteristics of immune cell infiltration in ovarian cancer. Additionally, our results indicate that CCL5 was involved in the aberrant metabolism of the AA/LTA4H axis, which contributes to the reduction of tumor-infiltrating CD8+ T cells and immune escape in ovarian cancer. These findings provide new insights into the prognosis and potential target of LTA4H/CCL5 in treating ovarian cancer.

Ultrasensitive plasma-based monitoring of tumor burden using machine-learning-guided signal enrichment

In solid tumor oncology, circulating tumor DNA (ctDNA) is poised to transform care through accurate assessment of minimal residual disease (MRD) and therapeutic response monitoring. To overcome the sparsity of ctDNA fragments in low tumor fraction (TF) settings and increase MRD sensitivity, we previously leveraged genome-wide mutational integration through plasma whole-genome sequencing (WGS). Here we now introduce MRD-EDGE, a machine-learning-guided WGS ctDNA single-nucleotide variant (SNV) and copy-number variant (CNV) detection platform designed to increase signal enrichment. MRD-EDGESNV uses deep learning and a ctDNA-specific feature space to increase SNV signal-to-noise enrichment in WGS by ~300× compared to previous WGS error suppression. MRD-EDGECNV also reduces the degree of aneuploidy needed for ultrasensitive CNV detection through WGS from 1 Gb to 200 Mb, vastly expanding its applicability within solid tumors. We harness the improved performance to identify MRD following surgery in multiple cancer types, track changes in TF in response to neoadjuvant immunotherapy in lung cancer and demonstrate ctDNA shedding in precancerous colorectal adenomas. Finally, the radical signal-to-noise enrichment in MRD-EDGESNV enables plasma-only (non-tumor-informed) disease monitoring in advanced melanoma and lung cancer, yielding clinically informative TF monitoring for patients on immune-checkpoint inhibition.

Androgen receptor activity inversely correlates with immune cell infiltration and immunotherapy response across multiple cancer lineages

There is now increasing recognition of the important role of androgen receptor (AR) in modulating immune function. To gain a comprehensive understanding of the effects of AR activity on cancer immunity, we employed a computational approach to profile AR activity in 33 human tumor types using RNA-Seq datasets from The Cancer Genome Atlas. Our pan-cancer analysis revealed that the genes most negatively correlated with AR activity across cancers are involved in active immune system processes. Importantly, we observed a significant negative correlation between AR activity and IFNγ pathway activity at the pan-cancer level. Indeed, using a matched biopsy dataset from subjects with prostate cancer before and after AR-targeted treatment, we verified that inhibiting AR enriches immune cell abundances and is associated with higher IFNγ pathway activity. Furthermore, by analyzing immunotherapy datasets in multiple cancers, our results demonstrate that low AR activity was significantly associated with a favorable response to immunotherapy. Together, our data provide a comprehensive assessment of the relationship between AR signaling and tumor immunity.

Proteogenomic characterization of primary colorectal cancer and metastatic progression identifies proteome-based subtypes and signatures

Metastatic progression of colorectal adenocarcinoma (CRC) remains poorly understood and poses significant challenges for treatment. To overcome these challenges, we performed multiomics analyses of primary CRC and liver metastases. Genomic alterations, such as structural variants or copy number alterations, were enriched in oncogenes and tumor suppressor genes and increased in metastases. Unsupervised mass spectrometry-based proteomics of 135 primary and 123 metastatic CRCs uncovered distinct proteomic subtypes, three each for primary and metastatic CRCs, respectively. Integrated analyses revealed that hypoxia, stemness, and immune signatures characterize these 6 subtypes. Hypoxic CRC harbors high epithelial-to-mesenchymal transition features and metabolic adaptation. CRC with a stemness signature shows high oncogenic pathway activation and alternative telomere lengthening (ALT) phenotype, especially in metastatic lesions. Tumor microenvironment analysis shows immune evasion via modulation of major histocompatibility complex (MHC) class I/II and antigen processing pathways. This study characterizes both primary and metastatic CRCs and provides a large proteogenomics dataset of metastatic progression.

NKG2A Is a Therapeutic Vulnerability in Immunotherapy Resistant MHC-I Heterogeneous Triple-Negative Breast Cancer

Despite the success of immune checkpoint inhibition (ICI) in treating cancer, patients with triple-negative breast cancer (TNBC) often develop resistance to therapy, and the underlying mechanisms are unclear. MHC-I expression is essential for antigen presentation and T-cell-directed immunotherapy responses. This study demonstrates that TNBC patients display intratumor heterogeneity in regional MHC-I expression. In murine models, loss of MHC-I negates antitumor immunity and ICI response, whereas intratumor MHC-I heterogeneity leads to increased infiltration of natural killer (NK) cells in an IFNγ-dependent manner. Using spatial technologies, MHC-I heterogeneity is associated with clinical resistance to anti-programmed death (PD) L1 therapy and increased NK:T-cell ratios in human breast tumors. MHC-I heterogeneous tumors require NKG2A to suppress NK-cell function. Combining anti-NKG2A and anti-PD-L1 therapies restores complete response in heterogeneous MHC-I murine models, dependent on the presence of activated, tumor-infiltrating NK and CD8+ T cells. These results suggest that similar strategies may enhance patient benefit in clinical trials.

SIGNIFICANCE

Clinical resistance to immunotherapy is common in breast cancer, and many patients will likely require combination therapy to maximize immunotherapeutic benefit. This study demonstrates that heterogeneous MHC-I expression drives resistance to anti-PD-L1 therapy and exposes NKG2A on NK cells as a target to overcome resistance. This article is featured in Selected Articles from This Issue, p. 201.

Tumor reactive γδ T cells contribute to a complete response to PD-1 blockade in a Merkel cell carcinoma patient

Immunotherapies targeting PD-1/PD-L1 are now widely used in the clinic to treat a variety of malignancies. While most of the research on T cell exhaustion and PD-1 blockade has been focused on conventional αβ T cells, the contribution of innate-like T cells such as γδ T cells to anti-PD-1/PD-L1 mediated therapy is limited. Here we show that tumor reactive γδ T cells respond to PD-1 blockade in a Merkel cell carcinoma (MCC) patient experiencing a complete response to therapy. We find clonally expanded γδ T cells in the blood and tumor after pembrolizumab treatment, and this Vγ2Vδ1 clonotype recognizes Merkel cancer cells in a TCR-dependent manner. Notably, the intra-tumoral γδ T cells in the MCC patient are characterized by higher expression of PD-1 and TIGIT, relative to conventional CD4 and CD8 T cells. Our results demonstrate that innate-like T cells could also contribute to an anti-tumor response after PD-1 blockade.

Transcriptome-level discovery of survival-associated biomarkers and therapy targets in non-small-cell lung cancer

BACKGROUND AND PURPOSE

Survival rate of patients with lung cancer has increased by over 60% in the recent two decades. With longer survival, the identification of genes associated with survival has emerged as an issue of utmost importance to uncover the most promising biomarkers and therapeutic targets.

EXPERIMENTAL APPROACH

An integrated database was set up by combining multiple independent datasets with clinical data and transcriptome-level gene expression measurements. Univariate and multivariate survival analyses were performed to identify genes with higher expression levels linked to shorter survival. The strongest genes were filtered to include only those with known druggability.

KEY RESULTS

The entire database includes 2852 tumour specimens from 17 independent cohorts. Of these, 2227 have overall survival data and 1256 samples have progression-free survival time. The most significant genes associated with survival were MIF, UBC and B2M in lung adenocarcinoma and ANXA2, CSNK2A2 and KRT18 in squamous cell carcinoma. We also aimed to reveal the best druggable targets in non-smokers lung cancer. The three most promising hits in this cohort were MDK, THY1 and PADI2. The established lung cancer cohort was added to the Kaplan-Meier plotter (https://www.kmplot.com) enabling the validation of future gene expression-based biomarkers in both the present and yet unexamined subgroups of patients.

