Measuring multiple parameters of CD8+ tumor-infiltrating lymphocytes in human cancers by image analysis

Synergistic B and T lymphocyte interaction: prognostic implications in non-small cell lung cancer

While T-cell-mediated immune responses in solid tumors have been well-established and have driven major therapeutic advances, our understanding of B-cell biology in cancer is comparatively less developed. A total of 60 lung cancer patients were included, of which 53% were diagnosed at an early stage while 47% were diagnosed at an advanced stage. Flow cytometry was used to analyze the proportion of T and B cells in all blood samples, and the levels of human serum cytokines were also assessed. Compared to the control group, cancer patients showed lower frequencies of IgD+CD27+ marginal B cells and CD32+ B cells, and higher frequencies of T cells with lower CD8+ T cells and higher central memory and naïve CD4+ T cells. Additionally, advanced-stage cancer patients exhibited higher levels of cytokines, a higher proportion of effector memory CD8+ T cells, and a lower frequency of CD27+CD28+CD4+/CD8+ T cells. Linear regression analysis revealed significant correlations between cancer stage and the frequency of B and T cell subsets, leukocyte count, and cytokine levels. Survival analysis demonstrated that patients with higher frequency of class-switched B cells had a worse prognosis, while patients with higher frequency of CD8+ effector T cells and lower frequency of CD4+57+ T cells appeared to have a better survival rate. These findings provide valuable insight into the immunological changes that occur during lung cancer progression and have the potential to inform the development of new immunotherapeutic strategies.

Image-based multiplex immune profiling of cancer tissues: translational implications. A report of the International Immuno-oncology Biomarker Working Group on Breast Cancer

Recent advances in the field of immuno-oncology have brought transformative changes in the management of cancer patients. The immune profile of tumours has been found to have key value in predicting disease prognosis and treatment response in various cancers. Multiplex immunohistochemistry and immunofluorescence have emerged as potent tools for the simultaneous detection of multiple protein biomarkers in a single tissue section, thereby expanding opportunities for molecular and immune profiling while preserving tissue samples. By establishing the phenotype of individual tumour cells when distributed within a mixed cell population, the identification of clinically relevant biomarkers with high-throughput multiplex immunophenotyping of tumour samples has great potential to guide appropriate treatment choices. Moreover, the emergence of novel multi-marker imaging approaches can now provide unprecedented insights into the tumour microenvironment, including the potential interplay between various cell types. However, there are significant challenges to widespread integration of these technologies in daily research and clinical practice. This review addresses the challenges and potential solutions within a structured framework of action from a regulatory and clinical trial perspective. New developments within the field of immunophenotyping using multiplexed tissue imaging platforms and associated digital pathology are also described, with a specific focus on translational implications across different subtypes of cancer. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Tumor epitope spreading by a novel multivalent therapeutic cellular vaccine targeting cancer antigens to invariant NKT-triggered dendritic cells in situ

Introduction

Cancer is categorized into two types based on the microenvironment: cold and hot tumors. The former is challenging to stimulate through immunity. The immunogenicity of cancer relies on the quality and quantity of cancer antigens, whether recognized by T cells or not. Successful cancer immunotherapy hinges on the cancer cell type, antigenicity and subsequent immune reactions. The T cell response is particularly crucial for secondary epitope spreading, although the factors affecting these mechanisms remain unknown. Prostate cancer often becomes resistant to standard therapy despite identifying several antigens, placing it among immunologically cold tumors. We aim to leverage prostate cancer antigens to investigate the potential induction of epitope spreading in cold tumors. This study specifically focuses on identifying factors involved in secondary epitope spreading based on artificial adjuvant vector cell (aAVC) therapy, a method established as invariant natural killer T (iNKT) -licensed DC therapy.

Methods

We concentrated on three prostate cancer antigens (prostate-specific membrane antigen (PSMA), prostate-specific antigen (PSA), and prostatic acid phosphatase (PAP)). By introducing allogeneic cells with the antigen and murine CD1d mRNA, followed by α-galactosylceramide (α-GalCer) loading, we generated five types of aAVCs, i.e, monovalent, divalent and trivalent antigen-expressing aAVCs and four types of prostate antigen-expressing cold tumors. We evaluated iNKT activation and antigen-specific CD8+ T cell responses against tumor cells prompted by the aAVCs.

Results

Our study revealed that monovalent aAVCs, expressing a single prostate antigen, primed T cells for primary tumor antigens and also induced T cells targeting additional tumor antigens by triggering a tumor antigen-spreading response. When we investigated the immune response by trivalent aAVC (aAVC-PROS), aAVC-PROS therapy elicited multiple antigen-specific CD8+ T cells simultaneously. These CD8+ T cells exhibited both preventive and therapeutic effects against tumor progression.

Conclusions

The findings from this study highlight the promising role of tumor antigen-expressing aAVCs, in inducing efficient epitope spreading and generating robust immune responses against cancer. Our results also propose that multivalent antigen-expressing aAVCs present a promising therapeutic option and could be a more comprehensive therapy for treating cold tumors like prostate cancer.

Spatial features of specific CD103+CD8+ tissue-resident memory T cell subsets define the prognosis in patients with non-small cell lung cancer

BACKGROUND

Tissue-resident memory T (TRM) cells can reside in the tumor microenvironment and are considered the primary response cells to immunotherapy. Heterogeneity in functional status and spatial distribution may contribute to the controversial role of TRM cells but we know little about it.

METHODS

Through multiplex immunofluorescence (mIF) (CD8, CD103, PD-1, Tim-3, GZMB, CK), the quantity and spatial location of TRM cell subsets were recognized in the tissue from 274 patients with NSCLC after radical surgery. By integrating multiple machine learning methods, we constructed a TRM-based spatial immune signature (TRM-SIS) to predict the prognosis. Furthermore, we conducted a CD103-related gene set enrichment analysis (GSEA) and verified its finding by another mIF panel (CD8, CD103, CK, CD31, Hif-1α).

RESULTS

The density of TRM cells was significantly correlated with the expression of PD-1, Tim-3 and GZMB. Four types of TRM cell subsets was defined, including TRM1 (PD-1-Tim-3-TRM), TRM2 (PD-1+Tim-3-TRM), TRM3 (PD-1-Tim-3+TRM) and TRM4 (PD-1+Tim-3+TRM). The cytotoxicity of TRM2 was the strongest while that of TRM4 was the weakest. Compare with TRM1 and TRM2, TRM3 and TRM4 had better infiltration and stronger interaction with cancer cells. The TRM-SIS was an independent prognostic factor for disease-free survival [HR = 2.43, 95%CI (1.63-3.60), P < 0.001] and showed a better performance than the TNM staging system for recurrence prediction. Furthermore, by CD103-related GSEA and mIF validation, we found a negative association between tumor angiogenesis and infiltration of TRM cells.

CONCLUSIONS

These findings reveal a significant heterogeneity in the functional status and spatial distribution of TRM cells, and support it as a biomarker for the prognosis of NSCLC patients. Regulating TRM cells by targeting tumor angiogenesis may be a potential strategy to improve current immunotherapy.

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.

CD8+ Cell Density Gradient across the Tumor Epithelium-Stromal Interface of Non-Muscle Invasive Papillary Urothelial Carcinoma Predicts Recurrence-Free Survival after BCG Immunotherapy

BACKGROUND

Bacille Calmette-Guerin (BCG) immunotherapy is the first-line treatment in patients with high-risk non-muscle invasive papillary urothelial carcinoma (NMIPUC), the most common type of bladder cancer. The therapy outcomes are variable and may depend on the immune response within the tumor microenvironment. In our study, we explored the prognostic value of CD8+ cell density gradient indicators across the tumor epithelium-stroma interface of NMIPUC.

METHODS

Clinical and pathologic data were retrospectively collected from 157 NMIPUC patients treated with BCG immunotherapy after transurethral resection. Whole-slide digital image analysis of CD8 immunohistochemistry slides was used for tissue segmentation, CD8+ cell quantification, and the assessment of CD8+ cell densities within the epithelium-stroma interface. Subsequently, the gradient indicators (center of mass and immunodrop) were computed to represent the density gradient across the interface.

RESULTS

By univariable analysis of the clinicopathologic factors, including the history of previous NMIPUC, poor tumor differentiation, and pT1 stage, were associated with shorter RFS (p < 0.05). In CD8+ analyses, only the gradient indicators but not the absolute CD8+ densities were predictive for RFS (p < 0.05). The best-performing cross-validated model included previous episodes of NMIPUC (HR = 4.4492, p = 0.0063), poor differentiation (HR = 2.3672, p = 0.0457), and immunodrop (HR = 5.5072, p = 0.0455).

CONCLUSIONS

We found that gradient indicators of CD8+ cell densities across the tumor epithelium-stroma interface, along with routine clinical and pathology data, improve the prediction of RFS in NMIPUC.

Advances in cancer vaccines for immunotherapy of prostate cancer

Prostate cancer is currently one of the most common malignancies that endanger the lives and health of elderly men. In recent years, immunotherapy, which exploits the activation of anti-cancer host immune cells to accomplish tumor-killing effects, has emerged as a new study avenue in the treatment of prostate cancer. As an important component of immunotherapy, cancer vaccines have a unique position in the precision treatment of malignant tumors. Monocyte cell vaccines, dendritic cell vaccines, viral vaccines, peptide vaccines, and DNA/mRNA vaccines are the most often used prostate cancer vaccines. Among them, Sipuleucel-T, as a monocyte cell-based cancer vaccine, is the only FDA-approved therapeutic vaccine for prostate cancer, and has a unique position and role in advancing the development of immunotherapy for prostate cancer. However, due to its own limitations, Sipuleucel-T has not been widely adopted. Meanwhile, owing to the complexity of immunotherapy and the specificity of prostate cancer, the remaining prostate cancer vaccines have not shown good clinical benefit in large randomized phase II and phase III trials, and further in-depth studies are still needed.

