Comparison of Biomarker Modalities for Predicting Response to PD-1/PD-L1 Checkpoint Blockade: A Systematic Review and Meta-analysis

Comparing and Correcting Spectral Sensitivities between Multispectral Microscopes: A Prerequisite to Clinical Implementation

Multispectral, multiplex immunofluorescence (mIF) microscopy has been used to great effect in research to identify cellular co-expression profiles and spatial relationships within tissue, providing a myriad of diagnostic advantages. As these technologies mature, it is essential that image data from mIF microscopes is reproducible and standardizable across devices. We sought to characterize and correct differences in illumination intensity and spectral sensitivity between three multispectral microscopes. We scanned eight melanoma tissue samples twice on each microscope and calculated their average tissue region flux intensities. We found a baseline average standard deviation of 29.9% across all microscopes, scans, and samples, which was reduced to 13.9% after applying sample-specific corrections accounting for differences in the tissue shown on each slide. We used a basic calibration model to correct sample- and microscope-specific effects on overall brightness and relative brightness as a function of the image layer. We tested the generalizability of the calibration procedure and found that applying corrections to independent validation subsets of the samples reduced the variation to 2.9 ± 0.03%. Variations in the unmixed marker expressions were reduced from 15.8% to 4.4% by correcting the raw images to a single reference microscope. Our findings show that mIF microscopes can be standardized for use in clinical pathology laboratories using a relatively simple correction model.

Combination of AFP vaccine and immune checkpoint inhibitors slows hepatocellular carcinoma progression in preclinical models

Many patients with hepatocellular carcinoma (HCC) do not respond to the first-line immune checkpoint inhibitor treatment. Immunization with effective cancer vaccines is an attractive alternative approach to immunotherapy. However, its efficacy remains insufficiently evaluated in preclinical studies. Here, we investigated HCC-associated self/tumor antigen, α-fetoprotein-based (AFP-based) vaccine immunization for treating AFP (+) HCC mouse models. We found that AFP immunization effectively induced AFP-specific CD8+ T cells in vivo. However, these CD8+ T cells expressed exhaustion markers, including PD1, LAG3, and Tim3. Furthermore, the AFP vaccine effectively prevented c-MYC/Mcl1 HCC initiation when administered before tumor formation, while it was ineffective against full-blown c-MYC/Mcl1 tumors. Similarly, anti-PD1 and anti-PD-L1 monotherapy showed no efficacy in this murine HCC model. In striking contrast, AFP immunization combined with anti-PD-L1 treatment triggered significant inhibition of HCC progression in most liver tumor nodules, while in combination with anti-PD1, it induced slower tumor progression. Mechanistically, we demonstrated that HCC-intrinsic PD-L1 expression was the primary target of anti-PD-L1 in this combination therapy. Notably, the combination therapy had a similar therapeutic effect in the cMet/β-catenin mouse HCC model. These findings suggest that combining the AFP vaccine and immune checkpoint inhibitors may be effective for AFP (+) HCC treatment.

Multiplexed electrochemical assays for clinical applications

Rapid, accurate diagnoses are central to future efficient healthcare to identify diseases at early stages, avoid unnecessary treatment, and improve outcomes. Electrochemical techniques have been applied in many ways to support clinical applications by enabling the analysis of relevant disease biomarkers in user-friendly, sensitive, low-cost assays. Electrochemistry offers a launchpad for multiplexed biomarker assays that offer more accurate and precise diagnostics compared to single biomarker assays. In this short review, we underpin the importance of multiplexed analyses and provide a universal overview of current electrochemical assay strategies for multiple biomarkers. We highlight relevant examples of electrochemical methods that successfully quantify important disease biomarkers. Finally, we offer a future outlook on possible strategies that can be employed to increase throughput, sensitivity, and specificity of multiplexed electrochemical assays.

Functional binding of PD1 ligands predicts response to anti-PD1 treatment in patients with cancer

Accurate predictive biomarkers of response to immune checkpoint inhibitors (ICIs) are required for better stratifying patients with cancer to ICI treatments. Here, we present a new concept for a bioassay to predict the response to anti-PD1 therapies, which is based on measuring the binding functionality of PDL1 and PDL2 to their receptor, PD1. In detail, we developed a cell-based reporting system, called the immuno-checkpoint artificial reporter with overexpression of PD1 (IcAR-PD1) and evaluated the functionality of PDL1 and PDL2 binding in tumor cell lines, patient-derived xenografts, and fixed-tissue tumor samples obtained from patients with cancer. In a retrospective clinical study, we found that the functionality of PDL1 and PDL2 predicts response to anti-PD1 and that the functionality of PDL1 binding is a more effective predictor than PDL1 protein expression alone. Our findings suggest that assessing the functionality of ligand binding is superior to staining of protein expression for predicting response to ICIs.

Immunoscore immune checkpoint using spatial quantitative analysis of CD8 and PD-L1 markers is predictive of the efficacy of anti- PD1/PD-L1 immunotherapy in non-small cell lung cancer

BACKGROUND

Anti-PD-1 and PD-L1 antibodies (mAbs) are approved immunotherapy agents to treat metastatic non-small cell lung cancer (NSCLC) patients. Only a minority of patients responds to these treatments and biomarkers predicting response are currently lacking.

METHODS

Immunoscore-Immune-Checkpoint (Immunoscore-IC), an in vitro diagnostic test, was used on 471 routine single FFPE-slides, and the duplex-immunohistochemistry CD8 and PD-L1 staining was quantified using digital-pathology. Analytical validation was performed on two independent cohorts of 206 NSCLC patients. Quantitative parameters related to cell location, number, proximity and clustering were analysed. The Immunoscore-IC was applied on a first cohort of metastatic NSCLC patients (n = 133), treated with anti-PD1 or anti-PD-L1 mAbs. Another independent cohort (n = 132) served as validation.

FINDINGS

Anti-PDL1 clone (HDX3) has similar characteristics as anti-PD-L1 clones (22C3, SP263). Densities of PD-L1+ cells, CD8+ cells and distances between CD8+ and PD-L1+ cells were quantified and the Immunoscore-IC classification was computed. Using univariate Cox model, 5 histological dichotomised variables (CD8 free of PD-L1+ cells, CD8 clusters, CD8 cells in proximity of PD-L1 cells, CD8 density and PD-L1 cells in proximity of CD8 cells) were significantly associated with Progression-Free Survival (PFS) (all P < 0.0001). Immunoscore-IC classification improved the discriminating power of prognostic model, which included clinical variables and pathologist PD-L1 assessment. In two categories, the Immunoscore-IC risk-score was significantly associated with patients' PFS (HR = 0.39, 95% CI (0.26-0.59), P < 0.0001) and Overall Survival (OS) (HR = 0.42, 95% CI (0.27-0.65), P < 0.0001) in the training-set. Further increased hazard ratios (HR) were found when stratifying patients into three-category Immunoscore-IC (IS-IC). All patients with Low-IS-IC progressed in less than 18 months, whereas PFS at 36 months were 34% and 33% of High-IS-IC patients in the training and validation sets, respectively.

INTERPRETATION

Immunoscore-IC is a powerful tool to predict the efficacy of immune-checkpoint inhibitors (ICIs) in patients with NSCLC.

FUNDING

Veracyte, INSERM, Labex Immuno-Oncology, Transcan ERAnet European project, ARC, SIRIC, CARPEM, Ligue Contre le Cancer, ANR, QNRF, INCa France, Louis Jeantet Prize Foundation.

Multiomics technologies for comprehensive tumor microenvironment analysis in triple-negative breast cancer under neoadjuvant chemotherapy

Triple-negative breast cancer (TNBC) is one of the most aggressive breast cancer subtypes and is characterized by abundant infiltrating immune cells within the microenvironment. As standard care, chemotherapy remains the fundamental neoadjuvant treatment in TNBC, and there is increasing evidence that supplementation with immune checkpoint inhibitors may potentiate the therapeutic efficiency of neoadjuvant chemotherapy (NAC). However, 20-60% of TNBC patients still have residual tumor burden after NAC and require additional chemotherapy; therefore, it is critical to understand the dynamic change in the tumor microenvironment (TME) during treatment to help improve the rate of complete pathological response and long-term prognosis. Traditional methods, including immunohistochemistry, bulk tumor sequencing, and flow cytometry, have been applied to elucidate the TME of breast cancer, but the low resolution and throughput may overlook key information. With the development of diverse high-throughput technologies, recent reports have provided new insights into TME alterations during NAC in four fields, including tissue imaging, cytometry, next-generation sequencing, and spatial omics. In this review, we discuss the traditional methods and the latest advances in high-throughput techniques to decipher the TME of TNBC and the prospect of translating these techniques to clinical practice.

