Validation of biomarkers to predict response to immunotherapy in cancer: Volume I - pre-analytical and analytical validation

Cutting-edge 3D printing in immunosensor design for early cancer detection

Cancer is a major cause of death globally, and early detection is a key to improving outcomes. Traditional diagnostic methods have limitations such as being invasive and lacking sensitivity. Immunosensors, which detect cancer biomarkers using antibodies, offer a solution with high sensitivity and selectivity. When combined with 3D printing, these immunosensors can be customized to detect specific cancer markers, creating rapid, cost-effective, and scalable diagnostic tools. The article reviews the principles behind immunosensors, different 3D fabrication methods such as Fused Deposition Modeling (FDM) and Stereolithography (SLA), and discusses how functionalization strategies, such as surface modifications, can enhance the sensitivity of these devices. The integration of 3D printing allows for the creation of complex sensor structures, offering advantages such as customization, rapid prototyping, and multi-material printing. These advancements make immunosensors arrays highly promising for early cancer detection, tumor profiling, and personalized medicine. The article also explores challenges like scalability, material biocompatibility, and the need for clinical validation. Future perspectives suggest the potential of integrating nanomaterials, multiplexed detection, and wearable technology to further improve the performance and accessibility of these diagnostic tools.

Progress of Immune Checkpoint Inhibitors Therapy for pMMR/MSS Metastatic Colorectal Cancer

Immunotherapy is one of the research hotspots in colorectal cancer field in recent years. The colorectal cancer patients with mismatch repair-deficient (dMMR) or high microsatellite instability (MSI-H) are the primary beneficiaries of immunotherapy. However, the vast majority of colorectal cancers are mismatch repair proficient (pMMR) or microsatellite stability (MSS), and their immune microenvironment is characterized by "cold tumors" that are generally insensitive to single immunotherapy based on immune checkpoint inhibitors (ICIs). Studies have shown that some pMMR/MSS colorectal cancer patients regulate the immune microenvironment by combining other treatments, such as multi-target tyrosine kinase inhibitors, anti-vascular endothelial growth factor (VEGF) monoclonal antibodies, chemotherapy, radiotherapy, anti-epithelial growth factor receptor (EGFR) monoclonal antibodies, and mitogen-activated protein kinase (MAPK) signaling pathway inhibitors and oncolytic viruses, etc. to transform "cold tumor" into "hot tumor", thereby improving the response to immunotherapy. In addition, screening for potential prognostic biomarkers can also enrich the population benefiting from immunotherapy for microsatellite stable colorectal cancer. Therefore, in pMMR or MSS metastatic colorectal cancer (mCRC), the optimization of immunotherapy regimens and the search for effective efficacy prediction biomarkers are currently important research directions. In this paper, we review the progress of efficacy of immunotherapy (mainly ICIs) in pMMR /MSS mCRC, challenges and potential markers, in order to provide research ideas for the development of immunotherapy for mCRC.

Physiological markers for immunotherapeutics: a review

Immunotherapy has been advanced through multiple approaches, including immunogenic cytokines, monoclonal antibodies, therapeutic vaccinations, adoptive cell transfer, stem cell transplantation, and oncolytic viruses. This review analyses various strategies in genomics, transcriptomics, single-cell techniques, computational analysis, big data, and imaging technologies for the identification of tumour microbiota and microenvironments. Immunotherapy is becoming acknowledged as a feasible cancer treatment method, facilitating innovative cancer medicines and personalized medicine techniques.

Identification of Functional Immune Biomarkers in Breast Cancer Patients

Cancer immunotherapy has emerged as an effective, personalized treatment for certain patients, particularly for those with hematological malignancies. However, its efficacy in breast cancer has been marginal-perhaps due to cold, immune-excluded, or immune-desert tumors. Natural killer T (NKT) cells play a critical role in cancer immune surveillance and are reduced in cancer patients. Thus, we hypothesized that NKT cells could serve as a surrogate marker for immune function. In order to assess which breast cancer patients would likely benefit from immune cell-based therapies, we have developed a quantitative method to rapidly assess NKT function using stimulation with artificial antigen presenting cells followed by quantitative real-time PCR for IFN-γ. We observed a significant reduction in the percentage of circulating NKT cells in breast cancer patients, compared to healthy donors; however, the majority of patients had functional NKT cells. When we compared BC patients with highly functional NKT cells, as indicated by high IFN-γ induction, to those with little to no induction, following stimulation of NKT cells, there was no significant difference in NKT cell number between the groups, suggesting functional loss has more impact than physical loss of this subpopulation of T cells. In addition, we assessed the percentage of tumor-infiltrating lymphocytes and PD-L1 expression within the tumor microenvironment in the low and high responders. Further characterization of immune gene signatures in these groups identified a concomitant decrease in the induction of TNFα, LAG3, and LIGHT in the low responders. We next investigated the mechanisms by which breast cancers suppress NKT-mediated anti-tumor immune responses. We found that breast cancers secrete immunosuppressive lipids, and treatment with commonly prescribed medications that modulate lipid metabolism, can reduce tumor growth and restore NKT cell responses.

Highly Multiplexed Tissue Imaging in Precision Oncology and Translational Cancer Research

Precision oncology tailors treatment strategies to a patient's molecular and health data. Despite the essential clinical value of current diagnostic methods, hematoxylin and eosin morphology, immunohistochemistry, and gene panel sequencing offer an incomplete characterization. In contrast, highly multiplexed tissue imaging allows spatial analysis of dozens of markers at single-cell resolution enabling analysis of complex tumor ecosystems; thereby it has the potential to advance our understanding of cancer biology and supports drug development, biomarker discovery, and patient stratification. We describe available highly multiplexed imaging modalities, discuss their advantages and disadvantages for clinical use, and potential paths to implement these into clinical practice. Significance: This review provides guidance on how high-resolution, multiplexed tissue imaging of patient samples can be integrated into clinical workflows. It systematically compares existing and emerging technologies and outlines potential applications in the field of precision oncology, thereby bridging the ever-evolving landscape of cancer research with practical implementation possibilities of highly multiplexed tissue imaging into routine clinical practice.