Prognostic Value of CD8+ Lymphocytes in Hepatocellular Carcinoma and Perineoplastic Parenchyma Assessed by Interface Density Profiles in Liver Resection Samples

Hepatocellular carcinoma (HCC) often emerges in the setting of long-standing inflammatory liver disease. CD8 lymphocytes are involved in both the antitumoral response and hepatocyte damage in the remaining parenchyma. We investigated the dual role of CD8 lymphocytes by assessing density profiles at the interfaces of both HCC and perineoplastic liver parenchyma with surrounding stroma in whole-slide immunohistochemistry images of surgical resection samples. We applied a hexagonal grid-based digital image analysis method to sample the interface zones and compute the CD8 density profiles within them. The prognostic value of the indicators was explored in the context of clinicopathological, peripheral blood testing, and surgery data. Independent predictors of worse OS were a low standard deviation of CD8+ density along the tumor edge, high mean CD8+ density within the epithelial aspect of the perineoplastic liver-stroma interface, longer duration of surgery, a higher level of aspartate transaminase (AST), and a higher basophil count in the peripheral blood. A combined score, derived from these five independent predictors, enabled risk stratification of the patients into three prognostic categories with a 5-year OS probability of 76%, 40%, and 8%. Independent predictors of longer RFS were stage pT1, shorter duration of surgery, larger tumor size, wider tumor-free margin, and higher mean CD8+ density in the epithelial aspect of the tumor-stroma interface. We conclude that (1) our computational models reveal independent and opposite prognostic impacts of CD8+ cell densities at the interfaces of the malignant and non-malignant epithelium interfaces with the surrounding stroma; and (2) together with pathology, surgery, and laboratory data, comprehensive prognostic models can be constructed to predict patient outcomes after liver resection due to HCC.

Application of digital pathology and machine learning in the liver, kidney and lung diseases

The development of rapid and accurate Whole Slide Imaging (WSI) has paved the way for the application of Artificial Intelligence (AI) to digital pathology. The availability of WSI in the recent years allowed the rapid development of various AI technologies to blossom. WSI-based digital pathology combined with neural networks can automate arduous and time-consuming tasks of slide evaluation. Machine Learning (ML)-based AI has been demonstrated to outperform pathologists by eliminating inter- and intra-observer subjectivity, obtaining quantitative data from slide images, and extracting hidden image patterns that are relevant to disease subtype and progression. In this review, we outline the functionality of different AI technologies such as neural networks and deep learning and discover how aspects of different diseases make them benefit from the implementation of AI. AI has proven to be valuable in many different organs, with this review focusing on the liver, kidney, and lungs. We also discuss how AI and image analysis not only can grade diseases objectively but also discover aspects of diseases that have prognostic value. In the end, we review the current status of the integration of AI in pathology and share our vision on the future of digital pathology.

PD-1T TILs as a Predictive Biomarker for Clinical Benefit to PD-1 Blockade in Patients with Advanced NSCLC

PURPOSE

Durable clinical benefit to PD-1 blockade in non-small cell lung cancer (NSCLC) is currently limited to a small fraction of patients, underlining the need for predictive biomarkers. We recently identified a tumor-reactive tumor-infiltrating T lymphocyte (TIL) pool, termed PD-1T TILs, with predictive potential in NSCLC. Here, we examined PD-1T TILs as biomarker in NSCLC.

EXPERIMENTAL DESIGN

PD-1T TILs were digitally quantified in 120 baseline samples from advanced NSCLC patients treated with PD-1 blockade. Primary outcome was disease control (DC) at 6 months. Secondary outcomes were DC at 12 months and survival. Exploratory analyses addressed the impact of lesion-specific responses, tissue sample properties, and combination with other biomarkers on the predictive value of PD-1T TILs.

RESULTS

PD-1T TILs as a biomarker reached 77% sensitivity and 67% specificity at 6 months, and 93% and 65% at 12 months, respectively. Particularly, a patient group without clinical benefit was reliably identified, indicated by a high negative predictive value (NPV) (88% at 6 months, 98% at 12 months). High PD-1T TILs related to significantly longer progression-free (HR 0.39, 95% CI, 0.24-0.63, P < 0.0001) and overall survival (HR 0.46, 95% CI, 0.28-0.76, P < 0.01). Predictive performance was increased when lesion-specific responses and samples obtained immediately before treatment were assessed. Notably, the predictive performance of PD-1T TILs was superior to PD-L1 and tertiary lymphoid structures in the same cohort.

CONCLUSIONS

This study established PD-1T TILs as predictive biomarker for clinical benefit to PD-1 blockade in patients with advanced NSCLC. Most importantly, the high NPV demonstrates an accurate identification of a patient group without benefit. See related commentary by Anagnostou and Luke, p. 4835.

Multiplex immunohistochemistry and high-throughput image analysis for evaluation of spatial tumor immune cell markers in human breast cancer

BACKGROUND

The clinicopathological significance of spatial tumor-infiltrating lymphocytes (TILs) subpopulations is not well studied due to lack of high-throughput scalable methodology for studies with large human sample sizes.

OBJECTIVE

Establishing a cyclic fluorescent multiplex immunohistochemistry (mIHC/IF) method coupled with computer-assisted high-throughput quantitative analysis to evaluate associations of six TIL markers (CD3, CD8, CD20, CD56, FOXP3, and PD-L1) with clinicopathological factors of breast cancer.

METHODS

Our 5-plex mIHC/IF staining was shown to be reliable and highly sensitive for labeling three biomarkers per tissue section. Through repetitive cycles of 5-plex mIHC/IF staining, more than 12 biomarkers could be detected per single tissue section. Using open-source software CellProfiler, the measurement pipelines were successfully developed for high-throughput multiplex evaluation of intratumoral and stromal TILs.

RESULTS

In analyses of 188 breast cancer samples from the Nashville Breast Health Study, high-grade tumors showed significantly increased intratumoral CD3+CD8+ CTL density (P= 0.0008, false discovery rate (FDR) adjusted P= 0.0168) and intratumoral PD-L1 expression (P= 0.0061, FDR adjusted P= 0.0602) compared with low-grade tumors.

CONCLUSIONS

The high- and low-grade breast cancers exhibit differential immune responses which may have clinical significances. The multiplexed imaging quantification strategies established in this study are reliable, cost-efficient and applicable in regular laboratory settings for high-throughput tissue biomarker studies, especially retrospective and population-based studies using archived paraffin tissues.

DNA Supramolecular Assembly on Micro/Nanointerfaces for Bioanalysis

ConspectusFacing increasing demand for precision medicine, materials chemistry systems for bioanalysis with accurate molecular design, controllable structure, and adjustable biological activity are required. As a genetic biomacromolecule, deoxyribonucleic acid (DNA) is created via precise, efficient, and mild processes in life systems and can in turn precisely regulate life activities. From the perspective of materials chemistry, DNA possesses the characteristics of sequence programmability and can be endowed with customized functions by the rational design of sequences. In recent years, DNA has been considered to be a potential biomaterial for analysis and has been applied in the fields of bioseparation, biosensing, and detection imaging. To further improve the precision of bioanalysis, the supramolecular assembly of DNA on micro/nanointerfaces is an effective strategy to concentrate functional DNA modules, and thus the functions of DNA molecules for bioanalysis can be enriched and enhanced. Moreover, the new modes of DNA supramolecular assembly on micro/nanointerfaces enable the integration of DNA with the introduced components, breaking the restriction of limited functions of DNA materials and achieving more precise regulation and manipulation in bioanalysis. In this Account, we summarize our recent work on DNA supramolecular assembly on micro/nanointerfaces for bioanalysis from two main aspects. In the first part, we describe DNA supramolecular assembly on the interfaces of microscale living cells. The synthesis strategy of DNA is based on rolling-circle amplification (RCA), which generates ultralong DNA strands according to circular DNA templates. The templates can be designed with complementary sequences of functional modules such as aptamers, which allow DNA to specifically bind with cellular interfaces and achieve efficient cell separation. In the second part, we describe DNA supramolecular assembly on the interfaces of nanoscale particles. DNA sequences are designed with functional modules such as targeting, drug loading, and gene expression and then are assembled on interfaces of particles including upconversion nanoparticles (UCNPs), gold nanoparticles (AuNPs), and magnetic nanoparticle (MNPs). The integration of DNA with these functional particles achieves cell manipulation, targeted tumor imaging, and cellular regulation. The processes of interfacial assembly are well controlled, and the functions of the obtained bioanalytical materials can be flexibly regulated. We envision that the work on DNA supramolecular assembly on micro/nanointerfaces will be a typical paradigm for the construction of more bioanalytical materials, which we hope will facilitate the development of precision medicine.

Relationship between consolidation tumor ratio and tumor-infiltrating lymphocytes in small-sized lung adenocarcinoma

Background

Consolidation tumor ratio (CTR) is associated with cancer progression and histological invasiveness in lung adenocarcinoma (LAD). However, little is known about the association between CTR and immune‐related factors, including tumor‐infiltrating lymphocytes (TILs) density or tumor expression of programmed death ligand 1 (PD‐L1) and indoleamine 2,3‐dioxygenase 1 (IDO1) in small‐sized LAD.