Current status of contemporary diagnostic radiotracers in the management of breast cancer: first steps toward theranostic applications

BACKGROUND

Expanding therapeutic possibilities have improved disease-related prospects for breast cancer patients. Pathological analysis on a tumor biopsy is the current reference standard biomarker used to select for treatment with targeted anticancer drugs. This method has, however, several limitations, related to intra- and intertumoral as well as spatial heterogeneity in receptor expression as well as the need to perform invasive procedures that are not always technically feasible.

MAIN BODY

In this narrative review, we focus on the current role of molecular imaging with contemporary radiotracers for positron emission tomography (PET) in breast cancer. We provide an overview of diagnostic radiotracers that represent treatment targets, such as programmed death ligand 1, human epidermal growth factor receptor 2, polyadenosine diphosphate-ribose polymerase and estrogen receptor, and discuss developments in therapeutic radionuclides for breast cancer management.

CONCLUSION

Imaging of treatment targets with PET tracers may provide a more reliable precision medicine tool to find the right treatment for the right patient at the right time. In addition to visualization of the target of treatment, theranostic trials with alpha- or beta-emitting isotopes provide a future treatment option for patients with metastatic breast cancer.

Breaking the Invisible Barriers: Unleashing the Full Potential of Immune Checkpoint Inhibitors in Oncogene-Driven Lung Adenocarcinoma

The rapid development of targeted therapy paved the way toward personalized medicine for advanced non-small cell lung cancer (NSCLC). Lung adenocarcinoma (ADC) harboring actionable genetic alternations including epidermal growth factor receptor (EGFR), anaplastic lymphoma kinase (ALK), Kirsten rat sarcoma virus (ALK) and c-ros oncogene 1 (ROS1) treated with tyrosine kinase inhibitors (TKIs) incurred lesser treatment toxicity but better therapeutic responses compared with systemic chemotherapy. Angiogenesis inhibitors targeting vascular endothelial growth factor (VEGF) have also shown an increase in overall survival (OS) for NSCLC patients. However, acquired resistance to these targeted therapies remains a major obstacle to long-term maintenance treatment for lung ADC patients. The emergence of immune checkpoint inhibitors (ICIs) against programmed cell death protein 1 (PD-1) or programmed cell death-ligand 1 (PD-L1) has changed the treatment paradigm for NSCLC tumors without actionable genetic alternations. Clinical studies have suggested, however, that there are no survival benefits with the combination of targeted therapy and ICIs. In this review, we will summarize and discuss the current knowledge on the tumor immune microenvironment and the dynamics of immune phenotypes, which could be crucial in extending the applicability of ICIs for this subpopulation of lung ADC patients.

Seven-colour multiplex immunochemistry/immunofluorescence and whole slide imaging of frozen sections

Multiplex Immunochemistry/Immunofluorescence (mIHC/IF) aims to visualise multiple biomarkers in a single tissue section and is especially powerful when used on slide scanners coupled with digital analysis tools. mIHC/IF is commonly employed in immuno-oncology to characterise features of the tumour microenvironment (TME) and correlate them with clinical parameters to guide prognostication and therapy. However, mIHC/IF can be applied to a wide range of organisms in any physiological or disease context. Recent innovation has extended the number of markers that can be detected using slide scanners well beyond the 3-4 markers typically reported in traditional fluorescence microscopy. However, these methods often require sequential antibody staining and stripping, and are not compatible with frozen tissue sections. Using fluorophore-conjugated antibodies, we have established a simple mIHC/IF imaging workflow that enables simultaneous staining and detection of seven markers in a single section of frozen tissue. Coupled with automated whole slide imaging and digital quantification, our data efficiently revealed the tumour-immune complexity in metastatic melanoma. Computational image analysis quantified the immune and stromal cell populations present in the TME as well as their spatial interactions. This imaging workflow can also be performed with an indirect labelling panel consisting of primary and secondary antibodies. Our new methods, combined with digital quantification, will provide a valuable tool for high-quality mIHC/IF assays in immuno-oncology research and other translational studies, especially in circumstances where frozen sections are required for detection of particular markers, or for applications where frozen sections may be preferred, such as spatial transcriptomics.

The prognostic significance and immune correlation of SLC10A3 in low-grade gliomas revealed by bioinformatic analysis and multiple immunohistochemistry

PURPOSE

Despite the fact that genetic risk factors contribute to low-grade gliomas (LGGs), the role of critical genes as prognostic and theraputic biomarkers is quite limited. This study is designed to comprehensively investigate the prognostic role and predictive ability of solute carrier family 10 member 3 (SLC10A3) for immunotherapy in LGGs.

METHODS

We analyzed the prognostic value of SLC10A3 from multiple datasets of LGG patients, and explored its immune correlation via multiple algorithms. Finally, we independently confirmed the clinical significance and its immune correlation using the multiplex staining assay of LGG samples on the tissue microarray.

RESULTS

SLC10A3 mRNA was up-regulated in LGGs compared with normal brain tissues, and correlated with tumor grade, histological type, IDH wide type and non-codel 1p19q. Up-regulation of SLC10A3 transcription was remarkably associated with shortened overall survival time compared with down-regulation in TCGA, CGGA and Rembrandt datasets, and SLC10A3 exhibited good predictive ability for survival outcomes among LGGs. Correlation analyses showed that SLC10A3 mRNA expression correlates well with the six immune check points and immune cells. When the expression and immune correlation of SLC10A3 at the translational level were verified via multiplex immunohistochemistry, expression of SLC10A3 protein was higher in LGG compared with normal tissues, and expression of SLC10A3 protein was correlated well with macrophage, CD4 + T cell and B cell.

CONCLUSIONS

Up-regulation of SLC10A3 mRNA is statistically associated with adverse survival outcomes and immune infiltration among LGGs. SLC10A3 might be a reliable survival predictor and a promising immunotherapy target for LGG patients.

Single-Cell Analysis in Immuno-Oncology

The complexity of the cellular and non-cellular milieu surrounding human tumors plays a decisive role in the course and outcome of disease. The high variability in the distribution of the immune and non-immune compartments within the tumor microenvironments (TME) among different patients governs the mode of their response or resistance to current immunotherapeutic approaches. Through deciphering this diversity, one can tailor patients' management to meet an individual's needs. Single-cell (sc) omics technologies have given a great boost towards this direction. This review gathers recent data about how multi-omics profiling, including the utilization of single-cell RNA sequencing (scRNA-seq), assay for transposase-accessible chromatin with sequencing (scATAC-seq), T-cell receptor sequencing (scTCR-seq), mass, tissue-based, or microfluidics cytometry, and related bioinformatics tools, contributes to the high-throughput assessment of a large number of analytes at single-cell resolution. Unravelling the exact TCR clonotype of the infiltrating T cells or pinpointing the classical or novel immune checkpoints across various cell subsets of the TME provide a boost to our comprehension of adaptive immune responses, their antigen specificity and dynamics, and grant suggestions for possible therapeutic targets. Future steps are expected to merge high-dimensional data with tissue localization data, which can serve the investigation of novel multi-modal biomarkers for the selection and/or monitoring of the optimal treatment from the current anti-cancer immunotherapeutic armamentarium.

Personalizing neoadjuvant immune-checkpoint inhibition in patients with melanoma

Neoadjuvant immune-checkpoint inhibition is a promising emerging treatment approach for patients with surgically resectable macroscopic stage III melanoma. The neoadjuvant setting provides an ideal platform for personalized therapy owing to the very homogeneous nature of the patient population and the opportunity for pathological response assessments within several weeks of starting treatment, thereby facilitating the efficient identification of novel biomarkers. A pathological response to immune-checkpoint inhibitors has been shown to be a strong surrogate marker of both recurrence-free survival and overall survival, enabling timely analyses of the efficacy of novel therapies in patients with early stage disease. Patients with a major pathological response (defined as the presence of ≤10% viable tumour cells) have a very low risk of recurrence, which offers an opportunity to adjust the extent of surgery and any subsequent adjuvant therapy and follow-up monitoring. Conversely, patients who have only a partial pathological response or who do not respond to neoadjuvant therapy still might benefit from therapy escalation and/or class switch during adjuvant therapy. In this Review, we outline the concept of a fully personalized neoadjuvant treatment approach exemplified by the current developments in neoadjuvant therapy for patients with resectable melanoma, which could provide a template for the development of similar approaches for patients with other immune-responsive cancers in the near future.