Potential prognostic predictors of treatment with immune checkpoint inhibitors for advanced endometrial cancer

BACKGROUND

Prognostic predictors of immunotherapy in patients with advanced endometrial cancer remain unclear. The potential role of inflammatory predictors, including pretreatment neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio and hemoglobin, albumin, lymphocyte and platelet scores, was investigated.

METHODS

Between August 2018 and December 2023, 35 patients were retrospectively analyzed. Prognostic predictors were compared, and optimal cut-off values that exhibited the greatest discrimination for overall response, disease control, progression-free survival and overall survival were determined. Multivariate analysis was used to assess the prognostic significance of the predictors.

RESULTS

The greatest discrimination for overall response, progression-free survival and overall survival included platelet-to-lymphocyte ratio, neutrophil-to-lymphocyte ratio and hemoglobin, albumin, lymphocyte and platelet; the areas under the curve were 0.638, 0.649 and 0.641, respectively. The precise cut-off values of neutrophil-to-lymphocyte ratio for progression-free survival and overall survival were 4.92 and 5.40, respectively. The lower neutrophil-to-lymphocyte ratio group had a significantly longer progression-free survival (P = 0.001, median survival; 4.0 months vs. 19 months) and longer overall survival (P = 0.002, median survival; 5.0 months vs. 21 months). Of the risk factors assessed, neutrophil-to-lymphocyte ratio (hazard ratio = 4.409; 95% CI = 1.10-17.64; P = 0.036) and regimen (hazard ratio = 5.559; 95% CI = 1.26-24.49; P = 0.023) were independently correlated with overall survival.

CONCLUSION

In patients with advanced endometrial cancer, pretreatment neutrophil-to-lymphocyte ratio may be a prognostic predictor of those who would benefit from immunotherapy.

Personalized metabolic whole-body models for newborns and infants predict growth and biomarkers of inherited metabolic diseases

Comprehensive whole-body models (WBMs) accounting for organ-specific dynamics have been developed to simulate adult metabolism, but such models do not exist for infants. Here, we present a resource of 360 organ-resolved, sex-specific models of newborn and infant metabolism (infant-WBMs) spanning the first 180 days of life. These infant-WBMs were parameterized to represent the distinct metabolic characteristics of newborns and infants, including nutrition, energy requirements, and thermoregulation. We demonstrate that the predicted infant growth was consistent with the recommendation by the World Health Organization. We assessed the infant-WBMs' reliability and capabilities for personalization by simulating 10,000 newborns based on their blood metabolome and birth weight. Furthermore, the infant-WBMs accurately predicted changes in known biomarkers over time and metabolic responses to treatment strategies for inherited metabolic diseases. The infant-WBM resource holds promise for personalized medicine, as the infant-WBMs could be a first step to digital metabolic twins for newborn and infant metabolism.

Peripheral immune biomarkers for immune checkpoint inhibition of solid tumours

BACKGROUND

With the rapid adoption of immunotherapy for the treatment of cancer comes the pressing need for readily accessible biomarkers to guide immunotherapeutic strategies and offer insights into outcomes with specific treatments. Regular sampling of solid tumour tissues outside of melanoma for immune monitoring is not often feasible; conversely, routine, frequent interrogation of circulating immune biomarkers is entirely possible. As immunotherapies and immune checkpoint inhibitors, in particular, are more widely used in first-line, neoadjuvant, and metastatic settings, the discovery and validation of peripheral immune biomarkers are urgently needed across solid tumour types for improved prediction and prognostication of clinical outcomes in response to immunotherapy, as well as elucidation of mechanistic underpinnings of the intervention. Careful experimental design, encompassing both retrospective and prospective studies, is required in such biomarker identification studies, and concerted efforts are essential for their advancement into clinical settings.

CONCLUSION

In this review, we summarize shared immune features between the tumour microenvironment and systemic circulation, evaluate exploratory peripheral immune biomarker studies, and discuss associations between candidate biomarkers with clinical outcomes. We also consider integration of multiple peripheral immune parameters for better prediction and prognostication and discuss considerations in study design to further evaluate the clinical utility of candidate peripheral immune biomarkers for immunotherapy of solid tumours.

HIGHLIGHTS

Peripheral immune biomarkers are critical for improved prediction and prognostication of clinical outcomes for patients with solid tumours treated with immune checkpoint inhibition. Candidate peripheral biomarkers, such as cytokines, soluble factors, and immune cells, have potential as biomarkers to guide immunotherapy of solid tumours. Multiple peripheral immune parameters may be integrated to improve prediction and prognostication. The potential of peripheral immune biomarkers to guide immunotherapy of solid tumours requires critical work in biomarker discovery, validation, and standardization.

Stimulator of interferon genes mediated immune senescence reveals the immune microenvironment and prognostic characteristics of bladder cancer

Background

Studies have shown that the stimulator of interferon genes (STING) is critical in tumorigenesis, and development. This study aimed to investigate the immune profile and prognostic significance of STING-mediated immune senescence in bladder cancer (BLCA).

Methods

We identified differential genes between tumor and normal tissue based on the Cancer Genome Atlas database, and used consensus clustering to identify BLCA subtypes. The genes most associated with overall survival were screened by further analysis and used to construct risk models. Then, comparing the immune microenvironment, tumor mutational load (TMB), and microsatellite instability (MSI) scores between different risk groups. Eventually, a nomogram was constructed based on clinical information and risk scores. The model was validated using receiver operating curves (ROC) and calibration plots.

Results

We identified 160 differential genes, including 13 genes most associated with prognosis. Three subtypes of bladder cancer with different clinical and immunological features were identified. Immunotherapy was more likely to benefit the low-risk group, which had higher TMB and MSI scores. The nomogram was found to be highly predictive based on ROC analysis and calibration plots.

Conclusion

The risk model and nomogram not only predict the prognosis of BLCA patients but also can guide the treatment.