Methods

This study included 258 patients with LAD (<3 cm) who underwent surgery. Patients were assigned to four groups: CTR = 0; 0 < CTR <0.5; 0.5 ≤ CTR <1 (ground‐glass opacity [GGO] group); and CTR = 1 (pure‐solid group). CD4⁺, CD8⁺, and FoxP3⁺ TIL density and PD‐L1 and IDO1 tumor expression were assessed by immunohistochemistry.

Results

Among the GGO group, CD8⁺ and FoxP3⁺ TIL density increased significantly with increasing CTR (p < 0.001 and p < 0.001, respectively). Moreover, PD‐L1 and IDO1 expression was significantly higher in the pure‐solid group than in the GGO group (p < 0.001 and p < 0.001, respectively).

Conclusions

CTR was correlated with the abundance of CD8⁺ and FoxP3⁺ TILs in the GGO group. PD‐L1 and IDO1 positivity rates were significantly higher in the pure‐solid group than in the GGO group. Increased CTR may be correlated with immunosuppressive condition.

Immune contexture of paediatric cancers

BACKGROUND

The clinical development of immune checkpoint-targeted immunotherapies has been disappointing so far in paediatric solid tumours. However, as opposed to adults, very little is known about the immune contexture of paediatric malignancies.

METHODS

We investigated by gene expression and immunohistochemistry (IHC) the immune microenvironment of five major paediatric cancers: Ewing sarcoma (ES), osteosarcoma (OS), rhabdomyosarcoma (RMS), medulloblastoma (MB) and neuroblastoma (NB; 20 cases each; n = 100 samples total), and correlated them with overall survival.

RESULTS

NB and RMS tumours had high immune cell gene expression values and high T-cell counts but were low for antigen processing cell (APC) genes. OS and ES tumours showed low levels of T-cells but the highest levels of APC genes. OS had the highest levels of macrophages (CSF1R, CD163 and CD68), whereas ES had the lowest. MB appeared as immune deserts. Tregs (FOXP3 staining) were higher in both RMS and OS. Most tumours scored negative for PD-L1 in tumour and immune cells, with only 11 of 100 samples positive for PD-L1 staining. PD-L1 and OX40 levels were generally low across all five indications. Interestingly, NB had comparable levels of CD8 by IHC and by gene expression to adult tumours. However, by gene expression, these tumours were low for T-cell cytotoxic molecules GZMB, GZMA and PRF1. Surprisingly, the lower the level of tumour infiltrative CD8 T-cells, the better the prognosis was in NB, RMS and ES. Gene expression analyses showed that MYCN-amplified NB have higher amounts of immune suppressive cells such as macrophages, myeloid-derived suppressor cells and Tregs, whereas the non-MYCN-amplified tumours were more infiltrated and had higher expression levels of Teff.

CONCLUSIONS

Our results describe the quality and quantity of immune cells across five major paediatric cancers and provide some key features differentiating these tumours from adult tumour types. These findings explain why anti-PD(L)1 might not have had single agent success in paediatric cancers. These results provides the rationale for the development of biologically stratified and personalised immunotherapy strategies in children with relapsing/refractory cancers.

Development and validation of a computed tomography-based immune ecosystem diversity index as an imaging biomarker in non-small cell lung cancer

OBJECTIVES

To date, there are no data on the noninvasive surrogate of intratumoural immune status that could be prognostic of survival outcomes in non-small cell lung cancer (NSCLC). We aimed to develop and validate the immune ecosystem diversity index (iEDI), an imaging biomarker, to indicate the intratumoural immune status in NSCLC. We further investigated the clinical relevance of the biomarker for survival prediction.

METHODS

In this retrospective study, two independent NSCLC cohorts (Resec1, n = 149; Resec2, n = 97) were included to develop and validate the iEDI to classify the intratumoural immune status. Paraffin-embedded resected specimens in Resec1 and Resec2 were stained by immunohistochemistry, and the density percentiles of CD3⁺, CD4⁺, and CD8⁺ T cells to all cells were quantified to estimate intratumoural immune status. Then, EDI features were extracted using preoperative computed tomography to develop an imaging biomarker, called iEDI, to determine the immune status. The prognostic value of iEDI was investigated on NSCLC patients receiving surgical resection (Resec1; Resec2; internal cohort Resec3, n = 419; external cohort Resec4, n = 96; and TCIA cohort Resec5, n = 55).

RESULTS

iEDI successfully classified immune status in Resec1 (AUC 0.771, 95% confidence interval [CI] 0.759-0.783; and 0.770 through internal validation) and Resec2 (0.669, 0.647-0.691). Patients with higher iEDI-score had longer overall survival (OS) in Resec3 (unadjusted hazard ratio 0.335, 95%CI 0.206-0.546, p < 0.001), Resec4 (0.199, 0.040-1.000, p < 0.001), and TCIA (0.303, 0.098-0.944, p = 0.001).

CONCLUSIONS

iEDI is a non-invasive surrogate of intratumoural immune status and prognostic of OS for NSCLC patients receiving surgical resection.

KEY POINTS

• Decoding tumour immune microenvironment enables advanced biomarkers identification. • Immune ecosystem diversity index characterises intratumoural immune status noninvasively. • Immune ecosystem diversity index is prognostic for NSCLC patients.

Validation of an Accurate Automated Multiplex Immunofluorescence Method for Immuno-Profiling Melanoma

Multiplex immunofluorescence staining enables the simultaneous detection of multiple immune markers in a single tissue section, and is a useful tool for the identification of specific cell populations within the tumour microenvironment. However, this technology has rarely been validated against standard clinical immunohistology, which is a barrier for its integration into clinical practice. This study sought to validate and investigate the accuracy, precision and reproducibility of a multiplex immunofluorescence compared with immunohistochemistry (IHC), including tissue staining, imaging and analysis, in characterising the expression of immune and melanoma markers in both the tumour and its microenvironment. Traditional chromogenic IHC, single-plex immunofluorescence and multiplex immunofluorescence were each performed on serial tissue sections of a formalin-fixed paraffin-embedded (FFPE) tissue microarray containing metastatic melanoma specimens from 67 patients. The panel included the immune cell markers CD8, CD68, CD16, the immune checkpoint PD-L1, and melanoma tumour marker SOX10. Slides were stained with the Opal^™ 7 colour Kit (Akoya Biosciences) on the intelliPATH autostainer (Biocare Medical) and imaged using the Vectra 3.0.5 microscope. Marker expression was quantified using Halo v.3.2.181 (Indica Labs). Comparison of the IHC and single-plex immunofluorescence revealed highly significant positive correlations between the cell densities of CD8, CD68, CD16, PD-L1 and SOX10 marker positive cells (Spearman’s rho = 0.927 to 0.750, p < 0.0001). Highly significant correlations were also observed for all markers between single-plex immunofluorescence and multiplex immunofluorescence staining (Spearman’s rho >0.9, p < 0.0001). Finally, correlation analysis of the three multiplex replicates revealed a high degree of reproducibility between slides (Spearman’s rho >0.940, p < 0.0001). Together, these data highlight the reliability and validity of multiplex immunofluorescence in accurately profiling the tumour and its associated microenvironment using FFPE metastatic melanoma specimens. This validated multiplex panel can be utilised for research evaluating melanoma and its microenvironment, such as studies performed to predict patient response or resistance to immunotherapies.

Tumor Microenvironment in Mixed Neuroendocrine Non-Neuroendocrine Neoplasms: Interaction between Tumors and Immune Cells, and Potential Effects of Neuroendocrine Differentiation on the Tumor Microenvironment

The tumor microenvironment is considered to play a pivotal role in various human malignancies. Neuroendocrine and non-neuroendocrine neoplasms are considered to have different tumor microenvironments. However, owing to differences in the systemic and/or local immune statuses, tumor microenvironments in different patients may be difficult to compare. Mixed neuroendocrine non-neuroendocrine neoplasms (MiNENs), although rare, could be useful for exploring the effects of neuroendocrine differentiation on the tumor microenvironment, because both neuroendocrine and non-neuroendocrine components are present in the same tumor. Here, we examined 33 cases of histologically confirmed MiNENs and evaluated the influence of neuroendocrine differentiation on the tumor microenvironment by comparing tumor-infiltrating lymphocytes, tumor-associated macrophages, and other relevant factors in the two components the same tumor. The immunoreactivity of those examined above was evaluated quantitatively. The values of vasohibin-1-positive density (p < 0.0001) and immunoreactivity (p < 0.0001) (representing the neoangiogenesis status) were significantly higher in neuroendocrine as compared to non-neuroendocrine areas of the same tumors. In addition, the Foxp3/CD8 (p = 0.0717) and the PD-1/CD8 ratios (p = 0.0176) (representing tumor immunity suppression) tend to increase in neuroendocrine carcinomas. Immunoreactivity of CD163, a marker of M2-like macrophages, was also higher in the neuroendocrine areas. Our findings indicate that neuroendocrine and non-neuroendocrine tumors differ from each other with respect to the characteristics of both tumor cells and the tumor microenvironment.