CONCLUSIONS AND IMPLICATIONS

In this study, we established a comprehensive database of transcriptome-level data for lung cancer. The database can be utilized to identify and rank the most promising biomarkers and therapeutic targets for different subtypes of lung cancer.

Plasma Cell-Free Tumor Methylome as a Biomarker in Solid Tumors: Biology and Applications

DNA methylation is a fundamental mechanism of epigenetic control in cells and its dysregulation is strongly implicated in cancer development. Cancers possess an extensively hypomethylated genome with focal regions of hypermethylation at CPG islands. Due to the highly conserved nature of cancer-specific methylation, its detection in cell-free DNA in plasma using liquid biopsies constitutes an area of interest in biomarker research. The advent of next-generation sequencing and newer computational technologies have allowed for the development of diagnostic and prognostic biomarkers that utilize methylation profiling to diagnose disease and stratify risk. Methylome-based predictive biomarkers can determine the response to anti-cancer therapy. An additional emerging application of these biomarkers is in minimal residual disease monitoring. Several key challenges need to be addressed before cfDNA-based methylation biomarkers become fully integrated into practice. The first relates to the biology and stability of cfDNA. The second concerns the clinical validity and generalizability of methylation-based assays, many of which are cancer type-specific. The third involves their practicability, which is a stumbling block for translating technologies from bench to clinic. Future work on developing pan-cancer assays with their respective validities confirmed using well-designed, prospective clinical trials is crucial in pushing for the greater use of these tools in oncology.

Genomics in Clinical trials for Breast Cancer

Breast cancer (B.C.) still has increasing incidences and mortality rates globally. It is known that B.C. and other cancers have a very high rate of genetic heterogeneity and genomic mutations. Traditional oncology approaches have not been able to provide a lasting solution. Targeted therapeutics have been instrumental in handling the complexity and resistance associated with B.C. However, the progress of genomic technology has transformed our understanding of the genetic landscape of breast cancer, opening new avenues for improved anti-cancer therapeutics. Genomics is critical in developing tailored therapeutics and identifying patients most benefit from these treatments. The next generation of breast cancer clinical trials has incorporated next-generation sequencing technologies into the process, and we have seen benefits. These innovations have led to the approval of better-targeted therapies for patients with breast cancer. Genomics has a role to play in clinical trials, including genomic tests that have been approved, patient selection and prediction of therapeutic response. Multiple clinical trials in breast cancer have been done and are still ongoing, which have applied genomics technology. Precision medicine can be achieved in breast cancer therapy with increased efforts and advanced genomic studies in this domain. Genomics studies assist with patient outcomes improvement and oncology advancement by providing a deeper understanding of the biology behind breast cancer. This article will examine the present state of genomics in breast cancer clinical trials.

Promising and Minimally Invasive Biomarkers: Targeting Melanoma

The therapeutic landscape of malignant melanoma has been radically reformed in recent years, with novel treatments emerging in both the field of cancer immunotherapy and signalling pathway inhibition. Large-scale tumour genomic characterization has accurately classified malignant melanoma into four different genomic subtypes so far. Despite this, only somatic mutations in BRAF oncogene, as assessed in tumour biopsies, has so far become a validated predictive biomarker of treatment with small molecule inhibitors. The biology of tumour evolution and heterogeneity has uncovered the current limitations associated with decoding genomic drivers based only on a single-site tumour biopsy. There is an urgent need to develop minimally invasive biomarkers that accurately reflect the real-time evolution of melanoma and that allow for streamlined collection, analysis, and interpretation. These will enable us to face challenges with tumour tissue attainment and process and will fulfil the vision of utilizing "liquid biopsy" to guide clinical decisions, in a manner akin to how it is used in the management of haematological malignancies. In this review, we will summarize the most recent published evidence on the role of minimally invasive biomarkers in melanoma, commenting on their future potential to lead to practice-changing discoveries.

Challenges and Future Directions in the Management of Tumor Mutational Burden-High (TMB-H) Advanced Solid Malignancies

A standardized assessment of Tumor Mutational Burden (TMB) poses challenges across diverse tumor histologies, treatment modalities, and testing platforms, requiring careful consideration to ensure consistency and reproducibility. Despite clinical trials demonstrating favorable responses to immune checkpoint inhibitors (ICIs), not all patients with elevated TMB exhibit benefits, and certain tumors with a normal TMB may respond to ICIs. Therefore, a comprehensive understanding of the intricate interplay between TMB and the tumor microenvironment, as well as genomic features, is crucial to refine its predictive value. Bioinformatics advancements hold potential to improve the precision and cost-effectiveness of TMB assessments, addressing existing challenges. Similarly, integrating TMB with other biomarkers and employing comprehensive, multiomics approaches could further enhance its predictive value. Ongoing collaborative endeavors in research, standardization, and clinical validation are pivotal in harnessing the full potential of TMB as a biomarker in the clinic settings.

Complete response with pembrolizumab in recurrent squamous cell carcinoma of the oral tongue: A case report

Immunotherapies such as immune checkpoint inhibitors have shown promising results in solid tumors associated with BRCA2, but there are no consistent predictors for who will respond to immunotherapy. More research is needed on the impact of this mutation in head and neck squamous cell carcinomas, particularly for recurrent/metastatic tumors. We report a case of stage IV oral squamous cell carcinoma associated with BRCA2 mutation that achieved complete remission with pembrolizumab treatment for relapsed disease.

Circulating tumor DNA as liquid biopsy in lung cancer: Biological characteristics and clinical integration

Lung cancer maintains high morbidity and mortality rate globally despite significant advancements in diagnosis and treatment in the era of precision medicine. Pathological analysis of tumor tissue, the current gold standard for lung cancer diagnosis, is intrusive and intrinsically confined to evaluating the limited amount of tissues that could be physically extracted. However, tissue biopsy has several limitations, including the invasiveness of the procedure and difficulty in obtaining samples for patients at advanced stages., there Additionally,has been no major breakthrough in tumor biomarkers with high specificity and sensitivity, particularly for early-stage lung cancer. Liquid biopsy has been considered a feasible auxiliary tool for tearly dianosis, evaluating treatment responses and monitoring prognosis of lung cancer. Circulating tumor DNA (ctDNA), an ideal biomarker of liquid biopsy, has emerged as one of the most reliable tools for monitoring tumor processes at molecular levels. Herein, this review focuses on tumor heterogeneity to elucidate the superiority of liquid biopsy and retrospectively discussdeciphersolution. We systematically elaborate ctDNA biological characteristics, introduce methods for ctDNA detection, and discuss the current role of plasma ctDNA in lung cancer management. Finally, we summarize the drawbacks of ctDNA analysis and highlight its potential clinical application in lung cancer.

Circulating Tumor DNA Monitoring on Chemo-immunotherapy for Risk Stratification in Advanced Non-Small Cell Lung Cancer

PURPOSE

Chemoimmunotherapy (chemoIO) is a prevalent first-line treatment for advanced driver-negative non-small cell lung cancer (NSCLC), with maintenance therapy given after induction. However, there is significant clinical variability in the duration, dosing, and timing of maintenance therapy after induction chemoIO. We used circulating tumor DNA (ctDNA) monitoring to inform outcomes in patients with advanced NSCLC receiving chemoIO.