The promise and challenge of spatial omics in dissecting tumour microenvironment and the role of AI

Growing evidence supports the critical role of tumour microenvironment (TME) in tumour progression, metastases, and treatment response. However, the in-situ interplay among various TME components, particularly between immune and tumour cells, are largely unknown, hindering our understanding of how tumour progresses and responds to treatment. While mainstream single-cell omics techniques allow deep, single-cell phenotyping, they lack crucial spatial information for in-situ cell-cell interaction analysis. On the other hand, tissue-based approaches such as hematoxylin and eosin and chromogenic immunohistochemistry staining can preserve the spatial information of TME components but are limited by their low-content staining. High-content spatial profiling technologies, termed spatial omics, have greatly advanced in the past decades to overcome these limitations. These technologies continue to emerge to include more molecular features (RNAs and/or proteins) and to enhance spatial resolution, opening new opportunities for discovering novel biological knowledge, biomarkers, and therapeutic targets. These advancements also spur the need for novel computational methods to mine useful TME insights from the increasing data complexity confounded by high molecular features and spatial resolution. In this review, we present state-of-the-art spatial omics technologies, their applications, major strengths, and limitations as well as the role of artificial intelligence (AI) in TME studies.

Role of Surgical Pathologist for the Detection of Immuno-oncologic Predictive Factors in Non-small Cell Lung Cancers

Until very recently, surgery, chemotherapy, and radiation therapy have been the mainstay of treatment in non-small cell carcinomas (NSCLCs). However, recent advances in molecular immunology have unveiled some of the complexity of the mechanisms regulating cellular immune responses and led to the successful targeting of immune checkpoints in attempts to enhance antitumor T-cell responses. Immune checkpoint molecules such as cytotoxic T-lymphocyte associated protein-4, programmed cell death protein-1, and programmed death ligand (PD-L) 1 have been shown to play central roles in evading cancer immunity. Thus, these molecules have been targeted by inhibitors for the management of cancers forming the basis of immunotherapy. Advanced NSCLC has been the paradigm for the benefits of immunotherapy in any cancer. Treatment decisions are made based on the expression of PD-L1 on the tumor cells and the presence or absence of driver mutations. Patients with high PD-L1 expression (≥50%) and no driver mutations are treated with single-agent immunotherapy whereas, for all other patients with a lower level of PD-L1 expression, a combination of chemotherapy and immunotherapy is preferred. Thus, PD-L1 blockers are the only immunotherapeutic agents approved in advanced NSCLC without any oncogenic driver mutations. PD-L1 immunohistochemistry, however, may not be the best biomarker in view of its dynamic nature in time and space, and the benefits may be seen regardless of PD -L1 expression. Each immunotherapy molecule is prescribed based on the levels of PD-L1 expression as assessed by a Food and Drug Administration-approved companion diagnostic assay. Other biomarkers that have been studied include tumor mutational burden, the T-effector signature, tumor-infiltrating lymphocytes, radiomic assays, inflammation index, presence or absence of immune-related adverse events and specific driver mutations, and gut as well as local microbiome. At the current time, none of these biomarkers are routinely used in the clinical decision-making process for immunotherapy in NSCLC. However, in individual cases, they can be useful adjuncts to conventional therapy. This review describes our current understanding of the role of biomarkers as predictors of response to immune checkpoint molecules. To begin with a brief on cancer immunology in general and in NSCLC, in particular, is discussed. In the end, recent advancements in laboratory techniques for refining biomarker assays are described.

Immune-Checkpoint-Inhibitor Therapy-Principles and Relevance of Biomarkers for Pathologists and Oncologists

Immune-checkpoint-inhibitor (ICI) therapy has been one of the major advances in the treatment of a variety of advanced or metastatic tumors in recent years. Therefore, ICI-therapy is already approved in first-line therapy for multiple tumors, either as monotherapy or as combination therapy. However, there are relevant differences in approval among different tumor entities, especially with respect to PD-L1 testing. Different response to ICI-therapy has been observed in the pivotal trials, so PD-L1 diagnostic testing is used for patient selection. In addition to PD-L1 testing of tumor tissue, liquid biopsy provides a noninvasive way to monitor disease in cancer patients and identify those who would benefit most from ICI-therapy. This overview focuses on the use of ICI-therapy and how it relates to common and potential future biomarkers for patient-directed treatment planning.

Mapping the functional interactions at the tumor-immune checkpoint interface

The interactions between tumor intrinsic processes and immune checkpoints can mediate immune evasion by cancer cells and responses to immunotherapy. It is, however, challenging to identify functional interactions due to the prohibitively complex molecular landscape of the tumor-immune interfaces. We address this challenge with a statistical analysis framework, immuno-oncology gene interaction maps (ImogiMap). ImogiMap quantifies and statistically validates tumor-immune checkpoint interactions based on their co-associations with immune-associated phenotypes. The outcome is a catalog of tumor-immune checkpoint interaction maps for diverse immune-associated phenotypes. Applications of ImogiMap recapitulate the interaction of SERPINB9 and immune checkpoints with interferon gamma (IFNγ) expression. Our analyses suggest that CD86-CD70 and CD274-CD70 immunoregulatory interactions are significantly associated with IFNγ expression in uterine corpus endometrial carcinoma and basal-like breast cancer, respectively. The open-source ImogiMap software and user-friendly web application will enable future applications of ImogiMap. Such applications may guide the discovery of previously unknown tumor-immune interactions and immunotherapy targets.

Effects of SMC1A on immune microenvironment and cancer stem cells in colon adenocarcinoma

BACKGROUND

Our previous study suggested that SMC1 has significant functions in colorectal cancer (CRC). However, few reports have shown the effects of structural maintenance of chromosomes 1 (SMC1A) on the immune microenvironment and tumor stem cells.

METHODS

The Cancer Genome Atlas (TCGA) database, CPTAC database, Human Protein Atlas (HPA) database, the Cancer Cell Line Encyclopedia (CCLE) and Tumor Immune Single-cell Hub were used. Flow cytometry and immunohistochemical analysis were checked for immune infiltration on MC38 mice model. Human CRC tissues were tested with RT-qPCR.

RESULTS

The mRNA and protein levels of SMC1A were increased in colon adenocarcinoma (COAD) samples. SMC1A was associated with DNA activity. Interestingly, SMC1A was highly expressed in many types of immune cells at single-cell levels. Moreover, the high expression of SMC1A was positively correlated with immune infiltration, and immunohistochemical analysis showed that SMC1A was positively associated with CD45 expression in MC38 mice model. Also, the percentage of IL4⁺ CD4⁺ T cells (Th2) and FoxP3⁺ CD4⁺ T cells (Tregs) was significantly higher in the SMC1A overexpression group than in control by flow cytometry assay in vivo. SMC1A expression could affect the proliferation of T cells in the mice model. The mutation and somatic cell copy number variation (SCNV) of SMC1A were also associated with immune cell infiltration. In addition to SMC1A in the "hot" T-cell inflammatory microenvironment of colon cancer, SMC1A also positively correlates with the immune checkpoint genes CD274, CTLA4, and PDCD1 in colon adenocarcinoma (COAD) samples. Furthermore, we also found that SMC1A plays a positive correlation with the induction of cancer stem cells (CSCs). Our results also showed that miR-23b-3p binds SMC1A.

CONCLUSION

SMC1A may be a bidirectional target switch that simultaneously regulates the immune microenvironment and tumor stem cells. Moreover, SMC1A may be a biomarker for the prediction of immune checkpoint inhibitor (ICI) therapy.