Motor Evoked Potential-A Pilot Study Looking at Reliability and Clinical Correlations in Multiple Sclerosis

PURPOSE

Multiple sclerosis (MS) is a clinically heterogeneous disease. Biomarkers that can assess pathological processes that are unseen with conventional imaging remain an unmet need in MS disease management. Motor evoked potentials (MEPs) could be such a biomarker. To determine and follow longitudinal MEP reliability and correlations with clinical measures in MS patients.

METHODS

This is a single-center study in alemtuzumab-treated MS patients to evaluate temporal reliability of MEPs, identify MEP minimum detectible differences, and explore correlations with existing clinical scales. Ten MS patients recently treated with alemtuzumab were evaluated every 6 months over 3 years. Clinical evaluations consisted of expanded disability status scale, timed 25-foot walk, 6-minute walk, and nine-hole peg test. MEPs were measured twice, 2 weeks apart, every 6 months.

RESULTS

Eight patients completed all 3 years of study. The intraclass correlation coefficient for MEP parameters ranged from 0.76 to 0.98. TA latency and amplitude with facilitation significantly and strongly correlated with all clinical measures, whereas the MEP duration modestly correlated. Biceps latency with facilitation significantly and moderately correlated with 9-hole peg test. Longitudinal correlations demonstrated good predictive values for either clinical deterioration or improvement.

CONCLUSIONS

MEPs have excellent intrapatient and intrarater reliability, and TA MEPs significantly and strongly correlated with expanded disability status scale, 6-minute walk, and timed 25-foot walk, whereas biceps MEPs significantly and moderately correlated with nine-hole peg test. Further studies using larger cohorts of MS patients are indicated.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov, Identifier: NCT02623946.

Current evidence of PD-1 and PD-L1 immune checkpoint inhibitors for esophageal cancer: an updated meta-analysis and synthesis of ongoing clinical trials

Background

Esophageal cancer (EC) is the sixth leading cause of cancer mortality worldwide, with a poor prognosis and a 5-year survival rate of 5% in advanced cases.

Objectives

To evaluate the efficacy of programmed death-1 (PD-1) and programmed death-ligand 1 (PD-L1) inhibitors in EC patients by analyzing phase III clinical trials.

Design

A meta-analysis following the PRISMA Statement 2020 guidelines.

Methods

PubMed/MEDLINE, Web of Science, and Embase were searched through 6 December 2022, and the analysis was conducted using Review Manager 5.4.3 (Cochrane).

Results

Out of 387 studies, 13 phase III clinical trials with 6519 participants were pooled. Overall survival (OS) favored PD-1/PD-L1 inhibitors with a Cohen's d of 0.28 (95% CI: 0.12-0.43; p = 0.0006), and the likelihood of achieving objective response also favored these inhibitors (OR: 2.04, 95% CI: 1.68-2.48; p < 0.0001).

Conclusion

This meta-analysis provides strong evidence that PD-1/PD-L1 inhibitors combined with chemotherapy improve OS and objective response rate among patients with advanced EC but do not affect progression-free survival.

Trial registration

Open Science Framework: osf.io/y27rx.

China special issue on gastrointestinal tumors-Regulatory-immunoscore-A novel indicator to guide precision adjuvant chemotherapy in colorectal cancer

Novel biomarkers are essential to improve the treatment efficacy and overall survival of stage II and III colorectal cancer (CRC), allowing for personalized treatment decisions. Here, the densities of CD8+ and FOXP3+ T cells in the tumor and invasive margin were processed by immunohistochemistry and digital pathology to form a scoring system named regulatory-Immunoscore (RIS). Cox proportional hazards regression models were used to determine the risk factors associated with time to recurrence. Harrell's concordance index and the time-dependent area under the curve were used to assess model performance. A total of 1213 stage I-III DNA mismatch repair-proficient colorectal cancer (pMMR CRC) patients were randomly assigned to a training set (n = 642) and a validation set (n = 571). From the Cox multivariable analysis, the association of RIS with survival was independent of patient age, sex and anatomy-based tumor risk parameters (P < .0001). For stage II patients, chemotherapy was significantly associated with better recurrence time in patients with low (95% confidence interval [CI]: 0.11-0.54, P = .001) and intermediate (95% CI = 0.25-0.57, P < .001) RIS values. In stage III patients treated with adjuvant chemotherapy, a treatment duration of 6 or more months was significantly associated with better recurrence time in patients with intermediate RIS values (95% CI = 0.38-0.90, P = .016) when compared with duration under 6 months. Therefore, these findings suggest that RIS is reliable for predicting recurrence risk and treatment responsiveness for patients with stage I-III pMMR CRC.

Multiplex imaging in immuno-oncology

Multiplex imaging has emerged as an invaluable tool for immune-oncologists and translational researchers, enabling them to examine intricate interactions among immune cells, stroma, matrix, and malignant cells within the tumor microenvironment (TME). It holds significant promise in the quest to discover improved biomarkers for treatment stratification and identify novel therapeutic targets. Nonetheless, several challenges exist in the realms of study design, experiment optimization, and data analysis. In this review, our aim is to present an overview of the utilization of multiplex imaging in immuno-oncology studies and inform novice researchers about the fundamental principles at each stage of the imaging and analysis process.

Image analysis-based tumor infiltrating lymphocytes measurement predicts breast cancer pathologic complete response in SWOG S0800 neoadjuvant chemotherapy trial

We assessed the predictive value of an image analysis-based tumor-infiltrating lymphocytes (TILs) score for pathologic complete response (pCR) and event-free survival in breast cancer (BC). About 113 pretreatment samples were analyzed from patients with stage IIB-IIIC HER-2-negative BC randomized to neoadjuvant chemotherapy ± bevacizumab. TILs quantification was performed on full sections using QuPath open-source software with a convolutional neural network cell classifier (CNN11). We used easTILs% as a digital metric of TILs score defined as [sum of lymphocytes area (mm2)/stromal area(mm2)] × 100. Pathologist-read stromal TILs score (sTILs%) was determined following published guidelines. Mean pretreatment easTILs% was significantly higher in cases with pCR compared to residual disease (median 36.1 vs.14.8%, p < 0.001). We observed a strong positive correlation (r = 0.606, p < 0.0001) between easTILs% and sTILs%. The area under the prediction curve (AUC) was higher for easTILs% than sTILs%, 0.709 and 0.627, respectively. Image analysis-based TILs quantification is predictive of pCR in BC and had better response discrimination than pathologist-read sTILs%.