EXPERIMENTAL DESIGN

This retrospective study included 221 patients from a phase III trial of atezolizumab+carboplatin+nab-paclitaxel versus carboplatin+nab-paclitaxel in squamous NSCLC (IMpower131). ctDNA monitoring used the FoundationOne Tracker involving comprehensive genomic profiling of pretreatment tumor tissue, variant selection using an algorithm to exclude nontumor variants, and multiplex PCR of up to 16 variants to detect and quantify ctDNA.

RESULTS

ctDNA was detected (ctDNA+) in 96% of pretreatment samples (median, 93 mean tumor molecules/mL), and similar ctDNA dynamics were noted across treatment arms during chemoIO. ctDNA decrease from baseline to C4D1 was associated with improved outcomes across multiple cutoffs for patients treated with chemoIO. When including patients with missing plasma or ctDNA- at baseline, patients with ctDNA- at C4D1 (clearance), had more favorable progression-free survival (median 8.8 vs. 3.5 months; HR, 0.32;0.20-0.52) and OS (median not reached vs. 8.9 months; HR, 0.22; 0.12-0.39) from C4D1 than ctDNA+ patients.

CONCLUSIONS

ctDNA monitoring during induction chemoIO can inform treatment outcomes in patients with advanced NSCLC. Importantly, monitoring remains feasible and informative for patients missing baseline ctDNA. ctDNA testing during induction chemoIO identifies patients at higher risk for disease progression and may inform patient selection for novel personalized maintenance or second-line treatment strategies.

Contribution of m5C RNA Modification-Related Genes to Prognosis and Immunotherapy Prediction in Patients with Ovarian Cancer

Background

5-Methylcytosine (m5C) RNA modification is closely implicated in the occurrence of a variety of cancers. Here, we established a novel prognostic signature for ovarian cancer (OC) patients based on m5C RNA modification-related genes and explored the correlation between these genes with the tumor immune microenvironment.

Methods

Methylated-RNA immunoprecipitation sequencing helped us to identify candidate genes related to m5C RNA modification at first. Based on TCGA database, we screened the differentially expressed candidate genes related to the prognosis and constructed a prognostic model using LASSO Cox regression analyses. Notably, the accuracy of the model was evaluated by Kaplan-Meier analysis and receiver operator characteristic curves. Independent prognostic risk factors were investigated by Cox proportional hazard model. Furthermore, we also analyzed the biological functions and pathways involved in the signature. Finally, the immune response of the model was visualized in great detail.

Results

Totally, 2,493 candidate genes proved to be involved in m5C modification of RNA for OC. We developed a signature with prognostic value consisting of six m5C RNA modification-related genes. Specially, samples have been split into two cohorts with low- and high-risk scores according to the model, in which the low-risk OC patients exhibited dramatically better overall survival time than those with high-risk scores. Besides, not only was this model a prognostic factor independent of other clinical characteristics but it predicted the intensity of the immune response in OC. Significantly, the accuracy and availability of the signature were verified by ICGC database.

Conclusions

Our study bridged the gap between m5C RNA modification and the prognosis of OC and was expected to provide an effective breakthrough for immunotherapy in OC patients.

Quantifying the impact of immunotherapy on RNA dynamics in cancer

BACKGROUND

Checkpoint inhibitor (CPI) immunotherapies have provided durable clinical responses across a range of solid tumor types for some patients with cancer. Nonetheless, response rates to CPI vary greatly between cancer types. Resolving intratumor transcriptomic changes induced by CPI may improve our understanding of the mechanisms of sensitivity and resistance.

METHODS

We assembled a cohort of longitudinal pre-therapy and on-therapy samples from 174 patients treated with CPI across six cancer types by leveraging transcriptomic sequencing data from five studies.

RESULTS

Meta-analyses of published RNA markers revealed an on-therapy pattern of immune reinvigoration in patients with breast cancer, which was not discernible pre-therapy, providing biological insight into the impact of CPI on the breast cancer immune microenvironment. We identified 98 breast cancer-specific correlates of CPI response, including 13 genes which are known IO targets, such as toll-like receptors TLR1, TLR4, and TLR8, that could hold potential as combination targets for patients with breast cancer receiving CPI treatment. Furthermore, we demonstrate that a subset of response genes identified in breast cancer are already highly expressed pre-therapy in melanoma, and additionally we establish divergent RNA dynamics between breast cancer and melanoma following CPI treatment, which may suggest distinct immune microenvironments between the two cancer types.

CONCLUSIONS

Overall, delineating longitudinal RNA dynamics following CPI therapy sheds light on the mechanisms underlying diverging response trajectories, and identifies putative targets for combination therapy.

Breaking the mold: Overcoming resistance to immune checkpoint inhibitors

Immune checkpoint blockade-based therapies are effective against a sorts of cancers. However, drug resistance is a problem that cannot be ignored. This review intends to elucidate the mechanisms underlying drug tolerance induced by PD-1/PD-L1 inhibitors, as well as to outline proposed mechanism-based combination therapies and small molecule drugs that target intrinsic immunity and immune checkpoints. According to the differences of patients and types of cancer, the optimization of individualized combination therapy will help to enhance PD-1/PD-L1-mediated immunoregulation, reduce chemotherapy resistance, and provide new ideas for chemotherapy-resistant cancer.

Autoimmune PaneLs as PrEdictors of Toxicity in Patients TReated with Immune Checkpoint InhibiTors (ALERT)

BACKGROUND

Immune-checkpoint inhibitors (ICI) can lead to immune-related adverse events (irAEs) in a significant proportion of patients. The mechanisms underlying irAEs development are mostly unknown and might involve multiple immune effectors, such as T cells, B cells and autoantibodies (AutoAb).

METHODS

We used custom autoantigen (AutoAg) microarrays to profile AutoAb related to irAEs in patients receiving ICI. Plasma was collected before and after ICI from cancer patients participating in two clinical trials (NCT03686202, NCT02644369). A one-time collection was obtained from healthy controls for comparison. Custom arrays with 162 autoAg were used to detect IgG and IgM reactivities. Differences of median fluorescent intensity (MFI) were analyzed with Wilcoxon sign rank test and Kruskal-Wallis test. MFI 500 was used as threshold to define autoAb reactivity.

RESULTS

A total of 114 patients and 14 healthy controls were included in this study. irAEs of grade (G) ≥ 2 occurred in 37/114 patients (32%). We observed a greater number of IgG and IgM reactivities in pre-ICI collections from patients versus healthy controls (62 vs 32 p < 0.001). Patients experiencing irAEs G ≥ 2 demonstrated pre-ICI IgG reactivity to a greater number of AutoAg than patients who did not develop irAEs (39 vs 33 p = 0.040). We observed post-treatment increase of IgM reactivities in subjects experiencing irAEs G ≥ 2 (29 vs 35, p = 0.021) and a decrease of IgG levels after steroids (38 vs 28, p = 0.009).

CONCLUSIONS

Overall, these results support the potential role of autoAb in irAEs etiology and evolution. A prospective study is ongoing to validate our findings (NCT04107311).

Comparison of different predictive biomarker testing assays for PD-1/PD-L1 checkpoint inhibitors response: a systematic review and network meta-analysis

Background

Accurate prediction of efficacy of programmed cell death 1 (PD-1)/programmed cell death ligand 1 (PD-L1) checkpoint inhibitors is of critical importance. To address this issue, a network meta-analysis (NMA) comparing existing common measurements for curative effect of PD-1/PD-L1 monotherapy was conducted.

Methods

We searched PubMed, Embase, the Cochrane Library database, and relevant clinical trials to find out studies published before Feb 22, 2023 that use PD-L1 immunohistochemistry (IHC), tumor mutational burden (TMB), gene expression profiling (GEP), microsatellite instability (MSI), multiplex IHC/immunofluorescence (mIHC/IF), other immunohistochemistry and hematoxylin-eosin staining (other IHC&HE) and combined assays to determine objective response rates to anti-PD-1/PD-L1 monotherapy. Study-level data were extracted from the published studies. The primary goal of this study was to evaluate the predictive efficacy and rank these assays mainly by NMA, and the second objective was to compare them in subgroup analyses. Heterogeneity, quality assessment, and result validation were also conducted by meta-analysis.