Prior anti-CTLA-4 therapy impacts molecular characteristics associated with anti-PD-1 response in advanced melanoma

Immune checkpoint inhibitors (ICIs), including CTLA-4- and PD-1-blocking antibodies, can have profound effects on tumor immune cell infiltration that have not been consistent in biopsy series reported to date. Here, we analyze seven molecular datasets of samples from patients with advanced melanoma (N = 514) treated with ICI agents to investigate clinical, genomic, and transcriptomic features of anti-PD-1 response in cutaneous melanoma. We find that prior anti-CTLA-4 therapy is associated with differences in genomic, individual gene, and gene signatures in anti-PD-1 responders. Anti-CTLA-4-experienced melanoma tumors that respond to PD-1 blockade exhibit increased tumor mutational burden, inflammatory signatures, and altered cell cycle processes compared with anti-CTLA-4-naive tumors or anti-CTLA-4-experienced, anti-PD-1-nonresponsive melanoma tumors. We report a harmonized, aggregate resource and suggest that prior CTLA-4 blockade therapy is associated with marked differences in the tumor microenvironment that impact the predictive features of PD-1 blockade therapy response.

Adventitial adaptive immune cells are associated with ascending aortic dilatation in patients with a bicuspid aortic valve

Background

Bicuspid aortic valve (BAV) is associated with ascending aorta aneurysms and dissections. Presently, genetic factors and pathological flow patterns are considered responsible for aneurysm formation in BAV while the exact role of inflammatory processes remains unknown.

Methods

In order to objectify inflammation, we employ a highly sensitive, quantitative immunohistochemistry approach. Whole slides of dissected, dilated and non-dilated ascending aortas from BAV patients were quantitatively analyzed.

Results

Dilated aortas show a 4-fold increase of lymphocytes and a 25-fold increase in B lymphocytes in the adventitia compared to non-dilated aortas. Tertiary lymphoid structures with B cell follicles and helper T cell expansion were identified in dilated and dissected aortas. Dilated aortas were associated with an increase in M1-like macrophages in the aorta media, in contrast the number of M2-like macrophages did not change significantly.

Conclusion

This study finds unexpected large numbers of immune cells in dilating aortas of BAV patients. These findings raise the question whether immune cells in BAV aortopathy are innocent bystanders or contribute to the deterioration of the aortic wall.

State of the Art of Pathologic and Molecular Testing

Advances in the treatment of non-small cell lung carcinoma have resulted in improved histologic classification and the implementation of molecular testing for predictive biomarkers into the routine diagnostic workflow. Over the past decade, molecular testing has evolved from single-gene assays to high-thoroughput comprehensive next-generation sequencing. Economic barriers, suboptimal turnaround time to obtain the results, and limited tissue available for molecular assays resulted in adoption of liquid biopsies (ctDNA) into clinical practice. Multiplex immunohistochemical/immunofluorescence assays evaluating tumor microenvironment together with the AI approaches are anticipated to translate from research into clinical care.

Spatial profiling technologies illuminate the tumor microenvironment

The tumor microenvironment (TME) is composed of many different cellular and acellular components that together drive tumor growth, invasion, metastasis, and response to therapies. Increasing realization of the significance of the TME in cancer biology has shifted cancer research from a cancer-centric model to one that considers the TME as a whole. Recent technological advancements in spatial profiling methodologies provide a systematic view and illuminate the physical localization of the components of the TME. In this review, we provide an overview of major spatial profiling technologies. We present the types of information that can be extracted from these data and describe their applications, findings and challenges in cancer research. Finally, we provide a future perspective of how spatial profiling could be integrated into cancer research to improve patient diagnosis, prognosis, stratification to treatment and development of novel therapeutics.

PD-L1 expression as biomarker of efficacy of PD-1/PD-L1 checkpoint inhibitors in metastatic triple negative breast cancer: A systematic review and meta-analysis

Background

Inhibitors of programmed cell death 1 (PD-1)/programmed cell death ligand 1(PD-L1) checkpoint have been approved for metastatic triple negative breast cancer (mTNBC) in patients positive for PD-L1 expression. Negative results from the recent phase III trials (IMPassion131 and IMPassion132) have raises questions on the efficacy of PD-1/PD-L1 checkpoint inhibitors and the predictive value of PD-L1 expression. Here we attempt to systematically analyze the biomarker value of PD-L1 expression for predicting the response of PD-1/PD-L1 checkpoint inhibitors in mTNBC.

Materials and methods

PubMed database was searched until Dec 2021 for studies evaluating PD-1/PD-L1 checkpoint inhibitors plus/minus chemotherapy in mTNBC. Outcome of interest included objective response rate (ORR), progression-free survival (PFS), and overall survival (OS). Review Manager (RevMan) version 5.4. was used for data-analysis.

Results

In total, 20 clinical trials comprising 3962 mTNBC patients (ICT: 2665 (67%); CT: 1297 (33%) were included in this study. Overall ORR was 22% (95%CI, 14-30%) and significant improvement was observed for PD-L1+ patients (ORR 1.78 [95%CI, 1.45-2.19], p<0.00001) as compared to PD-L1- cohort. Pooled outcome also indicated a significant 1-year PFS and 2-year OS advantage for patients with PD-L1 expression (1-year PFS: ORR 1.39 [95%CI, 1.04-1.85], p=0.02; I2 = 0%; 2-year OS: (ORR 2.47 [95%CI, 1.30-4.69], p=0.006; I2 = 63%). Subgroup analysis indicated that PD-L1 expression can successfully predict tumor response and 2-year OS benefit in mTNBC patients regardless of the type of investigating agent, line of treatment administration, and to some extent the type of treatment. Biomarker ability of PD-L1 expression to predict 1-year PFS was slightly better with pembrolizumab (p=0.09) than atezolizumab (p=0.18), and significantly better when treatment was administered in the first-line setting (OR 1.38 [95%CI, 1.02-1.87], p=0.04) and chemotherapy was added (OR 1.38 [95%CI, 1.02-1.86], p=0.03). Immune-related toxicity of any grade and grade≥3 was 39% (95%CI, 26%-52%) and 10% (95%CI, 8%-13%), respectively.

Conclusions

PD-L1 expression can predict objective response rate and 2-year OS in mTNBC patients receiving PD-1/PD-L1 checkpoint inhibitors. One-year PFS is also predicted in selected patients. PD-L1 expression can be a useful biomarker of efficacy of PD-1/PD-L1 checkpoint inhibitors in mTNBC.

Response prediction in patients with gastric and esophagogastric adenocarcinoma under neoadjuvant chemotherapy using targeted gene expression analysis and next-generation sequencing in pre-therapeutic biopsies

OBJECTIVES

Perioperative chemo-(radio-) therapy is the accepted standard in European patients with locally advanced adenocarcinoma of the esophagogastric junction or stomach (AEG/AS). However, 30-85% of patients do not respond to this treatment. The aim of our study was the identification of predictive biomarkers in pre-therapeutic endoscopic tumor biopsies from patients with histopathologic response (Becker-1) versus non-response (Becker-2/3) to preoperative chemotherapy.

METHODS

Formalin-fixed paraffin-embedded biopsies from 36 Caucasian patients (Becker-1 n = 11, Becker-2 n = 7, Becker-3 n = 18) with AEG/AS, taken prior to neoadjuvant chemotherapy were selected. For RNA expression analysis, we employed the NanoString nCounter System. To identify genomic alterations like single nucleotide variants (SNV), copy number variation (CNV) and fusion events, we used Illumina TST170 gene panel. For HER2 and FGFR2 protein expression, immunostaining was performed. Furthermore, we analyzed the microsatellite instability (MSI) and Epstein-Barr virus (EBV) infection status by EBER in situ hybridization.

RESULTS

Heat map and principal component analyses showed no clustering by means of gene expression according to regression grade. Concerning two recently proposed predictive markers, our data showed equal distribution for MSI (Becker-1: 2; Becker-2: 1; Becker-3: 3; out of 29 tested) and EBV infection was rare (1/32). We could not reveal discriminating target genes concerning SNV, but found a higher mutational burden in non-responders versus responders and fusion (in 6/14) and CNV events (in 5/14) exclusively in Becker-3.

CONCLUSIONS

Although we could not identify discriminating target genes, our data suggest that molecular alterations are in general more prevalent in patients with AEG/AS belonging to the non-responding Becker group 3.