Tumor Microenvironment in Mixed Neuroendocrine Non-Neuroendocrine Neoplasms: Interaction between Tumors and Immune Cells, and Potential Effects of Neuroendocrine Differentiation on the Tumor Microenvironment

The tumor microenvironment is considered to play a pivotal role in various human malignancies. Neuroendocrine and non-neuroendocrine neoplasms are considered to have different tumor microenvironments. However, owing to differences in the systemic and/or local immune statuses, tumor microenvironments in different patients may be difficult to compare. Mixed neuroendocrine non-neuroendocrine neoplasms (MiNENs), although rare, could be useful for exploring the effects of neuroendocrine differentiation on the tumor microenvironment, because both neuroendocrine and non-neuroendocrine components are present in the same tumor. Here, we examined 33 cases of histologically confirmed MiNENs and evaluated the influence of neuroendocrine differentiation on the tumor microenvironment by comparing tumor-infiltrating lymphocytes, tumor-associated macrophages, and other relevant factors in the two components the same tumor. The immunoreactivity of those examined above was evaluated quantitatively. The values of vasohibin-1-positive density (p < 0.0001) and immunoreactivity (p < 0.0001) (representing the neoangiogenesis status) were significantly higher in neuroendocrine as compared to non-neuroendocrine areas of the same tumors. In addition, the Foxp3/CD8 (p = 0.0717) and the PD-1/CD8 ratios (p = 0.0176) (representing tumor immunity suppression) tend to increase in neuroendocrine carcinomas. Immunoreactivity of CD163, a marker of M2-like macrophages, was also higher in the neuroendocrine areas. Our findings indicate that neuroendocrine and non-neuroendocrine tumors differ from each other with respect to the characteristics of both tumor cells and the tumor microenvironment.

Assessing the Potential Prognostic and Immunological Role of TK1 in Prostate Cancer

Background: It has been reported that thymidine kinase 1 (TK1) was up-regulated in multiple malignancies and participated in the regulation of tumor malignant behavior. However, its specific role in prostate cancer (PCa) remains unclear. Methods: TK1 expression in PCa patients and cell lines was identified via crossover analysis of the public datasets. A series of in vitro experiments and in vivo models was applied to investigate the function of TK1 in PCa. Functional enrichment analyses were further conducted to explore the underlying mechanism. Additionally, TISIDB was applied to explore the correlation between TK1 expression and tumor-infiltrating lymphocytes, immune subtypes, and immune regulatory factors. Results: TK1 expression was significantly up-regulated in PCa patients and cell lines. TK1 ablation inhibited tumor cell proliferation and migration potential, and in vivo experiments showed that TK1 inactivation can significantly restrain tumor growth. Functional enrichment analysis revealed TK1-related hub genes (AURKB, CCNB2, CDC20, CDCA5, CDK1, CENPA, CENPM, KIF2C, NDC80, NUF2, PLK1, SKA1, SPC25, ZWINT), and found that TK1 was closely involved in the regulation of cell cycle. Moreover, elevated mRNA expression of TK1 was related with higher Gleason score, higher clinical stage, higher pathological stage, higher lymph node stage, shorter overall survival, and DFS in PCa patients. Particularly, TK1 represented attenuated expression in C3 PCa and was related with infiltration of CD4+, CD8+ T cells, and dendritic cells as well as immunomodulator expression. Conclusion: Our study indicates that TK1 is a prognostic predictor correlated with poor outcomes of PCa patients, and for the first time represented that TK1 can promote the progression of PCa. Therefore, TK1 may be a potential diagnostic and prognostic biomarker, as well as a therapeutic target for PCa.

Deep Learning-Based Mapping of Tumor Infiltrating Lymphocytes in Whole Slide Images of 23 Types of Cancer

The role of tumor infiltrating lymphocytes (TILs) as a biomarker to predict disease progression and clinical outcomes has generated tremendous interest in translational cancer research. We present an updated and enhanced deep learning workflow to classify 50x50 um tiled image patches (100x100 pixels at 20x magnification) as TIL positive or negative based on the presence of 2 or more TILs in gigapixel whole slide images (WSIs) from the Cancer Genome Atlas (TCGA). This workflow generates TIL maps to study the abundance and spatial distribution of TILs in 23 different types of cancer. We trained three state-of-the-art, popular convolutional neural network (CNN) architectures (namely VGG16, Inception-V4, and ResNet-34) with a large volume of training data, which combined manual annotations from pathologists (strong annotations) and computer-generated labels from our previously reported first-generation TIL model for 13 cancer types (model-generated annotations). Specifically, this training dataset contains TIL positive and negative patches from cancers in additional organ sites and curated data to help improve algorithmic performance by decreasing known false positives and false negatives. Our new TIL workflow also incorporates automated thresholding to convert model predictions into binary classifications to generate TIL maps. The new TIL models all achieve better performance with improvements of up to 13% in accuracy and 15% in F-score. We report these new TIL models and a curated dataset of TIL maps, referred to as TIL-Maps-23, for 7983 WSIs spanning 23 types of cancer with complex and diverse visual appearances, which will be publicly available along with the code to evaluate performance.

Code Available at:https://github.com/ShahiraAbousamra/til_classification.

Clinical significance of CD8-positive lymphocytes on tumor cell clusters of ascites cell block in ovarian high-grade serous carcinoma

Background

The clinical significance of CD8‐positive (CD8⁺) lymphocytes on tumor cell clusters of ascites cell blocks in patients with ovarian high‐grade serous carcinoma (HGSC) was investigated.

Methods

Among HGSC patients who underwent surgery from January 2014 to December 2019, 38 patients with ascites cell block were selected. Using these cell blocks and primary ovarian tumor tissue, the presence of CD8⁺ lymphocytes and the expression of PD‐L1 were examined immunohistochemically. Tumor cell clusters were defined as cell clumps consisting of more than 10 malignant cells in cell block. Cases with at least one CD8⁺ lymphocyte in tumor cell cluster were defined as positive CD8⁺ lymphocytes (Group A); others were defined as negative CD8⁺ lymphocytes (Group B). The tumor tissue CD8⁺ lymphocytes were counted mechanically. Clinicopathological features were retrospectively compared between the two groups.

Results

In total, 38 cases were identified: 25 (65.8%) in Group A and 13 (34.2%) in Group B. More cases in Group A were positive for CD4 (p < 0.01), PD‐L1 (p = 0.02), FoxP3 (p = 0.02) and had a higher number of CD8⁺ lymphocytes in the tissue (p = 0.03). Patients in Group A had better progression‐free survival (p < 0.01) and overall survival (p = 0.04). In multivariate analysis, Group A was an independent prognostic factor for both progression‐free survival (hazard ratio, 0.24; p < 0.01) and overall survival (hazard ratio, 0.21; p = 0.03).

Conclusion

The presence of CD8⁺ lymphocytes in tumor cell clusters of ascites was associated with the status of immune reaction in the tissue and prognosis in patients with HGSC and might be useful information of the immune‐associated therapy.

Peripheral lymphocyte count as a surrogate marker of immune checkpoint inhibitor therapy outcomes in patients with non-small-cell lung cancer

Degree of expression of programmed death-ligand 1 (PD-L1) is related with Immune check point inhibitors (ICIs) response but it needs sufficient tumor tissue. There is unmet need for easily accessible and prognostic peripheral blood (PB) biomarkers. We investigated the application of serum peripheral lymphocyte count (PLC) as a predictive PB biomarker for ICI response in patients with NSCLC. We conducted a retrospective study and reviewed the patients with NSCLC who were treated with ICIs from April 1, 2016, to March 31, 2019. The PLC before and after 1 month of immunotherapy was collected. We evaluated the association between PLC and progression-free survival (PFS), overall survival (OS) and adverse events. A total of 231 patients were treated with ICIs for NSCLC. The median follow-up period was 4.7 months and the disease progressed in 138 patients (59.7%). Compared with the lowest quartile (Q1: the lowest 25%), the highest quartile (Q4: the highest 25%) of post-treatment PLC showed a significantly higher PFS (HR 0.28, 95% CI 0.16–0.52) and OS (HR 0.35, 95% CI 0.19–0.65) in the adjusted model. An association between adverse events and PLC was not observed. We revealed that an increased pre- and post-treatment PLC was associated with favorable PFS and OS with NSCLC patients treated with ICIs. PLC could be a helpful for ICI responses in NSCLC.

Digital pathology and artificial intelligence in translational medicine and clinical practice

Traditional pathology approaches have played an integral role in the delivery of diagnosis, semi-quantitative or qualitative assessment of protein expression, and classification of disease. Technological advances and the increased focus on precision medicine have recently paved the way for the development of digital pathology-based approaches for quantitative pathologic assessments, namely whole slide imaging and artificial intelligence (AI)-based solutions, allowing us to explore and extract information beyond human visual perception. Within the field of immuno-oncology, the application of such methodologies in drug development and translational research have created invaluable opportunities for deciphering complex pathophysiology and the discovery of novel biomarkers and drug targets. With an increasing number of treatment options available for any given disease, practitioners face the growing challenge of selecting the most appropriate treatment for each patient. The ever-increasing utilization of AI-based approaches substantially expands our understanding of the tumor microenvironment, with digital approaches to patient stratification and selection for diagnostic assays supporting the identification of the optimal treatment regimen based on patient profiles. This review provides an overview of the opportunities and limitations around implementing AI-based methods in biomarker discovery and patient selection and discusses how advances in digital pathology and AI should be considered in the current landscape of translational medicine, touching on challenges this technology may face if adopted in clinical settings. The traditional role of pathologists in delivering accurate diagnoses or assessing biomarkers for companion diagnostics may be enhanced in precision, reproducibility, and scale by AI-powered analysis tools.

T Lymphocyte-Captured DNA Network for Localized Immunotherapy

The efficient isolation of immune cells with high purity and low cell damage is important for immunotherapy and remains highly challenging. We herein report a cell capture DNA network containing polyvalent multimodules for the specific isolation and in situ incubation of T lymphocytes (T-cells). Two ultralong DNA chains synthesized by an enzymatic amplification process were rationally designed to include functional multimodules as cell anchors and immune adjuvants. Mutually complementary sequences facilitated the formation of a DNA network and encapsulation of T-cells, as well as offering cutting sites of a restriction enzyme for the responsive release of T-cells and immune adjuvants. The purity of captured tumor-infiltrating T-cells reached 98%, and the viability of T-cells maintained ∼90%. The T-cells-containing DNA network was further administrated to a tumor lesion for localized immunotherapy. Our work provides a robust nanobiotechnology for efficient isolation of immune cells and other biological particles.