Findings

144 diagnostic index tests in 49 studies covering 5322 patients were eligible for inclusion. mIHC/IF exhibited highest sensitivity (0.76, 95% CI: 0.57-0.89), the second diagnostic odds ratio (DOR) (5.09, 95% CI: 1.35-13.90), and the second superiority index (2.86). MSI had highest specificity (0.90, 95% CI: 0.85-0.94), and DOR (6.79, 95% CI: 3.48-11.91), especially in gastrointestinal tumors. Subgroup analyses by tumor types found that mIHC/IF, and other IHC&HE demonstrated high predictive efficacy for non-small cell lung cancer (NSCLC), while PD-L1 IHC and MSI were highly efficacious in predicting the effectiveness in gastrointestinal tumors. When PD-L1 IHC was combined with TMB, the sensitivity (0.89, 95% CI: 0.82-0.94) was noticeably improved revealed by meta-analysis in all studies.

Interpretation

Considering statistical results of NMA and clinical applicability, mIHC/IF appeared to have superior performance in predicting response to anti PD-1/PD-L1 therapy. Combined assays could further improve the predictive efficacy. Prospective clinical trials involving a wider range of tumor types are needed to establish a definitive gold standard in future.

Peeling the I-Onion to Demystify Pseudoprogression

In this issue of Cancer Cell, Topp et al. analyze data from 799 patients treated with pembrolizumab beyond progression by RECIST 1.1 across six trials. Although 8.9%-24.4% of patients demonstrate a ≥30% reduction in target lesions, conversely 11%-18% of patients had a ≥20% increase. The benefits of treatment beyond progression must be carefully weighed against physical and financial toxicities.

Immune checkpoint therapy for solid tumours: clinical dilemmas and future trends

Immune-checkpoint inhibitors (ICBs), in addition to targeting CTLA-4, PD-1, and PD-L1, novel targeting LAG-3 drugs have also been approved in clinical application. With the widespread use of the drug, we must deeply analyze the dilemma of the agents and seek a breakthrough in the treatment prospect. Over the past decades, these agents have demonstrated dramatic efficacy, especially in patients with melanoma and non-small cell lung cancer (NSCLC). Nonetheless, in the field of a broad concept of solid tumours, non-specific indications, inseparable immune response and side effects, unconfirmed progressive disease, and complex regulatory networks of immune resistance are four barriers that limit its widespread application. Fortunately, the successful clinical trials of novel ICB agents and combination therapies, the advent of the era of oncolytic virus gene editing, and the breakthrough of the technical barriers of mRNA vaccines and nano-delivery systems have made remarkable breakthroughs currently. In this review, we enumerate the mechanisms of each immune checkpoint targets, associations between ICB with tumour mutation burden, key immune regulatory or resistance signalling pathways, the specific clinical evidence of the efficacy of classical targets and new targets among different tumour types and put forward dialectical thoughts on drug safety. Finally, we discuss the importance of accurate triage of ICB based on recent advances in predictive biomarkers and diagnostic testing techniques.

Tertiary lymphoid structures and B lymphocytes: a promising therapeutic strategy to fight cancer

Tertiary lymphoid structures (TLSs) are clusters of lymphoid cells with an organization that resembles that of secondary lymphoid organs. Both structures share common developmental characteristics, although TLSs usually appear in chronically inflamed non-lymphoid tissues, such as tumors. TLSs contain diverse types of immune cells, with varying degrees of spatial organization that represent different stages of maturation. These structures support both humoral and cellular immune responses, thus the correlation between the existence of TLS and clinical outcomes in cancer patients has been extensively studied. The finding that TLSs are associated with better prognosis in some types of cancer has led to the design of therapeutic strategies based on promoting the formation of these structures. Agents such as chemokines, cytokines, antibodies and cancer vaccines have been used in combination with traditional antitumor treatments to enhance TLS generation, with good results. The induction of TLS formation therefore represents a novel and promising avenue for the treatment of a number of tumor types.

Location of CD39+ T cell subpopulations within tumors predict differential outcomes in non-small cell lung cancer

PURPOSE

An improved mechanistic understanding of immunosuppressive pathways in non-small cell lung cancer (NSCLC) is important to develop novel diagnostic and therapeutic approaches. Here, we investigate the prognostic significance of the ectonucleotidases CD39 and CD73 in NSCLC.

EXPERIMENTAL DESIGN

The expression and localization of CD39, CD73 and CD103 was digitally quantified in a cohort of 162 early treatment naïve NSCLC patients using multiplex-immunofluorescence and related to patient outcome. Expression among different cell-populations was assessed via flow cytometry. Targeted RNA-Seq was performed on CD4+ and CD8+ T cells from digested NSCLC tumor tissue and single-cell RNA-Seq data was analyzed to investigate the functional significance of CD39+ T cell populations.

RESULTS

We demonstrate that flow cytometry of early untreated NSCLC patients shows an upregulation of CD39 expression in the tumor tissue among natural killer (NK) cells, fibroblasts and T cells. CD73 expression is mainly found among fibroblasts and Epcam+cells in the tumor tissue. Multiplex Immunofluorescence in a cohort of 162 early untreated NSCLC patients demonstrates that CD39 expression is mainly localized in the tumor stroma while CD73 expression is equally distributed between tumor nest and stroma, and high expression of CD39 and CD73 in the tumor stroma is associated with poor recurrence-free survival (RFS) at 5 years. Additionally, we find that CD8+T cells located in the tumor nest express CD103 and the density of CD39+CD103+CD8+ T cells in the tumor nest predicts improved RFS at 5 years. Targeted RNA-Seq shows that the tumor microenvironment of NSCLC upregulates regulatory pathways in CD4+ T cells and exhaustion in CD8+ T cells, and analysis of a single cell RNA sequencing dataset shows that CD39+CD4+ cells are enriched in Treg signature gene-sets, and CD39+CD103+ cytotoxic T lymphocyte show gene signatures indicative of an exhausted cytotoxic phenotype with upregulated expression of CXCL13.

CONCLUSIONS

Knowledge of patterns of distribution and location are required to understand the prognostic impact of CD39+ T cell populations in NSCLC. This study provides an improved understanding of spatial and functional characteristics of CD39+ T cells and their significance to patient outcome.

MGME1 associates with poor prognosis and is vital for cell proliferation in lower-grade glioma

OBJECTIVE

Mitochondrial genome maintenance exonuclease 1 (MGME1) is associated with DNA depletion, deletion, duplication, and rearrangement. However, the function of MGME1 in tumors, especially lower-grade gliomas (LGGs), has not been established.

METHODS

Pan-cancer analysis was used to define the expression patterns and prognostic value of MGME1 in various cancers. Subsequently, we systematically determined the associations between MGME1 expression and clinicopathological characteristics, prognosis, biological functions, immune characteristics, genomic mutations, and therapeutic responses of LGGs based on their expression patterns. The expression level and specific functions of MGME1 in LGGs was detected by conducting in vitro experiments.

RESULTS

Abnormally enhanced and high MGME1 expressions were associated with poor prognoses of various tumors, including LGG. Multivariate and univariate Cox regression analyses manifested that MGME1 expression was an independent prognostic biomarker for LGG. The immune-related signatures, infiltration of immune cells, immune checkpoint genes (ICPGs), copy number alteration (CNA), tumor mutation burden (TMB), and treatment responses of LGG patients were associated with the expression of MGME1. The in vitro experiments affirmed that MGME1 was elevated and tightly connected with the cell proliferation and cell cycle in LGG.