Spatial PD-L1, immune-cell microenvironment, and genomic copy-number alteration patterns and drivers of invasive-disease transition in prospective oral precancer cohort

BACKGROUND

Studies of the immune landscape led to breakthrough trials of programmed death-1 (PD-1) inhibitors for recurrent/metastatic head and neck squamous cell carcinoma therapy. This study investigated the timing, influence of somatic copy-number alterations (SCNAs), and clinical implications of PD-L1 and immune-cell patterns in oral precancer (OPC).

METHODS

The authors evaluated spatial CD3, CD3/8, and CD68 density (cells/mm2 ) and PD-L1 (membranous expression in cytokeratin-positive intraepithelial neoplastic cells and CD68) patterns by multiplex immunofluorescence in a 188-patient prospective OPC cohort, characterized by clinical, histologic, and SCNA risk factors and protocol-specified primary end point of invasive cancer. The authors used Wilcoxon rank-sum and Fisher exact tests, linear mixed effect models, mediation, and Cox regression and recursive-partitioning analyses.

RESULTS

Epithelial, but not CD68 immune-cell, PD-L1 expression was detected in 28% of OPCs, correlated with immune-cell infiltration, 9p21.3 loss of heterozygosity (LOH), and inferior oral cancer-free survival (OCFS), notably in OPCs with low CD3/8 cell density, dysplasia, and/or 9p21.3 LOH. High CD3/8 cell density in dysplastic lesions predicted better OCFS and eliminated the excess risk associated with prior oral cancer and dysplasia. PD-L1 and CD3/8 patterns revealed inferior OCFS in PD-L1 high intrinsic induction and dysplastic immune-cold subgroups.

CONCLUSION

This report provides spatial insight into the immune landscape and drivers of OPCs, and a publicly available immunogenomic data set for future precancer interrogation. The data suggest that 9p21.3 LOH triggers an immune-hot inflammatory phenotype; whereas increased 9p deletion size encompassing CD274 at 9p24.1 may contribute to CD3/8 and PD-L1 depletion during invasive transition. The inferior OCFS in PD-L1-high, immune-cold OPCs support the development of T-cell recruitment strategies.

Deep learning in digital pathology for personalized treatment plans of cancer patients

Over the past decade, many new cancer treatments have been developed and made available to patients. However, in most cases, these treatments only benefit a specific subgroup of patients, making the selection of treatment for a specific patient an essential but challenging task for oncologists. Although some biomarkers were found to associate with treatment response, manual assessment is time-consuming and subjective. With the rapid developments and expanded implementation of artificial intelligence (AI) in digital pathology, many biomarkers can be quantified automatically from histopathology images. This approach allows for a more efficient and objective assessment of biomarkers, aiding oncologists in formulating personalized treatment plans for cancer patients. This review presents an overview and summary of the recent studies on biomarker quantification and treatment response prediction using hematoxylin-eosin (H&E) stained pathology images. These studies have shown that an AI-based digital pathology approach can be practical and will become increasingly important in improving the selection of cancer treatments for patients.

Dynamic changes in circulating tumor DNA assessed by shallow whole-genome sequencing associate with clinical efficacy of checkpoint inhibitors in NSCLC

Immune checkpoint inhibitors (ICIs) targeting the PD-1/PD-L1 axis are the main therapeutic option for patients with advanced non-small cell lung cancer (NSCLC) without a druggable oncogenic alteration. Nevertheless, only a portion of patients benefit from this type of treatment. Here, we assessed the value of shallow whole-genome sequencing (sWGS) on plasma samples to monitor ICI benefit. We applied sWGS on cell-free DNA (cfDNA) extracted from plasma samples of 45 patients with metastatic NSCLC treated with ICIs. Over 150 samples were obtained before ICI treatment initiation and at several time points throughout treatment. From sWGS data, we computed the tumor fraction (TFx) and somatic copy number alteration (SCNA) burden and associated them with ICI benefit and clinical features. TFx at baseline correlated with metastatic lesions at the bone and the liver, and high TFx (≥ 10%) associated with ICI benefit. Moreover, its assessment in on-treatment samples was able to better predict clinical efficacy, regardless of the TFx levels at baseline. Finally, for a subset of patients for whom SCNA burden could be computed, increased burden correlated with diminished benefit following ICI treatment. Thus, our data indicate that the analysis of cfDNA by sWGS enables the monitoring of two potential biomarkers-TFx and SCNA burden-of ICI benefit in a cost-effective manner, facilitating multiple serial-sample analyses. Larger cohorts will be needed to establish its clinical potential.

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

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

Visualization and quality control tools for large-scale multiplex tissue analysis in TissUUmaps3

Large-scale multiplex tissue analysis aims to understand processes such as development and tumor formation by studying the occurrence and interaction of cells in local environments in, for example, tissue samples from patient cohorts. A typical procedure in the analysis is to delineate individual cells, classify them into cell types, and analyze their spatial relationships. All steps come with a number of challenges, and to address them and identify the bottlenecks of the analysis, it is necessary to include quality control tools in the analysis workflow. This makes it possible to optimize the steps and adjust settings in order to get better and more precise results. Additionally, the development of automated approaches for tissue analysis requires visual verification to reduce skepticism with regard to the accuracy of the results. Quality control tools could be used to build users' trust in automated approaches. In this paper, we present three plugins for visualization and quality control in large-scale multiplex tissue analysis of microscopy images. The first plugin focuses on the quality of cell staining, the second one was made for interactive evaluation and comparison of different cell classification results, and the third one serves for reviewing interactions of different cell types.

Noninvasive evaluation of PD-L1 expression in non-small cell lung cancer by immunoPET imaging using an acylating agent-modified antibody fragment

PURPOSE

The aim of this study was to explore an effective ¹²⁴I labeling strategy and improve the signal-to-noise ratio when evaluating the expression of PD-L1 using an ¹²⁴I-iodinated durvalumab (durva) F(ab')₂ fragment.

METHODS

The prepared durva F(ab')₂ fragments were incubated with N-succinimidyl-3-(4-hydroxyphenyl) propionate (SHPP); after purification, the HPP-durva F(ab')₂ was iodinated using Iodo-Gen method. After the radiochemical purity, stability, and specific activities were determined, the binding affinities of probes prepared using different labeling strategies were compared in vitro. The clinical application value of [¹²⁴I]I-HPP-durva-F(ab')₂ was confirmed by PET imaging. To more objectively evaluate the in vivo distribution and clearance of tracers, the pharmacokinetics and biodistribution assays were also performed.

RESULTS

After being modified with SHPP, the average conjugation number of SHPP per durva-F(ab')₂ identified by LC-MS was about 8.92 ± 2.84. The prepared [¹²⁴I]I-HPP-durva F(ab')₂ was obtained with a satisfactory radiochemical purity of more than 98% and stability of more than 93% when incubated for 72 h. Compared with unmodified [¹²⁴I]I-durva F(ab')₂, the specific activity of [¹²⁴I]I-HPP-durva-F(ab')₂ was improved (52.91 ± 5.55 MBq/mg and 15.91 ± 0.74 MBq/mg), while the affinity did not significantly change. The biodistribution experiments and PET imaging showed that the prepared [¹²⁴I]I-HPP-durva-F(ab')₂ exhibited an accelerated clearance and improved tumor-to-background ratio compared with [¹²⁴I]I-durva-F(ab')₂. The specificity of [¹²⁴I]I-HPP-durva-F(ab')₂ to PD-L1 was well demonstrated both in vitro and in vivo.

CONCLUSIONS

A PD-L1 PET imaging probe [¹²⁴I]I-HPP-durva F(ab')₂ was successfully synthesized through the SHPP modification strategy. The prepared probe was able to accurately evaluate the PD-L1 expression level through high-contrast noninvasive imaging.