Tumour-infiltrating CD4-, CD8- and FOXP3-positive immune cells as predictive markers of mortality in BRCA1- and BRCA2-associated breast cancer

BACKGROUND

The prognostic value of tumour-infiltrating lymphocytes (TILs) in breast cancer is well-established. However, the investigation of specific T-cell subsets exclusively in BRCA-associated breast cancer is sparse.

METHODS

Tumour tissues from 414 BRCA-mutated breast cancer patients were analysed by immunohistochemistry and digital image analysis for expression of CD4, CD8 and FOXP3 immune markers. Distribution of CD4-, CD8- and FOXP3-positive cells and clinicopathological characteristics were assessed according to groups of low or high expression. The prognostic value was evaluated as continuous variables in univariate and multivariate analyses of overall survival and disease-free survival.

RESULTS

Both CD4 and CD8 expression are associated with histological diagnosis, tumour grade and oestrogen and progesterone receptor expression status. CD4 expression is associated with BRCA gene status. A high percentage of tumour-infiltrating CD4-, CD8- or FOXP3-positive cells is significantly associated with lower mortality in BRCA1- and BRCA2-associated breast cancer and CD8-positive cells are associated with disease-free survival. No heterogeneity according to BRCA gene status was found for the prognostic value of the immune markers.

CONCLUSIONS

The results support a prognostic role of specific T-cell subsets in BRCA-associated breast cancer and the promising potential of targeting the immune system in the treatment of these patients.

Proteomic Implications of Tumoral Infiltrating Lymphocytes in Melanoma: PD-L1, CD4 and CD8 - Short Review

Melanoma is a tumor developed by malignancy of melanocytes, being one of the most lethal cancers. Usually, it is associated with exposure to ultraviolet radiations, being most common in the skin, but can also be located extracutaneously as in the digestive tract, leptomeninges or uvea. Histopathologically it presents a phase of radial growth and a vertical one, often accompanied by an intra and peritumoral inflammatory infiltrate. Immunohistochemically, the confirmation of the diagnosis of melanoma should be accompanied by the assessment of proteomic markers of lymphocytic infiltrate such as PD-L1, CD4 and CD8. Those have a role in evaluating the prognosis and a possible prediction of the immunotherapeutic response.

Quantitative Image Analysis for Tissue Biomarker Use: A White Paper From the Digital Pathology Association

Tissue biomarkers have been of increasing utility for scientific research, diagnosing disease, and treatment response prediction. There has been a steady shift away from qualitative assessment toward providing more quantitative scores for these biomarkers. The application of quantitative image analysis has thus become an indispensable tool for in-depth tissue biomarker interrogation in these contexts. This white paper reviews current technologies being employed for quantitative image analysis, their application and pitfalls, regulatory framework demands, and guidelines established for promoting their safe adoption in clinical practice.

Analytical Concordance of PD-L1 Assays Utilizing Antibodies From FDA-Approved Diagnostics in Advanced Cancers: A Systematic Literature Review

PURPOSE

Four programmed death ligand 1 (PD-L1) immunohistochemistry assays (28-8, 22C3, SP263, and SP142) have been approved for use by the US Food and Drug Administration (FDA). Analytical concordance between these assays has been evaluated in multiple studies. This systematic review included studies that investigated the analytical concordance of immunohistochemistry assays utilizing two or more PD-L1 antibodies from FDA-approved diagnostics for evaluation of PD-L1 expression on tumor or immune cells across a range of tumor types and algorithms.

METHODS

Literature searches were conducted in MEDLINE (via PubMed) and EMBASE to identify studies published between January 1, 2010, and March 31, 2019, that evaluated analytical concordance between two or more assays based on antibodies from FDA-approved assays. Proceedings of key oncology and pathology congresses that took place between January 2016 and March 2019 were searched for abstracts of studies evaluating PD-L1 assay concordance.

RESULTS

A total of 42 studies across a range of tumor types met the selection criteria. Concordance between 28-8-, 22C3-, and SP263-based assays in lung cancer, urothelial carcinoma, and squamous cell carcinoma of the head and neck was high when used to assess PD-L1 expression on tumor cells (TCs). SP142-based assays had overall low concordance with other approved assays when used to assess PD-L1 expression on TCs. Analytical concordance for assessment of PD-L1 expression on immune cells was variable and generally lower than for PD-L1 expression on TCs.

CONCLUSION

A large body of evidence supports the potential interchangeability of 28-8-, 22C3-, and SP263-based assays for the assessment of PD-L1 expression on TCs in lung cancer. Further studies are required in tumor types for which less evidence is available.

PET imaging of immune checkpoint proteins in oncology

Despite the remarkable clinical successes of immune checkpoint inhibitors (ICIs) in various advanced cancers, response is still limited to a subset of patients that generally exhibit tumoral expression of immune checkpoint (IC) proteins. Development of biomarkers assessing the expression of such ICs is therefore a major challenge nowadays to refine patient selection and improve therapeutic benefits. Positron emission tomography (PET) imaging using IC-targeted radiolabeled monoclonal antibodies (immunoPET) provides a non-invasive and whole-body visualization of in vivo IC biodistribution. As such, PET imaging of ICs may serve as a robust biomarker to predict and monitor responses to ICIs, complementing the existing immunohistochemical techniques. Besides monoclonal antibodies, other PET radioligand formats, ranging from antibody-derived fragments to small proteins, have gained increasing interest owing to their faster pharmacokinetics and enhanced imaging characteristics. We provide an overview of the various strategies investigated so far for PET imaging of ICs in preclinical and clinical studies, emphasizing their benefits and limitations. Moreover, we discuss various parameters to consider for designing optimized and best-suited PET radioligands.

Prognostic Potential of Tumor-Infiltrating Immune Cells in Resectable Oral Squamous Cell Carcinoma

(1) Background: The immune microenvironment plays an important role in carcinogenesis and has prognostic potential in many types of cancer. In this study we assess the prognostic character of tumor-infiltrating immune cells CD4+, CD8+ and CD56+ in resectable oral squamous cell carcinoma (OSCC); (2) Methods: We have evaluated the densities of CD4+, CD8+ and CD56+ in two distinct compartments, intratumor and invasion front, in 90 patients with OSCC; (3) Results: Significant differences were found between the tumor compartments for the CD4+ and CD8+ lymphocytes. An improved outcome (OS) was seen in patients with high densities of intratumor CD8+ lymphocytes (p = 0.0086), CD8+ lymphocytes at the front of invasion (p = 0.0011) and for intratumor CD56+ cells (p = 0.0016). Multivariate analysis confirmed the independent prognostic role of CD8+ at the front of invasion (OR = 3.75, CI95% 1.17-12.35, p = 0.026) and for intratumor CD56+ cells (OR = 3.669, CI95% 1.09-15.37, p = 0.035); (4) Conclusions: Tumor-infiltrating CD8+ lymphocytes at the front of invasion and CD56+ in the intratumor compartment display predictive traits in OSCC. A reach immune infiltration with these types of cells is associated with an improved patient outcome.

Comparative analysis of assays to measure CAR T-cell-mediated cytotoxicity

The antitumor efficacy of genetically engineered 'living drugs', including chimeric antigen receptor and T-cell receptor T cells, is influenced by their activation, proliferation, inhibition, and exhaustion. A sensitive and reproducible cytotoxicity assay that collectively reflects these functions is an essential requirement for translation of these cellular therapeutic agents. Here, we compare various in vitro cytotoxicity assays (including chromium release, bioluminescence, impedance, and flow cytometry) with respect to their experimental setup, appropriate uses, advantages, and disadvantages, and measures to overcome their limitations. We also highlight the US Food and Drug Administration (FDA) directives for a potency assay for release of clinical cell therapy products. In addition, we discuss advanced assays of repeated antigen exposure and simultaneous testing of combinations of immune effector cells, immunomodulatory antibodies, and targets with variable antigen expression. This review article should help to equip investigators with the necessary knowledge to select appropriate cytotoxicity assays to test the efficacy of immunotherapeutic agents alone or in combination.

Development of DNA Vaccine Targeting E6 and E7 Proteins of Human Papillomavirus 16 (HPV16) and HPV18 for Immunotherapy in Combination with Recombinant Vaccinia Boost and PD-1 Antibody