CONCLUSIONS

MGME1 is an independent prognostic biomarker and closely related to the cell proliferation in LGG.

Multimodal immunogenomic biomarker analysis of tumors from pediatric patients enrolled to a phase 1-2 study of single-agent atezolizumab

We report herein an exploratory biomarker analysis of refractory tumors collected from pediatric patients before atezolizumab therapy (iMATRIX-atezolizumab, NCT02541604 ). Elevated levels of CD8⁺ T cells and PD-L1 were associated with progression-free survival and a diverse baseline infiltrating T-cell receptor repertoire was prognostic. Differential gene expression analysis revealed elevated expression of CALCA (preprocalcitonin) and CCDC183 (highly expressed in testes) in patients who experienced clinical activity, suggesting that tumor neoantigens from these genes may contribute to immune response. In patients who experienced partial response or stable disease, elevated Igα2 expression correlated with T- and B-cell infiltration, suggesting that tertiary lymphoid structures existed in these patients' tumors. Consensus gene co-expression network analysis identified core cellular pathways that may play a role in antitumor immunity. Our study uncovers features associated with response to immune-checkpoint inhibition in pediatric patients with cancer and provides biological and translational insights to guide prospective biomarker profiling in future clinical trials.

T follicular helper cells in cancer

T follicular helper (Tfh) cells provide essential help to B cells for effective antibody-mediated immune responses. Although the crucial function of these CD4⁺ T cells in infection and vaccination is well established, their involvement in cancer is only beginning to emerge. Increased numbers of Tfh cells in Tfh cell-derived or B cell-associated malignancies are often associated with an unfavorable outcome, whereas in various solid organ tumor types of non-lymphocytic origin, their presence frequently coincides with a better prognosis. We discuss recent advances in understanding how Tfh cell crosstalk with B cells and CD8⁺ T cells in secondary and tertiary lymphoid structures (TLS) enhances antitumor immunity, but may also exacerbate immune-related adverse events (irAEs) such as autoimmunity during immune checkpoint blockade (ICB) and cancer immunotherapy.

Association Between Biomarkers and Clinical Outcomes of Pembrolizumab Monotherapy in Patients With Metastatic Triple-Negative Breast Cancer: KEYNOTE-086 Exploratory Analysis

PURPOSE

In the two-cohort phase II KEYNOTE-086 study (ClinicalTrials.gov identifier: NCT02447003), first-line and second-line or later pembrolizumab monotherapy demonstrated antitumor activity in metastatic triple-negative breast cancer (mTNBC; N = 254). This exploratory analysis evaluates the association between prespecified molecular biomarkers and clinical outcomes.

METHODS

Cohort A enrolled patients with disease progression after one or more systemic therapies for metastatic disease irrespective of PD-L1 status; Cohort B enrolled patients with previously untreated PD-L1-positive (combined positive score [CPS] ≥ 1) metastatic disease. The association between the following biomarkers as continuous variables and clinical outcomes (objective response rate [ORR], progression-free survival [PFS], and overall survival [OS]) was evaluated: PD-L1 CPS (immunohistochemistry), cluster of differentiation 8 (CD8; immunohistochemistry), stromal tumor-infiltrating lymphocyte (sTIL; hematoxylin and eosin staining), tumor mutational burden (TMB; whole-exome sequencing [WES]), homologous recombination deficiency-loss of heterozygosity, mutational signature 3 (WES), mutational signature 2 (apolipoprotein B mRNA editing catalytic polypeptide-like; WES), T-cell-inflamed gene expression profile (Tcell_infGEP; RNA sequencing), and 10 non-Tcell_infGEP signatures (RNA sequencing); Wald test P values were calculated, and significance was prespecified at α = 0.05.

RESULTS

In the combined cohorts (A and B), PD-L1 (P = .040), CD8 (P < .001), sTILs (P = .012), TMB (P = .007), and Tcell_infGEP (P = .011) were significantly associated with ORR; CD8 (P < .001), TMB (P = .034), Signature 3 (P = .009), and Tcell_infGEP (P = .002) with PFS; and CD8 (P < .001), sTILs (P = .004), TMB (P = .025), and Tcell_infGEP (P = .001) with OS. None of the non-Tcell_infGEP signatures were associated with outcomes of pembrolizumab after adjusting for the Tcell_infGEP.

CONCLUSION

In this exploratory biomarker analysis from KEYNOTE-086, baseline tumor PD-L1, CD8, sTILs, TMB, and Tcell_infGEP were associated with improved clinical outcomes of pembrolizumab and may help identify patients with mTNBC who are most likely to respond to pembrolizumab monotherapy.

Bypassing anti-PD-(L)1 therapy: Mechanisms and management strategies

Resistance to immune checkpoint inhibitors (ICIs) is a major issue of the current era in cancer immunotherapy. Immune evasion is a multi-factorial event, which occurs generally at a base of cold immunity. Despite advances in the field, there are still unsolved challenges about how to combat checkpoint hijacked by tumor cells and what are complementary treatment strategies to render durable anti-tumor outcomes. A point is that anti-programed death-1 receptor (PD-1)/anti-programmed death-ligand 1 (PD-L1) is not the solo path of immune escape, and responses in many types of solid tumors to the PD-1/PD-L1 inhibitors are not satisfactory. Thus, seeking mechanisms inter-connecting tumor with its immune ecosystem nearby unravel more about resistance mechanisms so as to develop methods for sustained reinvigoration of immune activity against cancer. In this review, we aimed to discuss about common and specific paths taken by tumor cells to evade immune surveillance, describing novel detection strategies, as well as suggesting some approaches to recover tumor sensitivity to the anti-PD-(L)1 therapy based on the current knowledge.

Response to Immune Checkpoint Inhibitors Is Affected by Deregulations in the Antigen Presentation Machinery: A Systematic Review and Meta-Analysis

Immune checkpoint inhibitors (ICI) targeting programmed death 1 (PD-1), its ligand (PD-L1), or cytotoxic T-lymphocyte antigen 4 (CTLA-4) have shown promising results against multiple cancers, where they reactivate exhausted T cells primed to eliminate tumor cells. ICI therapies have been particularly successful in hypermutated cancers infiltrated with lymphocytes. However, resistance may appear in tumors evading the immune system through alternative mechanisms than the PD-1/PD-L1 or CTLA-4 pathways. A systematic pan-cancer literature search was conducted to examine the association between alternative immune evasion mechanisms via the antigen presentation machinery (APM) and resistance towards ICI treatments targeting PD-1 (pembrolizumab and nivolumab), PD-L1 (durvalumab, avelumab, and atezolizumab), and CTLA-4 (ipilimumab). The APM proteins included the human leucocyte antigen (HLA) class I, its subunit beta-2 microglobulin (B2M), the transporter associated with antigen processing (TAP) 1, TAP2, and the NOD-like receptor family CARD domain containing 5 (NLRC5). In total, 18 cohort studies (including 21 original study cohorts) containing 966 eligible patients and 9 case studies including 12 patients were reviewed. Defects in the APM significantly predicted poor clinical benefit with an odds ratio (OR) of 0.39 (95% CI 0.24−0.63, p < 0.001). The effect was non-significant, when considering complete and partial responses only (OR = 0.52, 95% CI 0.18−1.47, p = 0.216). In summary, the APM contains important targets for tumorigenic alterations which may explain insensitivity towards ICI therapy.

Leveraging big data of immune checkpoint blockade response identifies novel potential targets

BACKGROUND

The development of immune checkpoint blockade (ICB) has changed the way we treat various cancers. While ICB produces durable survival benefits in a number of malignancies, a large proportion of treated patients do not derive clinical benefit. Recent clinical profiling studies have shed light on molecular features and mechanisms that modulate response to ICB. Nevertheless, none of these identified molecular features were investigated in large enough cohorts to be of clinical value.