Challenges and Opportunities in Clinical Diagnostic Routine of Envenomation Using Blood Plasma Proteomics

Specific and sensitive tools for the diagnosis and monitoring of accidents by venomous animals are urgently needed. Several diagnostic and monitoring assays have been developed; however, they have not yet reached the clinic. This has resulted in late diagnoses, which represents one of the main causes of progression from mild to severe disease. Human blood is a protein-rich biological fluid that is routinely collected in hospital settings for diagnostic purposes, which can translate research progress from the laboratory to the clinic. Although it is a limited view, blood plasma proteins provide information about the clinical picture of envenomation. Proteome disturbances in response to envenomation by venomous animals have been identified, allowing mass spectrometry (MS)-based plasma proteomics to emerge as a tool in a range of clinical diagnostics and disease management that can be applied to cases of venomous animal envenomation. Here, we provide a review of the state of the art on routine laboratory diagnoses of envenomation by snakes, scorpions, bees, and spiders, as well as a review of the diagnostic methods and the challenges encountered. We present the state of the art on clinical proteomics as the standardization of procedures to be performed within and between research laboratories, favoring a more excellent peptide coverage of candidate proteins for biomarkers. Therefore, the selection of a sample type and method of preparation should be very specific and based on the discovery of biomarkers in specific approaches. However, the sample collection protocol (e.g., collection tube type) and the processing procedure of the sample (e.g., clotting temperature, time allowed for clotting, and anticoagulant used) are equally important to eliminate any bias.

Circulating HPV DNA in HPV-associated cancers

Human papillomavirus (HPV) infections are the primary cause of almost all cervical cancers, anal cancers, and a variable proportion of other anogenital tumors, as well as head and neck cancers. Circulating HPV DNA (cHPV-DNA) is emerging as a biomarker with extensive potential in the management of HPV-driven malignancies. There has been a rapid advancement in the development of techniques for analyzing cHPV-DNA for the detection, characterization, and monitoring of HPV-associated cancers. As clinical evidence accumulates, it is becoming evident that cHPV-DNA can be used as a diagnostic tool. By conducting clinical trials assessing the clinical utility of cHPV-DNA, the full potential of cHPV-DNA for the screening, diagnosis, and treatment of HPV-related malignancies can be corroborated. In this review, we examine the current landscape of applications for cHPV-DNA liquid biopsies throughout the cancer care continuum, highlighting future opportunities for research and integration into clinical practice.

Artificial intelligence and digital biomarker in precision pathology guiding immune therapy selection and precision oncology

BACKGROUND

The currently available immunotherapies already changed the strategy how many cancers are treated from first to last line. Understanding even the most complex heterogeneity in tumor tissue and mapping the spatial cartography of the tumor immunity allows the best and optimized selection of immune modulating agents to (re-)activate the patient's immune system and direct it against the individual cancer in the most effective way.

RECENT FINDINGS

Primary cancer and metastases maintain a high degree of plasticity to escape any immune surveillance and continue to evolve depending on many intrinsic and extrinsic factors In the field of immune-oncology (IO) immune modulating agents are recognized as practice changing therapeutic modalities. Recent studies have shown that an optimal and lasting efficacy of IO therapeutics depends on the understanding of the spatial communication network and functional context of immune and cancer cells within the tumor microenvironment. Artificial intelligence (AI) provides an insight into the immune-cancer-network through the visualization of very complex tumor and immune interactions in cancer tissue specimens and allows the computer-assisted development and clinical validation of such digital biomarker.

CONCLUSIONS

The successful implementation of AI-supported digital biomarker solutions guides the clinical selection of effective immune therapeutics based on the retrieval and visualization of spatial and contextual information from cancer tissue images and standardized data. As such, computational pathology (CP) turns into "precision pathology" delivering individual therapy response prediction. Precision Pathology does not only include digital and computational solutions but also high levels of standardized processes in the routine histopathology workflow and the use of mathematical tools to support clinical and diagnostic decisions as the basic principle of a "precision oncology".

A Systematic Pan-Cancer Analysis of MEIS1 in Human Tumors as Prognostic Biomarker and Immunotherapy Target

BACKGROUND

We intended to explore the potential immunological functions and prognostic value of Myeloid Ecotropic Viral Integration Site 1 (MEIS1) across 33 cancer types.

METHODS

The data were acquired from The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx) and Gene expression omnibus (GEO) datasets. Bioinformatics was used to excavate the potential mechanisms of MEIS1 across different cancers.

RESULTS

MEIS1 was downregulated in most tumors, and it was linked to the immune infiltration level of cancer patients. MEIS1 expression was different in various immune subtypes including C2 (IFN-gamma dominant), C5 (immunologically quiet), C3 (inflammatory), C4 (lymphocyte depleted), C6 (TGF-b dominant) and C1 (wound healing) in various cancers. MEIS1 expression was correlated with Macrophages_M2, CD8+T cells, Macrophages_M1, Macrophages_M0 and neutrophils in many cancers. MEIS1 expression was negatively related to tumor mutational burden (TMB), microsatellite instability (MSI) and neoantigen (NEO) in several cancers. Low MEIS1 expression predicts poor overall survival (OS) in adrenocortical carcinoma (ACC), head and neck squamous cell carcinoma (HNSC), and kidney renal clear cell carcinoma (KIRC) patients, while high MEIS1 expression predicts poor OS in colon adenocarcinoma (COAD) and low grade glioma (LGG) patients.

CONCLUSION

Our findings revealed that MEIS1 is likely to be a potential new target for immuno-oncology.

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.