Immunotherapy for cervical cancer should target high-risk human papillomavirus types 16 and 18, which cause 50% and 20% of cervical cancers, respectively. Here, we describe the construction and characterization of the pBI-11 DNA vaccine via the addition of codon-optimized human papillomavirus 18 (HPV18) E7 and HPV16 and 18 E6 genes to the HPV16 E7-targeted DNA vaccine pNGVL4a-SigE7(detox)HSP70 (DNA vaccine pBI-1). Codon optimization of the HPV16/18 E6/E7 genes in pBI-11 improved fusion protein expression compared to that in DNA vaccine pBI-10.1 that utilized the native viral sequences fused 3' to a signal sequence and 5' to the HSP70 gene of Mycobacterium tuberculosis Intramuscular vaccination of mice with pBI-11 DNA better induced HPV antigen-specific CD8+ T cell immune responses than pBI-10.1 DNA. Furthermore, intramuscular vaccination with pBI-11 DNA generated stronger therapeutic responses for C57BL/6 mice bearing HPV16 E6/E7-expressing TC-1 tumors. The HPV16/18 antigen-specific T cell-mediated immune responses generated by pBI-11 DNA vaccination were further enhanced by boosting with tissue-antigen HPV vaccine (TA-HPV). Combination of the pBI-11 DNA and TA-HPV boost vaccination with PD-1 antibody blockade significantly improved the control of TC-1 tumors and extended the survival of the mice. Finally, repeat vaccination with clinical-grade pBI-11 with or without clinical-grade TA-HPV was well tolerated in vaccinated mice. These preclinical studies suggest that the pBI-11 DNA vaccine may be used with TA-HPV in a heterologous prime-boost strategy to enhance HPV 16/18 E6/E7-specific CD8+ T cell responses, either alone or in combination with immune checkpoint blockade, to control HPV16/18-associated tumors. Our data serve as an important foundation for future clinical translation.IMPORTANCE Persistent expression of high-risk human papillomavirus (HPV) E6 and E7 is an obligate driver for several human malignancies, including cervical cancer, wherein HPV16 and HPV18 are the most common types. PD-1 antibody immunotherapy helps a subset of cervical cancer patients, and its efficacy might be improved by combination with active vaccination against E6 and/or E7. For patients with HPV16+ cervical intraepithelial neoplasia grade 2/3 (CIN2/3), the precursor of cervical cancer, intramuscular vaccination with a DNA vaccine targeting HPV16 E7 and then a recombinant vaccinia virus expressing HPV16/18 E6-E7 fusion proteins (TA-HPV) was safe, and half of the patients cleared their lesions in a small study (NCT00788164). Here, we sought to improve upon this therapeutic approach by developing a new DNA vaccine that targets E6 and E7 of HPV16 and HPV18 for administration prior to a TA-HPV booster vaccination and for application against cervical cancer in combination with a PD-1-blocking antibody.

Developing a Qualification and Verification Strategy for Digital Tissue Image Analysis in Toxicological Pathology

Digital tissue image analysis is a computational method for analyzing whole-slide images and extracting large, complex, and quantitative data sets. However, as with any analysis method, the quality of generated results is dependent on a well-designed quality control system for the entire digital pathology workflow. Such system requires clear procedural controls, appropriate user training, and involvement of specialists to oversee key steps of the workflow. The toxicologic pathologist is responsible for reporting data obtained by digital image analysis and therefore needs to ensure that it is correct. To accomplish that, they must understand the main parameters of the quality control system and should play an integral part in its conception and implementation. This manuscript describes the most common digital tissue image analysis end points and potential sources of analysis errors. In addition, it outlines recommended approaches for ensuring quality and correctness of results for both classical and machine-learning based image analysis solutions, as adapted from a recently proposed Food and Drug Administration regulatory framework for modifications to artificial intelligence/machine learning-based software as a medical device. These approaches are beneficial for any type of toxicopathologic study which uses the described end points and can be adjusted based on the intended use of the image analysis solution.

PD-1 blockade synergizes with intratumoral vaccination of a therapeutic HPV protein vaccine and elicits regression of tumor in a preclinical model

INTRODUCTION

The human papillomavirus (HPV) encoded oncoproteins E6 and E7 are constitutively expressed in HPV-associated cancers, making them logical therapeutic targets. Intramuscular immunization of patients with HPV16 L2E7E6 fusion protein vaccine (TA-CIN) is well tolerated and induces HPV-specific cellular immune responses. Efficacy of PD-1 immune checkpoint blockade correlates with the level of tumor-infiltrating CD8 + T cells, yet most patients lack significant tumor infiltration of immune cells making immune checkpoint blockade suboptimal. We hypothesized that intratumoral vaccination with TA-CIN could increase the number of tumor-infiltrating CD8 + T cells, synergize with PD-1 blockade and result in better control of tumors compared with either PD-1 blockade or vaccination alone.

METHODS

We examined the immunogenicity and antitumor effects of intratumoral vaccination with TA-CIN alone or in combination with PD-1 blockade in the TC-1 syngeneic murine tumor model expressing HPV16 E6/E7.

RESULTS

Intratumoral vaccination with TA-CIN induced stronger antigen-specific CD8 + T cell responses and antitumor effects. Intratumoral TA-CIN vaccination generated a systemic immune response that was able to control distal TC-1 tumors. Furthermore, intratumoral TA-CIN vaccination induced tumor infiltration of antigen-specific CD8 + T cells. Knockout of Batf3 abolished antigen-specific CD8 + T cell responses and antitumor effects of intratumoral TA-CIN vaccination. Finally, PD-1 blockade synergizes with intratumoral TA-CIN vaccination resulting in significantly enhanced antigen-specific CD8 + T cell responses and complete regression of tumors, whereas either alone failed to control established TC-1 tumor.

CONCLUSIONS

Our results provide rationale for future clinical testing of intratumoral TA-CIN vaccination in combination with PD-1 blockade for the control of HPV16-associated tumors.

Immunogenic characteristics of microsatellite instability-low esophagogastric junction adenocarcinoma based on clinicopathological, molecular, immunological and survival analyses

Microsatellite instability (MSI) is categorized by mutation frequency: high MSI (MSI-H), low MSI (MSI-L) and microsatellite stable (MSS). MSI-H tumors have a distinct immunogenic phenotype, with immunotherapies using checkpoint inhibitors already approved for the treatment of MSI-H gastroesophageal adenocarcinoma (GEA); this is not observed for MSI-L or MSS. Here, we tested the hypothesis that MSI-L tumors are also a distinct phenotype and potentially immunogenic. MSI-PCR assays (BAT25, BAT26, BAT40, D2S123, D5S346 and D17S250) were performed on 363 Epstein-Barr virus-negative, surgically resected esophagogastric junction (EGJ) adenocarcinoma samples. Tumors were characterized as MSI-H (≥2 markers), MSI-L (1 marker) or MSS (0 markers). CD8+ cell counts, PD-L1 and HER2 expression levels, TP53 mutations, epigenetic alterations and prognostic significance were also examined. All pathological and molecular experiments were conducted using serial, whole-tumor sections of chemo-naïve surgical specimens. MSI-H and MSI-L were assigned to 28 (7.7%) and 24 (6.6%) cases, respectively. Compared to MSS cases, MSI-L cases had significantly higher intratumoral CD8+ cell infiltration (P = .048) and favorable EGJ cancer-specific survival (multivariate hazard ratio = 0.35, 95% CI, 0.12-0.82; P = .012). MSI-L tumors were also significantly associated with TP53-truncating mutations as compared to MSI-H (P = .009) and MSS (P = .012) cases, and this trend was also observed in GEA data from The Cancer Genome Atlas (TCGA). Indel mutational burden among TCGA MSI-L tumors was significantly higher than that of MSS tumors (P = .016). These results suggest that MSI-L tumors may have a distinct tumor phenotype and be potentially immunogenic in EGJ adenocarcinoma.

Immuno-Interface Score to Predict Outcome in Colorectal Cancer Independent of Microsatellite Instability Status

Simple Summary

For pathologists, how to precisely diagnose cancer from microscopy slides of tumor tissue samples so that each patient may receive the optimal treatment for his specific type of disease is a major task. Recent research based on digital pathology image analysis enables new approaches to assess tumor-host interaction at a microscopic level. The current study applies a novel spatial analysis method which computes Immunogradient indicators to estimate the migration of immune cells towards the tumor across the tumor/stroma interface. These indicators, computed for two types of immune cells (CD8 and CD20), proved to be independent prognostic factors in this study of 87 patients with colorectal cancer. The indicators were combined with infiltrative tumor growth pattern, assessed by a pathologist, into a new immuno-interface score which enabled prediction of the patient survival independent of other clinical, pathology and molecular characteristics of the tumor. The study demonstrates the value of computational pathology to advance the precision of clinical decision-making.

Abstract

Tumor-associated immune cells have been shown to predict patient outcome in colorectal (CRC) and other cancers. Spatial digital image analysis-based cell quantification increases the informative power delivered by tumor microenvironment features and leads to new prognostic scoring systems. In this study we evaluated the intratumoral density of immunohistochemically stained CD8, CD20 and CD68 cells in 87 cases of CRC (48 were microsatellite stable, MSS, and 39 had microsatellite instability, MSI) in both the intratumoral tumor tissue and within the tumor-stroma interface zone (IZ) which was extracted by a previously developed unbiased hexagonal grid analytics method. Indicators of immune-cell gradients across the extracted IZ were computed and explored along with absolute cell densities, clinicopathological and molecular data, including gene mutation (BRAF, KRAS, PIK3CA) and MSI status. Multiple regression modeling identified (p < 0.0001) three independent prognostic factors: CD8+ and CD20+ Immunogradient indicators, that reflect cell migration towards the tumor, were associated with improved patient survival, while the infiltrative tumor growth pattern was linked to worse patient outcome. These features were combined into CD8-CD20 Immunogradient and immuno-interface scores which outperformed both tumor-node-metastasis (TNM) staging and molecular characteristics, and importantly, revealed high prognostic value both in MSS and MSI CRCs.

Safety and efficacy of single cycle induction treatment with cisplatin/docetaxel/ durvalumab/tremelimumab in locally advanced HNSCC: first results of CheckRad-CD8

Background

To determine safety and efficacy of single cycle induction treatment with cisplatin/docetaxel and durvalumab/tremelimumab in stage III-IVB head and neck cancer.

Methods

Patients received a single cycle of cisplatin 30 mg/m² on days 1–3 and docetaxel 75 mg/m² on day 1 combined with durvalumab 1500 mg fix dose on day 5 and tremelimumab 75 mg fix dose on day 5. Patients with pathologic complete response (pCR) in the rebiopsy after induction treatment or at least 20% increase of intratumoral CD8+ cell density in the rebiopsy compared with baseline entered radioimmunotherapy with concomitant durvalumab/tremelimumab. The objective of this interim analysis was to analyze safety and efficacy of the chemoimmunotherapy-induction treatment before radioimmunotherapy.