MATERIALS AND METHODS

Literature review was carried out to identify relevant studies including clinical dataset of patients treated with ICB [anti-programmed cell death protein 1 (PD-1)/programmed death-ligand 1 (PD-L1), anti-cytotoxic T-lymphocyte antigen 4 (CTLA-4) or the combination] and available sequencing data. Tumor mutational burden (TMB) and 37 previously reported gene expression (GE) signatures were computed with respect to the original publication. Biomarker association with ICB response (IR) and survival (progression-free survival/overall survival) was investigated separately within each study and combined together for meta-analysis.

RESULTS

We carried out a comparative meta-analysis of genomic and transcriptomic biomarkers of IRs in over 3600 patients across 12 tumor types and implemented an open-source web application (predictIO.ca) for exploration. TMB and 21/37 gene signatures were predictive of IRs across tumor types. We next developed a de novo GE signature (PredictIO) from our pan-cancer analysis and demonstrated its superior predictive value over other biomarkers. To identify novel targets, we computed the T-cell dysfunction score for each gene within PredictIO and their ability to predict dual PD-1/CTLA-4 blockade in mice. Two genes, F2RL1 (encoding protease-activated receptor-2) and RBFOX2 (encoding RNA-binding motif protein 9), were concurrently associated with worse ICB clinical outcomes, T-cell dysfunction in ICB-naive patients and resistance to dual PD-1/CTLA-4 blockade in preclinical models.

CONCLUSION

Our study highlights the potential of large-scale meta-analyses in identifying novel biomarkers and potential therapeutic targets for cancer immunotherapy.

A novel immune signature predicts immunotherapy responsiveness and reveals the landscape of the tumor immune microenvironment in head and neck squamous cell carcinoma

Background: Immune-checkpoint blockade (ICB) has been routinely implemented to treat head and neck squamous cell carcinoma (HNSCC) patients. However, only a few patients benefit from immune checkpoint inhibitor (ICI) therapies.

Methods: In this study, we used a combined cohort (including the GSE41613, GSE65858, TCGA, and CELL cohorts) to identify hub genes significantly associated with ICB and activated CD8+ T-cell gene signatures. We performed single‐sample gene set enrichment analysis (ssGSEA) to quantify the expression of hub genes; we then constructed a novel immune signature named “the IMS” that can predict immunotherapy responsiveness, prognosis, immune infiltration, and clinical characteristics. Data from the GSE102349 external cohort and the pembrolizumab cohort obtained from a clinical trial were used to validate the efficiency of the IMS. In addition, we revealed potential mechanisms of the antitumor response by analyzing the HNSCC single-cell database. Finally, we used the LASSO algorithm to build an IMS-related risk model.

Results: The high IMS group was associated with significant immune activation, better prognosis, and increased immunotherapy responsiveness; thus, the IMS potentially represents a candidate biomarker for ICB. Moreover, a tumor microenvironment with a higher IMS underwent remarkable metabolic reprogramming characterized by enrichment in the glycolysis/gluconeogenesis, oxidative phosphorylation, and citrate cycle (TCA cycle) pathways. We also revealed key information on cellular crosstalk between the IMS and other immune lineages, which may mechanistically explain immune escape. In addition, we constructed and validated a risk prediction model (CD2, TBC1D10C, and CD3E) that could stratify HNSCC patients based on survival and response to ICB treatment.

Conclusion: IMS is a signature closely correlated with the tumor immune microenvironment. The findings of this study contribute to the understanding of the immune landscape in HNSCC patients. IMS may aid in the clinical management of HNSCC patients through the identification of effective immunotherapies for specific patients.

Solving the puzzle of what makes immunotherapies work

The rapid adoption of immune checkpoint blockade (ICB) therapies has led to a need to understand the mechanistic drivers of efficacy and the identification of novel biomarkers that enrich for patients who benefit from ICB therapy. Here, we provide a perspective on emerging biomarker candidates, their underlying biological mechanisms, and how they may fit into the current landscape of ICB biomarkers. We discuss new frameworks to identify and evaluate biomarker candidates and review the opportunities and challenges of utilizing biomarker-derived models to facilitate the development of new immunotherapies.

Transcriptome profiles of fatty acid metabolism-related genes and immune infiltrates identify hot tumors for immunotherapy in cutaneous melanoma

Background: Immunotherapy with checkpoint inhibitors usually has a low response rate in some cutaneous melanoma (CM) cases due to its cold nature. Hence, identification of hot tumors is important to improve the immunotherapeutic efficacy and prognoses of CMs.

Methods: Fatty acid (FA) metabolism-related genes were extracted from the Gene Set Enrichment Analysis and used in the non-negative matrix factorization (NMF), copy number variation frequency, tumor mutation burden (TMB), and immune-related analyses, such as immunophenoscore (IPS). We generate a risk model and a nomogram for predicting patient prognoses and predicted the potential drugs for therapies using the Connectivity Map. Moreover, the NMF and the risk model were validated in a cohort of cases in the GSE65904 and GSE54467. At last, immunohistochemistry (IHC) was used for further validation.

Results: Based on the NMF of 11 FA metabolism-related DEGs, CM cases were stratified into two clusters. Cluster 2 cases had the characteristics of a hot tumor with higher immune infiltration levels, higher immune checkpoint (IC) molecules expression levels, higher TMB, and more sensitivity to immunotherapy and more potential immunotherapeutic drugs and were identified as hot tumors for immunotherapy. The risk model and nomogram displayed excellent predictor values. In addition, there were more small potential molecule drugs for therapies of CM patients, such as ambroxol. In immunohistochemistry (IHC), we could find that expression of PLA2G2D, ACOXL, and KMO was upregulated in CM tissues, while the expression of IL4I1, BBOX1, and CIDEA was reversed or not detected.

Conclusion: The transcriptome profiles of FA metabolism-related genes were effective for distinguishing CM into hot–cold tumors. Our findings may be valuable for development of effective immunotherapy for CM patients and for proposing new therapy strategies.

Identification of Novel Molecular Subgroups in Esophageal Adenocarcinoma to Predict Response to Neo-Adjuvant Therapies

Simple Summary

Gene expression of esophageal adenocarcinoma is highly heterogeneous. In general, these cancers have poor prognosis and unpredictable responses to chemo- and radiotherapy. Investigating expression profiles from RNA from pre-treatment biopsies are highly attractive to investigate the existence of diverse biological groups and signatures associated with the clinical response to current treatment strategies. We identified and validated three distinct biological esophageal adenocarcinoma subgroups and identified immune signatures with association to therapy response using RNA sequencing. These findings aid in understanding biological mechanisms’ underlying response to neo-adjuvant treatment.

Abstract

Esophageal adenocarcinoma (EAC) is a highly aggressive cancer and its response to chemo- and radiotherapy is unpredictable. EACs are highly heterogeneous at the molecular level. The aim of this study was to perform gene expression analysis of EACs to identify distinct molecular subgroups and to investigate expression signatures in relation to treatment response. In this prospective observational study, RNA sequencing was performed on pre-treatment endoscopic EAC biopsies from a discovery cohort included between 2012 and 2017 in one Dutch Academic Center. Four additional cohorts were analyzed for validation purposes. Unsupervised clustering was performed on 107 patients to identify biological EAC subgroups. Specific cell signaling profiles were identified and evaluated with respect to predicting response to neo-adjuvant chemo(radio)therapy. We identified and validated three distinct biological EAC subgroups, characterized by (1) p38 MAPK/Toll-like receptor signaling; (2) activated immune system; and (3) impaired cell adhesion. Subgroup 1 was associated with poor response to chemo-radiotherapy. Moreover, an immune signature with activated T-cell signaling, and increased number of activated CD4 T memory cells, neutrophils and dendritic cells, and decreased M1 and M2 macrophages and plasma cells, was associated with complete histopathological response. This study provides a novel molecular classification for EACs. EAC subgroup 1 proved to be more therapy-resistant, while immune signaling was increased in patients with complete response to chemo-radiotherapy. Our findings give insight into the biology of EACs and in cellular signaling mechanisms underlying response to neo-adjuvant treatment. Future implementation of this classification will improve patient stratification and enhance the development of targeted therapies.