Bibliometric Analysis of Hotspots and Frontiers of Immunotherapy in Pancreatic Cancer

BACKGROUND

Pancreatic cancer is one of the most common malignant neoplasms with an increasing incidence, low rate of early diagnosis, and high degree of malignancy. In recent years, immunotherapy has made remarkable achievements in various cancer types including pancreatic cancer, due to the long-lasting antitumor responses elicited in the human body. Immunotherapy mainly relies on mobilizing the host's natural defense mechanisms to regulate the body state and exert anti-tumor effects. However, no bibliometric research about pancreatic cancer immunotherapy has been reported to date. This study aimed to assess research trends and offer possible new research directions in pancreatic cancer immunotherapy.

METHODS

The articles and reviews related to pancreatic cancer immunotherapy were collected from the Web of Science Core Collection. CiteSpace, VOSviewer, and an online platform, and were used to analyze co-authorship, citation, co-citation, and co-occurrence of terms retrieved from the literature highlighting the scientific advances in pancreatic cancer immunotherapy.

RESULTS

We collected 2475 publications and the number of articles was growing year by year. The United States had a strong presence worldwide with the most articles. The most contributing institution was Johns Hopkins University (103 papers). EM Jaffee was the most productive researcher with 43 papers, and L Zheng and RH Vonderheide ranked second and third, with 34 and 29 papers, respectively. All the keywords were grouped into four clusters: "immunotherapy", "clinical treatment study", "tumor immune cell expression", "tumor microenvironment". In the light of promising hotspots, keywords with recent citation bursts can be summarized into four aspects: immune microenvironment, adaptive immunotherapy, immunotherapy combinations, and molecular and gene therapy.

CONCLUSIONS

In recent decades, immunotherapy showed great promise for many cancer types, so various immunotherapy approaches have been introduced to treat pancreatic cancer. Understanding the mechanisms of immunosuppressive microenvironment, eliminating immune suppression and blocking immune checkpoints, and combining traditional treatments will be hotspots for future research.

Identification and validation of a PD-L1-related signature from mass spectrometry in gastric cancer

BACKGROUND

According to the guidelines, PD-L1 expression is a critical indicator for guiding immunotherapy application. According to certain studies, regardless of PD-L1 expression, immunotherapy could be advantageous for individuals with gastric cancer. Therefore, new scoring systems or biomarkers are required to enhance treatment strategies.

METHODS

Mass spectrometry and machine learning were used to search for strongly related PD-L1 genes, and the NMF approach was then used to separate gastric cancer patients into two categories. Differentially expressed genes (DEGs) between the two subtypes identified in this investigation were utilized to develop the UBscore predictive model, which was verified by the Gene Expression Omnibus (GEO) database. Coimmunoprecipitation, protein expression, and natural killing (NK) cell coculture experiments were conducted to validate the findings.

RESULTS

A total of 123 proteins were identified as PD-L1 interactors that are substantially enriched in the proteasome complex at the mRNA level. Using random forest, 30 UPS genes were discovered in the GSE66229 cohort, and ANAPC7 was experimentally verified as one of 123 PD-L1 interactors. Depending on the expression of PD-L1 and ANAPC7, patients were separated into two subgroups with vastly distinct immune infiltration. Low UBscore was related to increased tumor mutation burden (TMB) and microsatellite instability-high (MSI-H). In addition, chemotherapy medications were more effective in individuals with a low UBscore. Finally, we discovered that ANAPC7 might lead to the incidence of immunological escape when cocultured with NK-92 cells.

CONCLUSION

According to our analysis of the PD-L1-related signature in GC, the UBscore played a crucial role in prognosis and had a strong relationship with TMB, MSI, and chemotherapeutic drug sensitivity. This research lays the groundwork for improving GC patient prognosis and treatment response.

Immune microenvironment of cholangiocarcinoma: Biological concepts and treatment strategies

Cholangiocarcinoma is characterized by a poor prognosis with limited treatment and management options. Chemotherapy using gemcitabine with cisplatin is the only available first-line therapy for patients with advanced cholangiocarcinoma, although it offers only palliation and yields a median survival of < 1 year. Recently there has been a resurgence of immunotherapy studies focusing on the ability of immunotherapy to inhibit cancer growth by impacting the tumor microenvironment. Based on the TOPAZ-1 trial, the US Food and Drug Administration has approved the combination of durvalumab and gemcitabine with cisplatin as the first-line treatment of cholangiocarcinoma. However, immunotherapy, like immune checkpoint blockade, is less effective in cholangiocarcinoma than in other types of cancer. Although several factors such as the exuberant desmoplastic reaction are responsible for cholangiocarcinoma treatment resistance, existing literature on cholangiocarcinoma cites the inflammatory and immunosuppressive environment as the most common factor. However, mechanisms activating the immunosuppressive tumor microenvironment contributing to cholangiocarcinoma drug resistance are complicated. Therefore, gaining insight into the interplay between immune cells and cholangiocarcinoma cells, as well as the natural development and evolution of the immune tumor microenvironment, would provide targets for therapeutic intervention and improve therapeutic efficacy by developing multimodal and multiagent immunotherapeutic approaches of cholangiocarcinoma to overcome the immunosuppressive tumor microenvironment. In this review, we discuss the role of the inflammatory microenvironment-cholangiocarcinoma crosstalk and reinforce the importance of inflammatory cells in the tumor microenvironment, thereby highlighting the explanatory and therapeutic shortcomings of immunotherapy monotherapy and proposing potentially promising combinational immunotherapeutic strategies.

Emerging Nano-/Biotechnology Drives Oncolytic Virus-Activated and Combined Cancer Immunotherapy

Oncolytic viruses (OVs) as one promising antitumor methods have made important contributions to tumor immunotherapy, which arouse increasing attention. They provide the dual mechanisms including direct killing effect toward tumor cells and immune activation for elevating antitumor responses, which have been proved in many preclinical studies. Especially, natural or genetically modified viruses as clinical immune preparations have emerged as a new promising approach objective to oncology treatment. The approval of talimogene laherparepvec (T-VEC) by the U.S. Food and Drug Administration (FDA) for the therapy of advanced melanoma could be considered as a milestone achievement in the clinical translation of OV. In this review, we first discussed the antitumor mechanisms of OVs with an emphasis on targeting, replication, and propagation. We further outlined the state of the art of current OVs in tumor and underlined the activated biological effects especially including immunity. More significantly, the enhanced immune responses based on OVs were systematically discussed from different perspectives such as combination with immunotherapy, genetic engineering of OVs, integration with nanobiotechnology or nanoparticles, and antiviral response counteraction, where their principles were shed light on. The development of OVs in the clinics was also highlighted to analyze the actuality and concerns of different OV applications in clinical trials. At last, the future perspectives and challenges of OVs as an already widely accepted treatment means were discussed. This review will provide a systematic review and deep insight into OV development and also offer new opportunities and guidance pathways to drive the further clinical translation.