Companion diagnostic requirements for spatial biology using multiplex immunofluorescence and multispectral imaging

Immunohistochemistry has long been held as the gold standard for understanding the expression patterns of therapeutically relevant proteins to identify prognostic and predictive biomarkers. Patient selection for targeted therapy in oncology has successfully relied upon standard microscopy-based methodologies, such as single-marker brightfield chromogenic immunohistochemistry. As promising as these results are, the analysis of one protein, with few exceptions, no longer provides enough information to draw effective conclusions about the probability of treatment response. More multifaceted scientific queries have driven the development of high-throughput and high-order technologies to interrogate biomarker expression patterns and spatial interactions between cell phenotypes in the tumor microenvironment. Such multi-parameter data analysis has been historically reserved for technologies that lack the spatial context that is provided by immunohistochemistry. Over the past decade, technical developments in multiplex fluorescence immunohistochemistry and discoveries made with improving image data analysis platforms have highlighted the importance of spatial relationships between certain biomarkers in understanding a patient's likelihood to respond to, typically, immune checkpoint inhibitors. At the same time, personalized medicine has instigated changes in both clinical trial design and its conduct in a push to make drug development and cancer treatment more efficient, precise, and economical. Precision medicine in immuno-oncology is being steered by data-driven approaches to gain insight into the tumor and its dynamic interaction with the immune system. This is particularly necessary given the rapid growth in the number of trials involving more than one immune checkpoint drug, and/or using those in combination with conventional cancer treatments. As multiplex methods, like immunofluorescence, push the boundaries of immunohistochemistry, it becomes critical to understand the foundation of this technology and how it can be deployed for use as a regulated test to identify the prospect of response from mono- and combination therapies. To that end, this work will focus on: 1) the scientific, clinical, and economic requirements for developing clinical multiplex immunofluorescence assays; 2) the attributes of the Akoya Phenoptics workflow to support predictive tests, including design principles, verification, and validation needs; 3) regulatory, safety and quality considerations; 4) application of multiplex immunohistochemistry through lab-developed-tests and regulated in vitro diagnostic devices.

High-multiplex tissue imaging in routine pathology-are we there yet?

High-multiplex tissue imaging (HMTI) approaches comprise several novel immunohistological methods that enable in-depth, spatial single-cell analysis. Over recent years, studies in tumor biology, infectious diseases, and autoimmune conditions have demonstrated the information gain accessible when mapping complex tissues with HMTI. Tumor biology has been a focus of innovative multiparametric approaches, as the tumor microenvironment (TME) contains great informative value for accurate diagnosis and targeted therapeutic approaches: unraveling the cellular composition and structural organization of the TME using sophisticated computational tools for spatial analysis has produced histopathologic biomarkers for outcomes in breast cancer, predictors of positive immunotherapy response in melanoma, and histological subgroups of colorectal carcinoma. Integration of HMTI technologies into existing clinical workflows such as molecular tumor boards will contribute to improve patient outcomes through personalized treatments tailored to the specific heterogeneous pathological fingerprint of cancer, autoimmunity, or infection. Here, we review the advantages and limitations of existing HMTI technologies and outline how spatial single-cell data can improve our understanding of pathological disease mechanisms and determinants of treatment success. We provide an overview of the analytic processing and interpretation and discuss how HMTI can improve future routine clinical diagnostic and therapeutic processes.

Pretreatment with antibiotics is associated with reduced therapeutic response to atezolizumab plus bevacizumab in patients with hepatocellular carcinoma

AIM

Alterations in microbial composition of gut microbiota due to antibiotics (ATB) may lead to resistance to immune checkpoint inhibitors (ICIs). This study aimed to assess the impact of ATB use on therapeutic response in patients with hepatocellular carcinoma (HCC) receiving atezolizumab plus bevacizumab.

METHODS

This study retrospectively analyzed 105 patients with HCC treated with atezolizumab plus bevacizumab as a primary systemic therapy from prospectively-registered, multicenter, cohorts. Nineteen patients who received prior ATB were included in the ATB (+) group; 86 patients who did not receive prior ATB were included in the ATB (-) group. The therapeutic outcomes were compared between the two groups.

RESULTS

Most of the patients' baseline characteristics were not significantly different between the two groups. The objective response rates according to the Response Evaluation Criteria in Solid Tumors version 1.1 (RECIST v1.1) (30.1% vs. 11.1%; p = 0.143) and modified RECIST (mRECIST) (44.6% vs. 27.8%; p = 0.190) were not significantly different between the ATB (-) and ATB (+) groups. The disease control rates were higher in the ATB (-) group than in the ATB (+) group according to RECIST v1.1 (74.7% vs. 44.4%; p = 0.012) and mRECIST (78.3% vs. 50.0%; p = 0.020). Prior ATB use was found to be independently associated with radiological progressive disease of the first therapeutic assessment. The median progression-free survival according to RECIST v1.1 (9.1 months vs. 3.0 months; p = 0.049) and mRECIST (9.1 months vs. 3.0 months; p = 0.036), and overall survival (not reached vs. 11.4 months; p = 0.015) were longer in the ATB (-) group than in the ATB (+) group.

CONCLUSIONS

Prior ATB use was associated with reduced therapeutic responses in patients with HCC receiving atezolizumab plus bevacizumab.

Development and validation of an integrative pan-solid tumor predictor of PD-1/PD-L1 blockade benefit

BACKGROUND

Anti-PD-1 and PD-L1 (collectively PD-[L]1) therapies are approved for many advanced solid tumors. Biomarkers beyond PD-L1 immunohistochemistry, microsatellite instability, and tumor mutation burden (TMB) may improve benefit prediction.

METHODS

Using treatment data and genomic and transcriptomic tumor tissue profiling from an observational trial (NCT03061305), we developed Immunotherapy Response Score (IRS), a pan-tumor predictive model of PD-(L)1 benefit. IRS real-world progression free survival (rwPFS) and overall survival (OS) prediction was validated in an independent cohort of trial patients.

RESULTS

Here, by Cox modeling, we develop IRS-which combines TMB with CD274, PDCD1, ADAM12 and TOP2A quantitative expression-to predict pembrolizumab rwPFS (648 patients; 26 tumor types; IRS-High or -Low groups). In the 248 patient validation cohort (248 patients; 24 tumor types; non-pembrolizumab PD-[L]1 monotherapy treatment), median rwPFS and OS are significantly longer in IRS-High vs. IRS-Low patients (rwPFS adjusted hazard ratio [aHR] 0.52, p = 0.003; OS aHR 0.49, p = 0.005); TMB alone does not significantly predict PD-(L)1 rwPFS nor OS. In 146 patients treated with systemic therapy prior to pembrolizumab monotherapy, pembrolizumab rwPFS is only significantly longer than immediately preceding therapy rwPFS in IRS-High patients (interaction test p = 0.001). In propensity matched lung cancer patients treated with first-line pembrolizumab monotherapy or pembrolizumab+chemotherapy, monotherapy rwPFS is significantly shorter in IRS-Low patients, but is not significantly different in IRS-High patients. Across 24,463 molecularly-evaluable trial patients, 7.6% of patients outside of monotherapy PD-(L)1 approved tumor types are IRS-High/TMB-Low.

CONCLUSIONS

The validated, predictive, pan-tumor IRS model can expand PD-(L)1 monotherapy benefit outside currently approved indications.

Multiplex Immunofluorescence: A Powerful Tool in Cancer Immunotherapy

Traditional immunohistochemistry (IHC) has already become an essential method of diagnosis and therapy in cancer management. However, this antibody-based technique is limited to detecting a single marker per tissue section. Since immunotherapy has revolutionized the antineoplastic therapy, developing new immunohistochemistry strategies to detect multiple markers simultaneously to better understand tumor environment and predict or assess response to immunotherapy is necessary and urgent. Multiplex immunohistochemistry (mIHC)/multiplex immunofluorescence (mIF), such as multiplex chromogenic IHC and multiplex fluorescent immunohistochemistry (mfIHC), is a new and emerging technology to label multiple biomarkers in a single pathological section. The mfIHC shows a higher performance in cancer immunotherapy. This review summarizes the technologies, which are applied for mfIHC, and discusses how they are employed for immunotherapy research.

Immunogenomic Biomarkers and Validation in Lynch Syndrome

Lynch syndrome (LS) is an inherited disorder in which affected individuals have a significantly higher-than-average risk of developing colorectal and non-colorectal cancers, often before the age of 50 years. In LS, mutations in DNA repair genes lead to a dysfunctional post-replication repair system. As a result, the unrepaired errors in coding regions of the genome produce novel proteins, called neoantigens. Neoantigens are recognised by the immune system as foreign and trigger an immune response. Due to the invasive nature of cancer screening tests, universal cancer screening guidelines unique for LS (primarily colonoscopy) are poorly adhered to by LS variant heterozygotes (LSVH). Currently, it is unclear whether immunogenomic components produced as a result of neoantigen formation can be used as novel biomarkers in LS. We hypothesise that: (i) LSVH produce measurable and dynamic immunogenomic components in blood, and (ii) these quantifiable immunogenomic components correlate with cancer onset and stage. Here, we discuss the feasibility to: (a) identify personalised novel immunogenomic biomarkers and (b) validate these biomarkers in various clinical scenarios in LSVH.