Integrating circulating-free DNA (cfDNA) analysis into clinical practice: opportunities and challenges

In the current era of precision medicine, the identification of genomic alterations has revolutionised the management of patients with solid tumours. Recent advances in the detection and characterisation of circulating tumour DNA (ctDNA) have enabled the integration of liquid biopsy into clinical practice for molecular profiling. ctDNA has also emerged as a promising biomarker for prognostication, monitoring disease response, detection of minimal residual disease and early diagnosis. In this Review, we discuss current and future clinical applications of ctDNA primarily in non-small cell lung cancer in addition to other solid tumours.

Development and validation of a combined ferroptosis- and pyroptosis-related gene signatures for the prediction of clinical outcomes in lung adenocarcinoma

Lung adenocarcinoma (LUAD) is a very heterogeneous cancer with a bad prognosis. Pyroptosis and ferroptosis are two newly discovered forms of regulated cell death, which can trigger inflammation-related immunosuppression in tumor microenvironments, thereby promoting tumor growth. So far, there has been no thorough systematic investigation of the predictive values of ferroptosis and pyroptosis-related genes in LUAD. Therefore, in this study, we conducted a combined analyses in the gene expression of ferroptosis and pyroptosis and identified four distinct subgroups: immobility, ferroptosis, pyroptosis, and mixed. The gene sets most closely associated to both ferroptosis and pyroptosis were utilized to build a risk prediction model based on their variations in survival and biological activities. More importantly, our conclusions from bioinformatics analyses were validated by external experiments in patients with LUAD. In conclusion, the establishment of LUAD subgroups based on the ferroptosis- and pyroptosis-related gene expression profile provided new insights into understanding the roles of programmed cell death in oncogenesis and might contribute to the development of individualized therapy.

Interpretable Machine Learning Models to Predict the Resistance of Breast Cancer Patients to Doxorubicin from Their microRNA Profiles

Doxorubicin is a common treatment for breast cancer. However, not all patients respond to this drug, which sometimes causes life-threatening side effects. Accurately anticipating doxorubicin-resistant patients would therefore permit to spare them this risk while considering alternative treatments without delay. Stratifying patients based on molecular markers in their pretreatment tumors is a promising approach to advance toward this ambitious goal, but single-gene gene markers such as HER2 expression have not shown to be sufficiently predictive. The recent availability of matched doxorubicin-response and diverse molecular profiles across breast cancer patients permits now analysis at a much larger scale. 16 machine learning algorithms and 8 molecular profiles are systematically evaluated on the same cohort of patients. Only 2 of the 128 resulting models are substantially predictive, showing that they can be easily missed by a standard-scale analysis. The best model is classification and regression tree (CART) nonlinearly combining 4 selected miRNA isoforms to predict doxorubicin response (median Matthew correlation coefficient (MCC) and area under the curve (AUC) of 0.56 and 0.80, respectively). By contrast, HER2 expression is significantly less predictive (median MCC and AUC of 0.14 and 0.57, respectively). As the predictive accuracy of this CART model increases with larger training sets, its update with future data should result in even better accuracy.

Dynamic CD8+ T Cell Cooperation with Macrophages and Monocytes for Successful Cancer Immunotherapy

Simple Summary

Innate and adaptive immunity mutually regulate one another in a dynamic fashion during immune responses. In infectious contexts, positive interactions between macrophages, monocytes and T cells are well recognized, but this is not the case in the field of cancer, where the growth of tumors disturbs the immune response. However, recent advances revealed that successful immunotherapy profoundly remodels the tumor microenvironment, promoting the activation of both T cells and myeloid cells. This review highlights the studies that hint at positive CD8⁺ T cell cooperation with monocytes and macrophages in this context, and discusses the potential mechanisms behind this.

Abstract

The essential roles endorsed by macrophages and monocytes are well established in response to infections, where they contribute to launching the differentiation of specific T-lymphocytes for long-term protection. This knowledge is the result of dynamic studies that can inspire the cancer field, particularly now that cancer immunotherapies elicit some tumor regression. Indeed, immune responses to cancer have mainly been studied after tumors have escaped immune attacks. In particular, the suppressive functions of macrophages were revealed in this context, introducing an obvious bias across the literature. In this review, we will focus on the ways inwhich monocytes and macrophages cooperate with T-lymphocytes, leading to successful immune responses. We will bring together the preclinical studies that have revealed the existence of such positive cooperation in the cancer field, and we will place particular emphasis on proposing the underlying mechanisms. Finally, we will give some perspectives to decipher the functional roles of such T-cell and myeloid cell interactions in the frame of human cancer immunotherapy.

Indoleamine 2,3-Dioxygenase Immune Status as a Potential Biomarker of Radioiodine Efficacy for Advanced Distant Metastatic Differentiated Thyroid Cancer

Purpose

Host immunity influences the impact of cancer therapy but the effect of immune status in radioiodine (RAI)-treated differentiated thyroid cancer (DTC) remains obscure. Here we investigated indoleamine 2,3-dioxygenase (IDO) activity as a biomarker of response to RAI in patients with distant metastatic DTC (dmDTC).

Methods

Patients with dmDTC receiving RAI were evaluated for serum IDO activity (kynurenine and kynurenine:tryptophan ratio) at baseline and 3 months after RAI. The optimal cut-off value for these biomarkers to predict response was established by receiver operating characteristic analysis. The relationship between disease outcomes, overall survival (OS) and progression-free survival (PFS), and IDO activity levels was studied.

Results

Higher baseline kynurenine:tryptophan ratio (&gt;2.46) was correlated with poorer RAI response as well as shorter median PFS (45 mo versus not reached, p=0.002) and OS (78 mo versus not reached, p=0.035). High baseline kynurenine:tryptophan ratio was also correlated with a reduced number of tumor-infiltrating lymphocytes. Higher post/pre-kynurenine ratio (&gt;1.69) was associated with survival endpoints: shorter median PFS (48 mo versus not reached, p=0.002) and OS (68 mo versus not reached, p=0.010). Favorable baseline and favorable change corresponded with better PFS and OS.

Conclusions

Our results suggest that RAI also alters IDO activity in dmDTC patients. IDO activity could predict progression and survival outcomes for advanced dmDTC patients. Serum IDO biomarker levels could be used to select dmDTC likely to benefit from RAI therapy, although further studies are necessary.

Pre-encoded responsiveness to type I interferon in the peripheral immune system defines outcome of PD1 blockade therapy

Type I interferons (IFN-Is) are central regulators of anti-tumor immunity and responses to immunotherapy, but they also drive the feedback inhibition underlying therapeutic resistance. In the present study, we developed a mass cytometry approach to quantify IFN-I-stimulated protein expression across immune cells and used multi-omics to uncover pre-therapy cellular states encoding responsiveness to inflammation. Analyzing peripheral blood cells from multiple cancer types revealed that differential responsiveness to IFN-Is before anti-programmed cell death protein 1 (PD1) treatment was highly predictive of long-term survival after therapy. Unexpectedly, IFN-I hyporesponsiveness efficiently predicted long-term survival, whereas high responsiveness to IFN-I was strongly associated with treatment failure and diminished survival time. Peripheral IFN-I responsive states were not associated with tumor inflammation, identifying a disconnect between systemic immune potential and 'cold' or 'hot' tumor states. Mechanistically, IFN-I responsiveness was epigenetically imprinted before therapy, poising cells for differential inflammatory responses and dysfunctional T cell effector programs. Thus, we identify physiological cell states with clinical importance that can predict success and long-term survival of PD1-blocking immunotherapy.