Innate immune function during antineoplastic treatment is associated with 12-months survival in non-small cell lung cancer

Introduction

The immune system has proven to be a key player in the progression as well as containment of cancer with new treatment strategies based on immunotherapy targeting this interaction. Assessing immune function could reveal critical information about the immune response to therapeutic interventions, revealing predictive biomarkers for tailored care and precision medicine.

Methods

We investigated immune function in 37 patients with inoperable non-small cell lung cancer (NSCLC) undergoing treatment with PD-L1 immune checkpoint inhibitor (ICI), chemotherapy (CT) or chemo-radiotherapy (CT/RT). Blood samples before (day 0) and during therapy (day 7, 21 and 80) were investigated by a standardized immunoassay, TruCulture®.

Results

Outcomes revealed a developing innate immune response induced by both immunotherapy and chemotherapy. NSCLC-patients displayed evidence of chronic innate immune activation and exhaustion prior to treatment. This pattern was particularly pronounced during treatment in patients dying within 12-months follow-up. Compared to treatment with CT, ICI demonstrated a higher ex vivo-stimulated release of proinflammatory cytokines.

Discussion

These preliminary findings may pave the way for tailored treatment and immune-monitoring.

One Step Nucleic Acid Amplification (OSNA) Lysate Samples Are Suitable to Establish a Transcriptional Metastatic Signature in Patients with Early Stage Hormone Receptors-Positive Breast Cancer

The One Step Nucleic Acid Amplification (OSNA) is being adopted worldwide for sentinel lymph nodes (SLNs) staging in breast cancer (BC). As major disadvantage, OSNA precludes prognostic information based on structural evaluation of SLNs. Our aim is to identify biomarkers related to tumor-microenvironment interplay exploring gene expression data from the OSNA remaining lysate. This study included 32 patients with early stage hormone receptors-positive BC. Remaining OSNA lysates were prepared for targeted RNA-sequencing analysis. Identification of differentially expressed genes (DEGs) was performed by DESeq2 in R and data analysis in STATA. The results show that, in metastatic SLNs, several genes were upregulated: KRT7, VTCN1, CD44, GATA3, ALOX15B, RORC, NECTIN2, LRG1, CD276, FOXM1 and IGF1R. Hierarchical clustering analysis revealed three different clusters. The identified DEGs codify proteins mainly involved in cancer aggressiveness and with impact in immune response. The overexpression of the immune suppressive genes VTCN1 and CD276 may explain that no direct evidence of activation of immune response in metastatic SLNs was found. We show that OSNA results may be improved incorporating microenvironment-related biomarkers that may be useful in the future for prognosis stratification and immunotherapy selection. As OSNA assay is being implemented for SLNs staging in other cancers, this approach could also have a wider utility.

Computational Biology Predicts the Efficacy of Tumor Immune Checkpoint Blockade

Tumor immunotherapy is considered as one of the most promising methods in cancer treatment in recent years. Immune checkpoint blockade (ICB) can activate immune cells to destroy tumors by relieving the inhibitory pathway of tumor cells to immune cells. In silico prediction of the ICB response is an important step toward achieving effective and personalized cancer immunotherapy. Although immune checkpoint inhibitors have shown exciting clinical effects in the treatment of many types of tumors, there are still some clinical problems in practical application, such as low response rate and large individualized differences. How to predict the efficacy of effective individualized immune checkpoint inhibitors for tumor patients based on specific biomarkers and computational models is one of the key issues in the immunotherapy of this kind of tumor. In our work, from the five levels of genome level, transcription level, epigenetic level, microbial taxonomy level, and the immune cell infiltration profile level, the biomarkers and in silico calculation methods that affect the efficacy of tumor immune checkpoint inhibitors are comprehensively summarized.

Study of PD-1 Customization and Autoimmune T Cells for Advanced Colorectal Cancer with High MSI Expression

Objective

To evaluate the significance of PD-1 customization and autoimmune T-cell therapy for advanced colorectal cancer with high MSI expression.

Methods

One hundred and eight patients with advanced colorectal cancer with high MSI expression admitted to our hospital between August 2019 and January 2022 were divided into control and study groups, and PD-1 customization and autoimmune T-cell therapy were administered to the two groups, respectively. Trends in immune indexes, PD-1 exposure, and survival rates were studied in both groups.

Results

The treatment efficiency of the study group was 90.74%, which was higher than that of the control group (61.11%) (P < 0. 05); after treatment, the presence of CDl07a, perforin, and GranB cells was significantly higher in both groups compared with that before treatment, but the expression of PD-1 was more pronounced in the study group (P < 0. 05); that is, the expression of PD-1 in peripheral T lymphocytes in the study group compared with that of the control group was higher in patients with grade III-IV, and peripheral T lymphocytes were also higher in patients with grade III-IV compared with patients with grade I-II (P < 0. 05).

Conclusion

PD-1 customization combined with autoimmune T-cell therapy is a novel therapeutic modality that can substantially improve.

Prognostic model of immune-related genes for patients with hepatocellular carcinoma

Background

Immune-related genes (IRGs) are closely connected to the occurrence and development of tumors. Their influence on the prognosis of patients with HCC, however, remains unclear.