Clinical Trials and Digital Pathology-Toward Quantitative Therapeutic Immunohistochemistry and Tissue Hybridization

This Viewpoint discusses immunohistochemistry and tissue-hybridization-based diagnostics delivery and compares it with digital pathology.

Association of immune-related adverse events and efficacy in advanced non-small-cell lung cancer: a systematic review and meta-analysis

Aim: This study aimed to explore the association of immune-related adverse events (irAEs) with efficacy in advanced non-small-cell lung cancer (NSCLC). Materials & methods: A literature search was conducted under preselected criteria. Primary outcomes were hazard ratio (HR) and 95% CI of irAEs on objective response rate, overall survival (OS) and progression-free survival (PFS). Results: 35 studies covering 8435 patients with advanced NSCLC were included. Patients with irAEs exhibited significantly longer PFS and OS (for PFS, HR: 0.481; 95% CI: 0.370-0.568; p < 0.001 and for OS, HR: 0.470; 95% CI: 0.410-0.539; p < 0.001), and also showed significantly higher objective response rate compared with those without irAEs (pooled OR: 0.023 [95% CI: 0.009-0.590]). Conclusion: This meta-analysis showed that irAEs were associated with efficacy for advanced NSCLC.

Gallium-68-labeled Peptide PET Quantifies Tumor Exposure of PD-L1 Therapeutics

PURPOSE

Immune checkpoint therapy (ICT) is currently ineffective in a majority of patients. Tumor drug exposure measurements can provide vital insights into mechanisms involved in the resistance of solid tumors to those therapeutics; however, tools to quantify in situ drug exposure are few. We have investigated the potential of programmed death-ligand 1 (PD-L1) pharmacodynamics, quantified using PET, to inform on the tumor exposure of anti-PD-L1 (aPD-L1) therapeutics.

EXPERIMENTAL DESIGN

To noninvasively quantify PD-L1 levels, we first developed a novel peptide-based gallium-68-labeled binder, [68Ga]Ga-DK223, and evaluated its in vivo distribution, pharmacokinetics, and PD-L1 specificity in preclinical models of triple-negative breast cancer and urothelial carcinoma with variable PD-L1 expression. We then quantified baseline and accessible PD-L1 levels in tumors as a noninvasive pharmacodynamic measure to assess tumor exposure to two aPD-L1 antibodies (avelumab and durvalumab).

RESULTS

DK223 exhibited a KD of 1.01±0.83 nmol/L for PD-L1 and inhibited the PD-1:PD-L1 interaction in a dose-dependent manner. [68Ga]Ga-DK223 provides high-contrast PET images within 60 minutes of administration and detects PD-L1 in an expression-dependent manner in xenograft models. PD-L1 pharmacodynamics measured using [68Ga]Ga-DK223-PET revealed that avelumab and durvalumab had similar exposure early during therapy, but only durvalumab exhibited sustained exposure at the tumor.

CONCLUSIONS

[68Ga]Ga-DK223 detected variable PD-L1 levels and exhibited salient features required for clinical translation. [68Ga]Ga-DK223-PET could be useful for quantifying total PD-L1 levels at baseline and accessible PD-L1 levels during therapy to understand drug exposure at the tumor, thus supporting its use for guiding and optimizing ICT.

Design, Synthesis, and Biological Evaluation of a Small-Molecule PET Agent for Imaging PD-L1 Expression

Immunotherapy blocking programmed cell death protein 1/programmed death ligand 1 (PD-1/PD-L1) pathway has achieved great therapeutic effect in the clinic, but the overall response rate is not satisfactory. Early studies showed that response to treatment and overall survival could be positively related to PD-L1 expression in tumors. Therefore, accurate measurement of PD-L1 expression will help to screen cancer patients and improve the overall response rate. A small molecular positron emission tomography (PET) probe [18F]LP-F containing a biphenyl moiety was designed and synthesized for measurement of PD-L1 expression in tumors. The PET probe [18F]LP-F was obtained with a radiochemical yield of 12.72 ± 1.98%, a radiochemical purity of above 98% and molar activity of 18.8 GBq/μmol. [18F]LP-F had good stability in phosphate buffer saline (PBS) and mouse serum. In vitro assay indicated that [18F]LP-F showed moderate affinity to PD-L1. Micro-PET results showed that the tumor accumulation of [18F]LP-F in A375 tumor was inferior to that in A375-hPD-L1 tumor. All the results demonstrated that [18F]LP-F could specifically bind to PD-L1 and had a potential application in non-invasive evaluation of PD-L1 expression in tumors.

An immune score reflecting pro- and anti-tumoural balance of tumour microenvironment has major prognostic impact and predicts immunotherapy response in solid cancers

BACKGROUND

Cancer immunity is based on the interaction of a multitude of cells in the spatial context of the tumour tissue. Clinically relevant immune signatures are therefore anticipated to fundamentally improve the accuracy in predicting disease progression.

METHODS

Through a multiplex in situ analysis we evaluated 15 immune cell classes in 1481 tumour samples. Single-cell and bulk RNAseq data sets were used for functional analysis and validation of prognostic and predictive associations.

FINDINGS

By combining the prognostic information of anti-tumoural CD8⁺ lymphocytes and tumour supportive CD68⁺CD163⁺ macrophages in colorectal cancer we generated a signature of immune activation (SIA). The prognostic impact of SIA was independent of conventional parameters and comparable with the state-of-art immune score. The SIA was also associated with patient survival in oesophageal adenocarcinoma, bladder cancer, lung adenocarcinoma and melanoma, but not in endometrial, ovarian and squamous cell lung carcinoma. We identified CD68⁺CD163⁺ macrophages as the major producers of complement C1q, which could serve as a surrogate marker of this macrophage subset. Consequently, the RNA-based version of SIA (ratio of CD8A to C1QA) was predictive for survival in independent RNAseq data sets from these six cancer types. Finally, the CD8A/C1QA mRNA ratio was also predictive for the response to checkpoint inhibitor therapy.

INTERPRETATION

Our findings extend current concepts to procure prognostic information from the tumour immune microenvironment and provide an immune activation signature with high clinical potential in common human cancer types.

FUNDING

Swedish Cancer Society, Lions Cancer Foundation, Selanders Foundation, P.O. Zetterling Foundation, U-CAN supported by SRA CancerUU, Uppsala University and Region Uppsala.

Flexible Cyclic Immunofluorescence (cyCIF) Using Oligonucleotide Barcoded Antibodies

Advances in our understanding of the complex, multifaceted interactions between tumor epithelia, immune infiltrate, and tumor microenvironmental cells have been driven by highly multiplexed imaging technologies. These techniques are capable of labeling many more biomarkers than conventional immunostaining methods. However, multiplexed imaging techniques suffer from low detection sensitivity, cell loss-particularly in fragile samples-, and challenges with antibody labeling. Herein, we developed and optimized an oligonucleotide antibody barcoding strategy for cyclic immunofluorescence (cyCIF) that can be amplified to increase the detection efficiency of low-abundance antigens. Stained fluorescence signals can be readily removed using ultraviolet light treatment, preserving tissue and fragile cell sample integrity. We also extended the oligonucleotide barcoding strategy to secondary antibodies to enable the inclusion of difficult-to-label primary antibodies in a cyCIF panel. Using both the amplification oligonucleotides to label DNA barcoded antibodies and in situ hybridization of multiple fluorescently labeled oligonucleotides resulted in signal amplification and increased signal-to-background ratios. This procedure was optimized through the examination of staining parameters including staining oligonucleotide concentration, staining temperature, and oligonucleotide sequence design, resulting in a robust amplification technique. As a proof-of-concept, we demonstrate the flexibility of our cyCIF strategy by simultaneously imaging with the original oligonucleotide conjugated antibody (Ab-oligo) cyCIF strategy, the novel Ab-oligo cyCIF amplification strategy, as well as direct and indirect immunofluorescence to generate highly multiplexed images.