Results

A total of 57 patients were enrolled, 56 were treated. Median pretreatment intratumoral CD8+ cell density was 342 cells/mm². After induction treatment, 27 patients (48%) had a pCR in the rebiopsy and further 25 patients (45%) had a relevant increase of intratumoral CD8+ cells (median increase by a factor of 3.0). Adverse event (AE) grade 3–4 appeared in 38 patients (68%) and mainly consisted of leukopenia (43%) and infections (29%). Six patients (11%) developed grade 3–4 immune-related AE. Univariate analysis computed p16 positivity, programmed death ligand 1 immune cell area and intratumoral CD8+ cell density as predictors of pCR. On multivariable analysis, intratumoral CD8+ cell density predicted pCR independently (OR 1.0012 per cell/mm², 95% CI 1.0001 to 1.0022, p=0.016). In peripheral blood CD8+ cells, the coexpression of programmed death protein 1 significantly increased especially in patients with pCR.

Conclusions

Single cycle induction treatment with cisplatin/docetaxel and durvalumab/tremelimumab is feasible and achieves a high biopsy-proven pCR rate.

Treatment Combinations with DNA Vaccines for the Treatment of Metastatic Castration-Resistant Prostate Cancer (mCRPC)

Simple Summary

The only vaccine approved by FDA as a treatment for cancer is sipuleucel-T, a therapy for patients with metastatic castration-resistant prostate cancer (mCRPC). Most investigators studying anti-tumor vaccines believe they will be most effective as parts of combination therapies, rather than used alone. Unfortunately, the cost and complexity of sipuleucel-T makes it difficult to feasibly be used in combination with many other agents. In this review article we discuss the use of DNA vaccines as a simpler vaccine approach that has demonstrated efficacy in several animal species. We discuss the use of DNA vaccines in combination with traditional treatments for mCRPC, and other immune-modulating treatments, in preclinical and early clinical trials for patients with mCRPC.

Abstract

Metastatic castration-resistant prostate cancer (mCRPC) is a challenging disease to treat, with poor outcomes for patients. One antitumor vaccine, sipuleucel-T, has been approved as a treatment for mCRPC. DNA vaccines are another form of immunotherapy under investigation. DNA immunizations elicit antigen-specific T cells that cause tumor cell lysis, which should translate to meaningful clinical responses. They are easily amenable to design alterations, scalable for large-scale manufacturing, and thermo-stable for easy transport and distribution. Hence, they offer advantages over other vaccine formulations. However, clinical trials with DNA vaccines as a monotherapy have shown only modest clinical effects against tumors. Standard therapies for CRPC including androgen-targeted therapies, radiation therapy and chemotherapy all have immunomodulatory effects, which combined with immunotherapies such as DNA vaccines, could potentially improve treatment. In addition, many investigational drugs are being developed which can augment antitumor immunity, and together with DNA vaccines can further enhance antitumor responses in preclinical models. We reviewed the literature available prior to July 2020 exploring the use of DNA vaccines in the treatment of prostate cancer. We also examined various approved and experimental therapies that could be combined with DNA vaccines to potentially improve their antitumor efficacy as treatments for mCRPC.

Tackling Resistance to Cancer Immunotherapy: What Do We Know?

Cancer treatment has evolved tremendously in the last few decades. Immunotherapy has been considered to be the forth pillar in cancer treatment in addition to conventional surgery, radiotherapy, and chemotherapy. Though immunotherapy has resulted in impressive response, it is generally limited to a small subset of patients. Understanding the mechanisms of resistance toward cancer immunotherapy may shed new light to counter that resistance. In this review, we highlighted and summarized two major hurdles (recognition and attack) of cancer elimination by the immune system. The mechanisms of failure of some available immunotherapy strategies were also described. Moreover, the significance role of immune compartment for various established cancer treatments were also elucidated in this review. Then, the mechanisms of combinatorial treatment of various conventional cancer treatment with immunotherapy were discussed. Finally, a strategy to improve immune cancer killing by characterizing cancer immune landscape, then devising treatment based on that cancer immune landscape was put forward.

Bioengineering the Oxygen-Deprived Tumor Microenvironment Within a Three-Dimensional Platform for Studying Tumor-Immune Interactions

Oxygen deprivation within tumors is one of the most prevalent causes of resilient cancer cell survival and increased immune evasion in breast cancer (BCa). Current in vitro models do not adequately mimic physiological oxygen levels relevant to breast tissue and its tumor-immune interactions. In this study, we propose an approach to engineer a three-dimensional (3D) model (named 3D engineered oxygen, 3D-O) that supports the growth of BCa cells and generates physio- and pathophysiological oxygen levels to understand the role of oxygen availability in tumor-immune interactions. BCa cells (MDA-MB-231 and MCF-7) were embedded into plasma-derived 3D-O scaffolds that reflected physio- and pathophysiological oxygen levels relevant to the healthy and cancerous breast tissue. BCa cells grown within 3D-O scaffolds were analyzed by flow cytometry, confocal imaging, immunohistochemistry/immunofluorescence for cell proliferation, extracellular matrix protein expression, and alterations in immune evasive outcomes. Exosome secretion from 3D-O scaffolds were evaluated using the NanoSight particle analyzer. Peripheral blood mononuclear cells were incorporated on the top of 3D-O scaffolds and the difference in tumor-infiltrating capabilities as a result of different oxygen content were assessed by flow cytometry and confocal imaging. Lastly, hypoxia and Programmed death-ligand 1 (PD-L1) inhibition were validated as targets to sensitize BCa cells in order to overcome immune evasion. Low oxygen-induced adaptations within 3D-O scaffolds validated known tumor hypoxia characteristics such as reduced BCa cell proliferation, increased extracellular matrix protein expression, increased extracellular vesicle secretion and enhanced immune surface marker expression on BCa cells. We further demonstrated that low oxygen in 3D-O scaffolds significantly influence immune infiltration. CD8+ T cell infiltration was impaired under pathophysiological oxygen levels and we were also able to establish that hypoxia and PD-L1 inhibition re-sensitized BCa cells to cytotoxic CD8+ T cells. Bioengineering the oxygen-deprived BCa tumor microenvironment in our engineered 3D-O physiological and tumorous scaffolds supported known intra-tumoral hypoxia characteristics allowing the study of the role of oxygen availability in tumor-immune interactions. The 3D-O model could serve as a promising platform for the evaluation of immunological events and as a drug-screening platform tool to overcome hypoxia-driven immune evasion.

Digital image analysis in pathologist-selected regions of interest predicts survival more accurately than whole-slide analysis: a direct comparison study in 153 gastric carcinomas

Automatic quantification of biomarkers such as tumor‐infiltrating lymphocytes and PD‐L1 is one of the most studied topics in digital pathology image analysis (DIA). However, direct comparison between the DIA of a whole‐slide image (WSI) and that of regions of interest (ROIs) chosen by pathologists has not been performed. In this study, we aimed to compare the prognostic value of tumor microenvironment markers CD8 and PD‐L1, measured by DIA of WSIs and ROIs. We selected 153 primary gastric cancer tissues and stained them with CD8 and PD‐L1. All IHC slides were scanned at ×200 magnification and ratios of CD8 and PD‐L1 were measured in WSIs and ROIs from the invasive front, within the tumor, and the mucosa. Patients with high CD8 and PD‐L1 ratios showed more favorable outcomes compared to those with low ratios. Pathologist‐aided DIA predicted the survival of patients more accurately than WSI analysis (CD8, p = 0.025 versus p = 0.068; PD‐L1, p = 0.008 versus p = 0.2). Although a high density of CD8+ T cells at the invasive front correlated best with patient survival, CD8 ratio in the mucosa could also predict patient outcome. In conclusion, CD8 and PD‐L1 ratios measured by pathologist‐aided DIA predicted survival more accurately than WSI analyses and ROIs at the invasive front correlated best with patient outcome.

Onodera's prognostic nutritional index correlates with tumor immune environment and survival in patients with oral squamous cell carcinoma undergoing chemoradiotherapy

Pretreatment nutritional and immunological status is useful for predicting survival outcomes for various types of malignant tumors. Our objective was to determine the impact of the pretreatment Onodera's prognostic nutritional index (OPNI) on outcomes of patients who underwent definitive chemoradiotherapy for advanced oral squamous cell carcinoma (OSCC). We reviewed 47 patients treated for OSCC with definitive chemoradiotherapy (CRT) at our institution between January 2004 and December 2011. We determined the OPNI according to the following formula: 10 × serum albumin (g/dL) + 0.005 × total lymphocyte count (per μL). We determined the optimum OPNI cut-off through a receiver operating characteristic analysis. We analyzed the associations between OPNI status and various clinicopathological features and evaluated the effects of OPNI on the prognosis. We examined the relationships between OPNI and systemic inflammatory response parameters and analyzed intratumoral CD8+ T cells and their correlation with OPNI. The optimum OPNI cut-off was 42.7. A Kaplan–Meier curve analysis revealed that low OPNI was significantly associated with poor overall survival and cause-specific survival. The multivariate analysis revealed that low OPNI was independently correlated with poor 5 year overall survival and cause-specific survival. OPNI was significantly correlated with systemic inflammatory response parameters. Intratumoral CD8+ T cell counts in primary tumors were significantly lower for low OPNI than for high OPNI. The present data demonstrate that pretreatment OPNI is a valuable independent prognostic indicator of overall and cause-specific survival in advanced OSCC following definitive CRT. OPNI might reflect the tumor immune microenvironment characterization in OSCC.