Methods

From the TCGA database, we integrated 365 liver cancer tissues and 50 normal tissues to identify differential immune genes related to prognosis. Multivariate COX analysis was used to establish a new prognostic index on account of IRGs, whereby risk score = (Expression level of HSPA4*0.022) + (Expression level of PSMD14*0.042) + (Expression level of RBP2*0.019) + (Expression level of MAPT*0.197) + (Expression level of TRAF3*0.146) + (Expression level of NDRG1*(0.006) + (Expression level of NRAS*0.027) + (Expression level of IL17D*0.075).

Results

The risk score was clearly correlated with an unfavorable survival rate and with clinical characteristics. By integrating the immune-related risk score model with clinical features, a nomogram was constructed to predict the survival rate of HCC patients (1-, 3- and 5-year AUC of 0.721, 0.747 and 0.781, respectively).

Conclusion

We have established a valuable prognostic risk score for HCC patients that may be a better predictor of survival than the present method. With the risk score's strong predictive value for immune cells and functions, it may provide clinical guidance for the diagnosis and prognosis of different immunophenotypes, and provide multiple therapeutic targets for the treatment of HCC patients based on subtype-specific immune molecules.

The role of biomarkers in personalized immunotherapy

BACKGROUND

Immune checkpoint inhibitors have revolutionized cancer therapeutic paradigm and substantially improved the survival of patients with advanced malignancies. However, a significant limitation is the wide variability in clinical response.

MAIN TEXT

Several biomarkers have been evaluated in prior and ongoing clinical trials to investigate their prognostic and predictive role of patient response, nonetheless, most have not been comprehensively incorporated into clinical practice. We reviewed published data regarding biomarkers that have been approved by the United States Food and Drug Administration as well as experimental tissue and peripheral blood biomarkers currently under investigation. We further discuss the role of current biomarkers to predict response and response to immune checkpoint inhibitors and the promise of combination biomarker strategies. Finally, we discuss ideal biomarker characteristics, and novel platforms for clinical trial design including enrichment and stratification strategies, all of which are exciting and dynamic to advance the field of precision immuno-oncology.

CONCLUSION

Incorporation and standardization of strategies to guide selection of combination biomarker approaches will facilitate expansion of the clinical benefit of immune checkpoint inhibitor therapy to appropriate subsets of cancer patients.

Biomarkers of Response and Resistance to Immunotherapy in Microsatellite Stable Colorectal Cancer: Toward a New Personalized Medicine

Immune Checkpoint Inhibitors (ICIs) are well recognized as a major immune treatment modality for multiple types of solid cancers. However, for colorectal cancer (CRC), ICIs are only approved for the treatment of Mismatch-Repair-Deficient and Microsatellite Instability-High (dMMR/MSI-H) tumors. For the vast majority of CRC, that are not dMMR/MSI-H, ICIs alone provide limited to no clinical benefit. This discrepancy of response between CRC and other solid cancers suggests that CRC may be inherently resistant to ICIs alone. In translational research, efforts are underway to thoroughly characterize the immune microenvironment of CRC to better understand the mechanisms behind this resistance and to find new biomarkers of response. In the clinic, trials are being set up to study biomarkers along with treatments targeting newly discovered immune checkpoint molecules or treatments combining ICIs with other existing therapies to improve response in MSS CRC. In this review, we will focus on the characteristics of response and resistance to ICIs in CRC, and discuss promising biomarkers studied in recent clinical trials combining ICIs with other therapies.

The Essentials of Multiomics

Within the last decade, the science of molecular testing has evolved from single gene and single protein analysis to broad molecular profiling as a standard of care, quickly transitioning from research to practice. Terms such as genomics, transcriptomics, proteomics, circulating omics, and artificial intelligence are now commonplace, and this rapid evolution has left us with a significant knowledge gap within the medical community. In this paper, we attempt to bridge that gap and prepare the physician in oncology for multiomics, a group of technologies that have gone from looming on the horizon to become a clinical reality. The era of multiomics is here, and we must prepare ourselves for this exciting new age of cancer medicine.

Accounting for B-cell Behavior and Sampling Bias Predicts Anti-PD-L1 Response in Bladder Cancer

Cancer immunotherapy is predominantly based on T cell-centric approaches. At the same time, the adaptive immune response in the tumor environment also includes clonally produced immunoglobulins and clonal effector/memory B cells that participate in antigen-specific decisions through their interactions with T cells. Here, we investigated the role of infiltrating B cells in bladder cancer via patient dataset analysis of intratumoral immunoglobulin repertoires. We showed that the IgG1/IgA ratio is a prognostic indicator for several subtypes of bladder cancer and for the whole IMVigor210 anti-PD-L1 immunotherapy study cohort. A high IgG1/IgA ratio associated with the prominence of a cytotoxic gene signature, T-cell receptor signaling, and IL21-mediated signaling. Immunoglobulin repertoire analysis indicated that effector B-cell function, rather than clonally produced antibodies, was involved in antitumor responses. From the T-cell side, we normalized a cytotoxic signature against the extent of immune cell infiltration to neutralize the artificial sampling-based variability in immune gene expression. Resulting metrics reflected proportion of cytotoxic cells among tumor-infiltrating immune cells and improved prediction of anti-PD-L1 responses. At the same time, the IgG1/IgA ratio remained an independent prognostic factor. Integration of the B-cell, natural killer cell, and T-cell signatures allowed for the most accurate prediction of anti-PD-L1 therapy responses. On the basis of these findings, we developed a predictor called PRedIctive MolecUlar Signature (PRIMUS), which outperformed PD-L1 expression scores and known gene signatures. Overall, PRIMUS allows for reliable identification of responders among patients with muscle-invasive urothelial carcinoma, including the subcohort with the low-infiltrated "desert" tumor phenotype.

Prognostic Value of Programmed Death Ligand-1 Expression in Solid Tumors Irrespective of Immunotherapy Exposure: A Systematic Review and Meta-Analysis

BACKGROUND

The programmed cell death-1/programmed cell death ligand-1 (PD-L1) pathway, which plays a crucial role in cancer immune surveillance, is the target of several approved immunotherapeutic agents and is used as a predictive biomarker in some solid tumors. However, its use as a prognostic marker (i.e., regardless of therapy used) is not established clearly with available data demonstrating inconsistent prognostic impact of PD-L1 expression in solid tumors.