Application of Value Framework to Phase III Trials of Immune Checkpoint Inhibitors in Esophageal and Gastric Cancer

BACKGROUND

Recent trials testing immune-checkpoint inhibitors in esophago-gastric malignancies have shown mixed results. We aim to assess key subgroups using the ASCO Net Health Benefit Score (NHBS) and ESMO Magnitude of Clinical Benefit Scale (MCBS).

MATERIALS AND METHODS

A search for phase III trials of FDA-approved anti-PD-1 or anti-PD-L1 drugs in esophago-gastric cancer trials was identified using www.clinicaltrials.gov. These published studies were scored using the ASCO NHBS and ESMO MCBS. The ASCO NHBS scores were compared by primary site of cancer (esophageal vs gastric) and PD-L1 expression using the Mann-Whitney test and the ESMO-MCBS grading, by Fisher's Exact test.

RESULTS

Fifteen of 45 clinical trials were included. Of them, 6 were primarily esophageal cancer trials, and 9 were primarily gastric cancer trials. Ten stratified their analysis based on PD-L1 expression. The ASCO NHBS score was higher (mean 40, range 20 to 56.6 vs. mean 12, range -1.1 to 18.4, P < .01) for esophageal cancer than gastric cancer. No difference was observed in survival and response endpoints between the 2 groups. Similarly, the ESMO MCBS scored higher for esophageal cancer group than gastric cancer (P < .05). Additionally, the scores were higher in those with high PD-L1 expression vs. low PD-L1 (mean 36, range 11.2-66.6 vs. mean 14, range -19.5 to 43.6, P < .05).

CONCLUSION

The ASCO NHB and ESMO scores were consistently higher among esophageal cancer trials than gastric cancer trials and in those with high PD-L1 expression than low expression. Histology and PD-L1 expression should be considered when discussing value of immunotherapy to patients.

Interaction of glioma-associated microglia/macrophages and anti-PD1 immunotherapy

Anti-PD-1-based therapy has resulted in a minimal clinical response in malignant gliomas. Gliomas contain numerous glioma-associated microglia/macrophages (GAMs), reported to contribute to an immunosuppressive microenvironment and promote glioma progression. However, whether and how GAMs affect anti-PD-1 immunotherapy in glioma remains unclear. Here, we demonstrated that M1-like GAMs contribute to the anti-PD-1 therapeutic response, while the accumulation of M2-like GAMs is associated with therapeutic resistance. Furthermore, we found that PD-L1 ablation reverses GAMs M2-like phenotype and is beneficial to anti-PD-1 therapy. We also demonstrated that tumor-induced impairment of the antigen-presenting function of GAMs could limit the antitumor immunity of CD4⁺ T cells in anti-PD-1 therapy. Our study highlights the impact of GAMs activation on anti-PD-1 treatment and provides new insights into the role of GAMs in regulating anti-PD-1 therapy in gliomas.

Fundamentals to therapeutics: Epigenetic modulation of CD8+ T Cell exhaustion in the tumor microenvironment

In the setting of chronic antigen exposure in the tumor microenvironment (TME), cytotoxic CD8+ T cells (CTLs) lose their immune surveillance capabilities and ability to clear tumor cells as a result of their differentiation into terminally exhausted CD8+ T cells. Immune checkpoint blockade (ICB) therapies reinvigorate exhausted CD8+ T cells by targeting specific inhibitory receptors, thus promoting their cytolytic activity towards tumor cells. Despite exciting results with ICB therapies, many patients with solid tumors still fail to respond to such therapies and patients who initially respond can develop resistance. Recently, through new sequencing technologies such as the assay for transposase-accessible chromatin with sequencing (ATAC-seq), epigenetics has been appreciated as a contributing factor that enforces T cell differentiation toward exhaustion in the TME. Importantly, specific epigenetic alterations and epigenetic factors have been found to control CD8+ T cell exhaustion phenotypes. In this review, we will explain the background of T cell differentiation and various exhaustion states and discuss how epigenetics play an important role in these processes. Then we will outline specific epigenetic changes and certain epigenetic and transcription factors that are known to contribute to CD8+ T cell exhaustion. We will also discuss the most recent methodologies that are used to study and discover such epigenetic modulations. Finally, we will explain how epigenetic reprogramming is a promising approach that might facilitate the development of novel exhausted T cell-targeting immunotherapies.

Multiparameter single-cell proteomic technologies give new insights into the biology of ovarian tumors

High-grade serous ovarian cancer (HGSOC) is the most lethal gynecological malignancy. Its diagnosis at advanced stage compounded with its excessive genomic and cellular heterogeneity make curative treatment challenging. Two critical therapeutic challenges to overcome are carboplatin resistance and lack of response to immunotherapy. Carboplatin resistance results from diverse cell autonomous mechanisms which operate in different combinations within and across tumors. The lack of response to immunotherapy is highly likely to be related to an immunosuppressive HGSOC tumor microenvironment which overrides any clinical benefit. Results from a number of studies, mainly using transcriptomics, indicate that the immune tumor microenvironment (iTME) plays a role in carboplatin response. However, in patients receiving treatment, the exact mechanistic details are unclear. During the past decade, multiplex single-cell proteomic technologies have come to the forefront of biomedical research. Mass cytometry or cytometry by time-of-flight, measures up to 60 parameters in single cells that are in suspension. Multiplex cellular imaging technologies allow simultaneous measurement of up to 60 proteins in single cells with spatial resolution and interrogation of cell-cell interactions. This review suggests that functional interplay between cell autonomous responses to carboplatin and the HGSOC immune tumor microenvironment could be clarified through the application of multiplex single-cell proteomic technologies. We conclude that for better clinical care, multiplex single-cell proteomic technologies could be an integral component of multimodal biomarker development that also includes genomics and radiomics. Collection of matched samples from patients before and on treatment will be critical to the success of these efforts.

Pathology of neoadjuvant therapy and immunotherapy testing for breast cancer

Neoadjuvant chemotherapy (NACT) has become the standard of care for high-risk breast cancer, including triple-negative (TNBC) and HER2-positive disease. As a result, handling and reporting of breast specimens post-NACT is part of routine practice, and it is important for pathologists to recognise the changes in tumour cells, tumour-associated stroma and background breast tissue induced by NACT. Familiarity with characteristic stromal features enables identification of the pre-treatment tumour site and allows confident diagnosis of pathological complete response (pCR) which is important for decisions concerning adjuvant therapy. Neoadjuvant endocrine therapy (NAET) is used less frequently than NACT; however, the SARS-COVID-19 pandemic has changed practice, with increased use as bridging therapy if surgery is delayed. NAET also induces characteristic changes in the tumour and stroma. Changes in the tumour microenvironment following NACT and NAET are also described. Immunotherapy is approved for use in advanced TNBC, and there are several trials exploring its role in early TNBC in the neoadjuvant setting. The current biomarker to determine eligibility for treatment with immune checkpoint inhibitors is programmed death ligand-1 (PD-L1) immunohistochemistry; however, this is complicated by lack of standardisation with different drugs linked to tests using different antibodies with different scoring systems. The situation in the neoadjuvant setting is further complicated by improved pCR rates for PD-L1-positive tumours in both immune therapy and placebo arms. Alternative biomarkers are urgently needed to identify which patients will derive benefit from immunotherapy and key candidates are discussed.

Biomarkers for immune checkpoint inhibitors in solid tumors

The use of immune checkpoint inhibitors in solid organ malignancies has become widespread in the last decade. Accumulating evidence shows broad survival benefit as compared to traditional chemotherapies. At the same time, a need has emerged to stratify these drugs in various patient populations and histologies. Consequently, various immune biomarkers have been proposed to help in selecting patients for these therapies. Here, we review the evidence pertaining to biomarkers including programmed death-ligand 1, defective mismatch repair, tumor mutational burden, tumor-infiltrating lymphocytes, gene expression profiles, circulating blood cells, circulating DNA and the gut microbiome. The value of PD-L1 testing in certain malignancies, such as lung and urothelial cancer is highlighted as well as emerging data from trials such as GARNET and CheckMate142.