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The optimum Onodera's prognostic nutritional index (OPNI) cut-off was 42.7 in OSCC patients who underwent definitive chemoradiotherapy

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Low OPNI was significantly associated with poor overall survival and cause-specific survival

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OPNI was significantly correlated with systemic inflammatory response parameters

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High-OPNI group showed significantly higher intratumoral CD8+ T cell counts in primary tumors

Automated detection algorithm for C4d immunostaining showed comparable diagnostic performance to pathologists in renal allograft biopsy

A deep learning-based image analysis could improve diagnostic accuracy and efficiency in pathology work. Recently, we proposed a deep learning-based detection algorithm for C4d immunostaining in renal allografts. The objective of this study is to assess the diagnostic performance of the algorithm by comparing pathologists' diagnoses and analyzing the associations of the algorithm with clinical data. C4d immunostaining slides of renal allografts were obtained from two different institutions (100 slides from the Asan Medical Center and 86 slides from the Seoul National University Hospital) and scanned using two different slide scanners. Three pathologists and the algorithm independently evaluated each slide according to the Banff 2017 criteria. Subsequently, they jointly reviewed the results for consensus scoring. The result of the algorithm was compared with that of each pathologist and the consensus diagnosis. Clinicopathological associations of the results of the algorithm with allograft survival, histologic evidence of microvascular inflammation, and serologic results for donor-specific antibodies were also analyzed. As a result, the reproducibility between the pathologists was fair to moderate (kappa 0.36-0.54), which is comparable to that between the algorithm and each pathologist (kappa 0.34-0.51). The C4d scores predicted by the algorithm achieved substantial concordance with the consensus diagnosis (kappa = 0.61), and they were significantly associated with remarkable microvascular inflammation (P = 0.001), higher detection rate of donor-specific antibody (P = 0.003), and shorter graft survival (P < 0.001). In conclusion, the deep learning-based C4d detection algorithm showed a diagnostic performance similar to that of the pathologists.

TBLR1 and CREBBP as potential novel prognostic immunohistochemical biomarkers in diffuse large B-cell lymphoma

Recent studies have identified prognostic mutational clusters for diffuse large B-cell lymphoma (DLBCL) patients, both within and outside the original cell-of-origin (COO) classification. For many of these mutations, there is limited information regarding the corresponding protein expression. With the aim to determine the relationship of protein expression and intensity to COO and prognosis, we used digital image analysis to quantitate immunohistochemical staining of CREBBP, IRF8, EZH2, and TBLR1 in 209 DLBCL patients. We found that patients with strong nuclear expression of TBLR1 had inferior progression-free survival (PFS) and overall survival (OS) in univariable analysis and inferior PFS in multivariable analysis. Patients with higher proportion of intermediate to strong nuclear CREBBP expression had a worse PFS and OS in univariable analysis. CREBBP was expressed with stronger intensity in non-GCB patients and the prognostic impact was restricted to this subgroup. These findings suggest that high nuclear protein expression of TBLR1 and CREBBP is negatively associated with prognosis in DLBCL.

Prevalence of CD8+ cytotoxic lymphocytes in human neoplasms

PURPOSE

Immune checkpoint inhibitors have recently been approved by the US FDA as first and/or second line therapy in a subset of cancer types. Recent evidence suggests that the quantity of tumor infiltrating lymphocytes (TILs) influences the likelihood of response to immune checkpoint inhibitors. Here, we set out to assess the density of CD8+ lymphocytes in a wide range of different cancer types and subtypes.

METHODS

The density of CD8+ lymphocytes was compared across different cancer types using tissue microarrays (TMAs) composed of up to 50 tumor samples each from 84 different cancer types and subtypes. In total 2652 cancers and 608 normal tissues were successfully analyzed by CD8 immunohistochemistry followed by automated image analysis of digitized slides.

RESULTS

We found that the median CD8+ lymphocyte counts ranged from 6 cells/mm2 in pleomorphic adenoma up to 1573 cells/mm2 in Hodgkin's lymphoma. The CD8 counts were generally lower in normal tissues compared to cancer tissues. Blood vessels of the spleen were the only non-lymphatic tissue staining positive for CD8. Tumor types approved for checkpoint inhibitor therapy, including malignant melanoma (81), muscle invasive urothelial carcinoma (119), small cell lung cancer (120), clear cell renal cell cancer (153), squamous cell carcinoma (189) and adenocarcinoma of the lung (328) as well as Hodgkin's lymphoma (1573) were all ranking among the upper half of our list. Comparably high CD8 densities (median cells/mm2) were also found in several rare and aggressive cancer types including Merkel cell carcinoma (70), angiosarcoma (95), anaplastic thyroid cancer (156) and embryonal carcinoma of the testis (186). In 73 of the 84 analyzed cancer types, the highly variable CD8 counts occasionally exceeded the average CD8 count of tumors for which checkpoint inhibitors have been approved.

CONCLUSION

These data support the concept that among most tumor types at least some individual cancers may benefit from treatment with immune checkpoint inhibitors.

The paratumoral immune cell signature reveals the potential for the implementation of immunotherapy in esophageal carcinoma patients

PURPOSE

Esophageal cancer (EC) is one of the most lethal gastrointestinal malignancies. Immunotherapy is a promising treatment modality for this disease. However, broader implementation of EC immunotherapy has been discouraged because of insufficient understanding of tumor interactions with the immune system. As with other malignancies, the current research on EC focuses on deciphering the immune cell signatures within the tumor microenvironment. However, the disease-elicited immune cell profiles in the paratumoral compartments are largely unknown.

METHODS

We examined the immune cell signatures in 62 tissue samples from 16 EC patients in different esophageal tissue compartments: tumor tissue, peritumoral tissue, healthy esophageal tissue, and adjacent lymph nodes. We analyzed the proportions and distribution patterns of NK cells and CD4⁺ and CD8⁺ T cells as well as their death receptor (FasR, FasR/DR3)-expressing subpopulations. The analyzed data were then compared and correlated with the patients' clinicopathological data.

RESULTS

We found that the FasR⁺ NK cells, CD4⁺ and CD8⁺ T cells infiltrated lymph nodes at the lowest levels and that the FasR⁺DR3⁺ CD4⁺ T cells were enhanced in tumors. The comparisons with the clinicopathological data revealed a major impact of active smoking on the reduction in paratumoral NK cells and the upregulation of FasR in tumor-infiltrating NK and CD8⁺ T cells. The lymph node metastatic stage, tumor stage, and Mandard grade correlated with the compartmental proportions of the evaluated immune cells.

CONCLUSION

The novel association of the disease state with tumoral and paratumoral immune cell signatures suggests new possibilities for personalized immunotherapy for EC patients.

Chance to rein in a cancer--Spontaneous regression of lung carcinoma (1988-2018): a 30-year perspective

BACKGROUND

Spontaneous regression of tumor is an extremely rare phenomenon in the oncology field and even rarer for lung cancer. However, the underlying mechanism is poorly understood. Summarizing the available clinical information and the supposed mechanism shed new light on lung cancer therapy strategies in the new era of immunotherapy.

SUMMARY

We conducted a PubMed search using the retrieval tactics ("Lung Neoplasms" [Mesh]) AND "Neoplasm Regression, Spontaneous" [Mesh] for reports from 1988 to January 2018, and all references in the relevant literature were subsequently investigated for relevance. Using the criteria of Everson and Cole, 14 cases were finally defined as spontaneous regression and were reviewed in the research. Key messages: The information regarding patient characteristics, treatments, and follow-up has been summarized. In this review, we found that spontaneous lung cancer regression cases fall into two categories including: (1) neurologic disorders in 6 cases, half of whom suffered with paraneoplastic neurological syndromes (PNS) and (2) immunological reactions in 7 cases. Getting data on more spontaneous regression cases and more detailed information will definitely help us understand the mechanism for the body's surveillance system-cancer balance, creating a big chance to increase cancer immunotherapy.

Phenotypic characterization of tumor CTLA-4 expression in melanoma tissues and its possible role in clinical response to Ipilimumab

The expression of the immune checkpoint molecule CTLA-4 has been almost exclusively studied in the T cell lineage, but increasing evidence has shown its expression on tumors with implications for immunotherapy. To date, the degree of expression of CTLA-4 on tumor cells as a predictive biomarker of response to immune checkpoint inhibitors has not been studied. In this report, we analyzed this issue in melanoma patients treated with CTLA-4 inhibitor Ipilimumab (IPI). We show that the level of CTLA-4 expression on melanoma cells is higher than that on tumor infiltrating lymphocytes (TIL) and it is associated with clinical response to IPI therapy supporting the idea of its possible role as a predictive biomarker.

Streamlined selection of cancer antigens for vaccine development through integrative multi-omics and high-content cell imaging

Identification of tumor antigens that induce cytotoxic T lymphocytes (CTLs) is crucial for cancer-vaccine development. Despite their predictive ability, current algorithmic approaches and human leukocyte antigen (HLA)-peptidomic analysis allow limited selectivity. Here, we optimized a method to rapidly screen and identify highly immunogenic epitopes that trigger CTL responses. We used a combined application of this method involving immune-specific signature analysis and HLA-associated peptidomics using samples from six patients with triple-negative breast cancer (TNBC) in order to select immunogenic HLA epitopes for in vitro testing. Additionally, we applied high-throughput imaging at the single-cell level in order to confirm the immunoreactivity of the selected peptides. The results indicated that this method enabled identification of promising CTL peptides capable of inducing antitumor immunity. This platform combining high-resolution computational analysis, HLA-peptidomics, and high-throughput immunogenicity testing allowed rapid and robust identification of highly immunogenic epitopes and represents a powerful technique for cancer-vaccine development.