Next-generation sequencing: unraveling genetic mechanisms that shape cancer immunotherapy efficacy

Immunity is governed by fundamental genetic processes. These processes shape the nature of immune cells and set the rules that dictate the myriad complex cellular interactions that power immune systems. Everything from the generation of T cell receptors and antibodies, control of epitope presentation, and recognition of pathogens by the immunoediting of cancer cells is, in large part, made possible by core genetic mechanisms and the cellular machinery that they encode. In the last decade, next-generation sequencing has been used to dissect the complexities of cancer immunity with potent effect. Sequencing of exomes and genomes has begun to reveal how the immune system recognizes “foreign” entities and distinguishes self from non-self, especially in the setting of cancer. High-throughput analyses of transcriptomes have revealed deep insights into how the tumor microenvironment affects immunotherapy efficacy. In this Review, we discuss how high-throughput sequencing has added to our understanding of how immune systems interact with cancer cells and how cancer immunotherapies work.

A local human Vδ1 T cell population is associated with survival in nonsmall-cell lung cancer

Murine tissues harbor signature γδ T cell compartments with profound yet differential impacts on carcinogenesis. Conversely, human tissue-resident γδ cells are less well defined. In the present study, we show that human lung tissues harbor a resident Vδ1 γδ T cell population. Moreover, we demonstrate that Vδ1 T cells with resident memory and effector memory phenotypes were enriched in lung tumors compared with nontumor lung tissues. Intratumoral Vδ1 T cells possessed stem-like features and were skewed toward cytolysis and helper T cell type 1 function, akin to intratumoral natural killer and CD8+ T cells considered beneficial to the patient. Indeed, ongoing remission post-surgery was significantly associated with the numbers of CD45RA-CD27- effector memory Vδ1 T cells in tumors and, most strikingly, with the numbers of CD103+ tissue-resident Vδ1 T cells in nonmalignant lung tissues. Our findings offer basic insights into human body surface immunology that collectively support integrating Vδ1 T cell biology into immunotherapeutic strategies for nonsmall cell lung cancer.

Increase in serum choline levels predicts for improved progression-free survival (PFS) in patients with advanced cancers receiving pembrolizumab

Background

Recent studies have demonstrated that T cells can induce vasodilation in a choline-acetyltransferase dependent manner, leading to an increase in T cell migration to infected tissues in response to viral infection, but its role in cancer is unclear. Choline acetyltransferase catalyzes the production of acetylcholine from choline and acetyl-CoA, however, acetylcholine is challenging to quantify due to its extremely short half-life while choline is stable. This study aims to correlate serum choline levels in patients with advanced solid tumors receiving pembrolizumab with treatment outcomes.

Methods

Blood samples were collected at baseline and at week 7 (pre-cycle 3) in patients treated with pembrolizumab in the INvestigator-initiated Phase 2 Study of Pembrolizumab Immunological Response Evaluation phase II trial (NCT02644369). Samples were analyzed for choline and circulating tumor DNA (ctDNA). Multivariable Cox models were used to assess the association between choline and overall survival (OS) and progression-free survival (PFS) when including ΔctDNA_C3 (the change in ctDNA from baseline to cycle 3), cohort, PD-L1 expression and tumor mutation burden (TMB). An independent validation cohort from the LIBERATE study (NCT03702309) included patients on early phase trials treated with a PD-1 inhibitor.

Results

A total of 106 pts were included in the analysis. With a median follow-up of 12.6 months, median PFS and OS were 1.9 and 13.7 months, respectively. An increase in serum choline level at week 7 compared with baseline (Δcholine_C3) in 81 pts was significantly associated with a better PFS (aHR 0.48, 95% CI 0.28 to 0.83, p=0.009), and a trend toward a better OS (aHR 0.64, 95% CI 0.37 to 1.12, p=0.119). A combination of ΔctDNA_C3 and Δcholine_C3 was prognostic for both OS and PFS. Multivariable analyses show Δcholine_C3 was a prognostic factor for PFS independent of ΔctDNA_C3, cohort, PD-L1 and TMB. In the independent validation cohort (n=51), an increase in serum choline at cycle 2 was associated with a trend to improved PFS.

Conclusions

This is the first exploratory report of serum choline levels in pan-cancer patients receiving pembrolizumab. The association between improved PFS and Δcholine_C3 suggests a possible role for the cholinergic system in the regulation of antitumor immunity. Further pre-clinical and clinical studies are required to validate this finding.

Trial registration number

NCT03702309.

Necroptosis is Related to Anti-PD-1 Treatment Response and Influences the Tumor Microenvironment in Head and Neck Squamous Cell Carcinoma

The latest research suggesting that necroptosis plays a vital role in immune response. However, the influence of necroptosis on tumor microenvironment (TME) remodeling and immunotherapy is still unclear. We analyzed the variations in the expression of 26 necroptosis-related molecules in HNSCC and the influence of genome changes. We investigated HNSCC samples and determined that there are two necroptosis phenotypes in HNSCC cancer, and there are significant differences in cell infiltration characteristics and survival in different necroptosis phenotypes. We used the single‐sample gene set enrichment analysis to measure the level of necroptosis in patients with NecroticScore, we confirmed that the NecroticScore can predict the prognosis of HNSCC patients and the response to immunotherapy. Patients with a high NecroticScore are more sensitive to immunotherapy and have a better prognosis. Our study suggests a significant correlation between the expression imbalance of necroptosis-related molecules and suggests necroptosis plays an important role in modeling the TME. In addition, we construct a risk prediction model which could stratify patients with HNSCC and predict patient prognosis according to this necroptosis-related molecules. In conclusion, evaluating necroptosis modification patterns contributes to enhancing our understanding of TME and can guide more effective immunotherapy strategies.

B cells and tertiary lymphoid structures as determinants of tumour immune contexture and clinical outcome

B cells are a major component of the tumour microenvironment, where they are predominantly associated with tertiary lymphoid structures (TLS). In germinal centres within mature TLS, B cell clones are selectively activated and amplified, and undergo antibody class switching and somatic hypermutation. Subsequently, these B cell clones differentiate into plasma cells that can produce IgG or IgA antibodies targeting tumour-associated antigens. In tumours without mature TLS, B cells are either scarce or differentiate into regulatory cells that produce immunosuppressive cytokines. Indeed, different tumours vary considerably in their TLS and B cell content. Notably, tumours with mature TLS, a high density of B cells and plasma cells, as well as the presence of antibodies to tumour-associated antigens are typically associated with favourable clinical outcomes and responses to immunotherapy compared with those lacking these characteristics. However, polyclonal B cell activation can also result in the formation of immune complexes that trigger the production of pro-inflammatory cytokines by macrophages and neutrophils. In complement-rich tumours, IgG antibodies can also activate the complement cascade, resulting in the production of anaphylatoxins that sustain tumour-promoting inflammation and angiogenesis. Herein, we review the phenotypic heterogeneity of intratumoural B cells and the importance of TLS in their generation as well as the potential of B cells and TLS as prognostic and predictive biomarkers. We also discuss novel therapeutic approaches that are being explored with the aim of increasing mature TLS formation, B cell differentiation and anti-tumour antibody production within tumours.