METHODS

We conducted a systematic literature search of electronic databases and identified publications exploring the effect of PD-L1 expression on overall survival and/or disease-free survival. Hazard ratios were pooled in a meta-analysis using generic inverse-variance and random-effects modeling. We used the Deeks method to explore subgroup differences based on disease site, stage of disease, and method of PD-L1 quantification.

RESULTS

One hundred and eighty-six studies met the inclusion criteria. Programmed cell death ligand-1 expression was associated with worse overall survival (hazard ratio 1.33, 95% confidence interval 1.26-1.39; p < 0.001). There was significant heterogeneity between disease sites (subgroup p = 0.002) with pancreatic, hepatocellular, and genitourinary cancers associated with the highest magnitude of adverse outcomes. Programmed cell death ligand-1 was also associated with worse overall disease-free survival (hazard ratio 1.19, 95% confidence interval 1.09-1.30; p < 0.001). Stage of disease did not significantly affect the results (subgroup p = 0.52), nor did the method of quantification via immunohistochemistry or messenger RNA (subgroup p = 0.70).

CONCLUSIONS

High expression of PD-L1 is associated with worse survival in solid tumors albeit with significant heterogeneity among tumor types. The effect is consistent in early-stage and metastatic disease and is not sensitive to method of PD-L1 quantification. These data can provide additional information for the counseling of patients with cancer about prognosis.

Immune Checkpoint Inhibitors in Non-Small Cell Lung Cancer: Progress, Challenges, and Prospects

Non-small cell lung cancer is one of the most common types of malignances worldwide and the main cause of cancer-related deaths. Current treatment for NSCLC is based on surgical resection, chemotherapy, radiotherapy, and targeted therapy, with poor therapeutic effectiveness. In recent years, immune checkpoint inhibitors have applied in NSCLC treatment. A large number of experimental studies have shown that immune checkpoint inhibitors are safer and more effective than traditional therapeutic modalities and have allowed for the development of better guidance in the clinical treatment of advanced NSCLC patients. In this review, we describe clinical trials using ICI immunotherapies for NSCLC treatment, the available data on clinical efficacy, and the emerging evidence regarding biomarkers.

A Novel Strategy to Identify Haematology Patients at High Risk of Developing Aspergillosis

Invasive Aspergillosis (IA), typically caused by the fungus Aspergillus fumigatus, is a leading cause of morbidity and mortality in immunocompromised patients. IA remains a significant burden in haematology patients, despite improvements in the diagnosis and treatment of Aspergillus infection. Diagnosing IA is challenging, requiring multiple factors to classify patients into possible, probable and proven IA cohorts. Given the low incidence of IA, using negative results as exclusion criteria is optimal. However, frequent false positives and severe IA mortality rates in haematology patients have led to the empirical use of toxic, drug-interactive and often ineffective anti-fungal therapeutics. Improvements in IA diagnosis are needed to reduce unnecessary anti-fungal therapy. Early IA diagnosis is vital for positive patient outcomes; therefore, a pre-emptive approach is required. In this study, we examined the sequence and expression of four C-type Lectin-like receptors (Dectin-1, Dectin-2, Mincle, Mcl) from 42 haematology patients and investigated each patient's anti-Aspergillus immune response (IL-6, TNF). Correlation analysis revealed novel IA disease risk factors which we used to develop a pre-emptive patient stratification protocol to identify haematopoietic stem cell transplant patients at high and low risk of developing IA. This stratification protocol has the potential to enhance the identification of high-risk patients whilst reducing unnecessary treatment, minimizing the development of anti-fungal resistance, and prioritising primary disease treatment for low-risk patients.

Explainable nucleus classification using Decision Tree Approximation of Learned Embeddings

MOTIVATION

Nucleus detection, segmentation and classification are fundamental to high-resolution mapping of the tumor microenvironment using whole-slide histopathology images. The growing interest in leveraging the power of deep learning to achieve state-of-the-art performance often comes at the cost of explainability, yet there is general consensus that explainability is critical for trustworthiness and widespread clinical adoption. Unfortunately, current explainability paradigms that rely on pixel saliency heatmaps or superpixel importance scores are not well-suited for nucleus classification. Techniques like Grad-CAM or LIME provide explanations that are indirect, qualitative and/or nonintuitive to pathologists.

RESULTS

In this article, we present techniques to enable scalable nuclear detection, segmentation and explainable classification. First, we show how modifications to the widely used Mask R-CNN architecture, including decoupling the detection and classification tasks, improves accuracy and enables learning from hybrid annotation datasets like NuCLS, which contain mixtures of bounding boxes and segmentation boundaries. Second, we introduce an explainability method called Decision Tree Approximation of Learned Embeddings (DTALE), which provides explanations for classification model behavior globally, as well as for individual nuclear predictions. DTALE explanations are simple, quantitative, and can flexibly use any measurable morphological features that make sense to practicing pathologists, without sacrificing model accuracy. Together, these techniques present a step toward realizing the promise of computational pathology in computer-aided diagnosis and discovery of morphologic biomarkers.

AVAILABILITY AND IMPLEMENTATION

Relevant code can be found at github.com/CancerDataScience/NuCLS.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

A high OXPHOS CD8 T cell subset is predictive of immunotherapy resistance in melanoma patients

Immune checkpoint inhibitor (ICI) therapy continues to revolutionize melanoma treatment, but only a subset of patients respond. Major efforts are underway to develop minimally invasive predictive assays of ICI response. Using single-cell transcriptomics, we discovered a unique CD8 T cell blood/tumor-shared subpopulation in melanoma patients with high levels of oxidative phosphorylation (OXPHOS), the ectonucleotidases CD38 and CD39, and both exhaustion and cytotoxicity markers. We called this population with high levels of OXPHOS "CD8+ TOXPHOS cells." We validated that higher levels of OXPHOS in tumor- and peripheral blood-derived CD8+ TOXPHOS cells correlated with ICI resistance in melanoma patients. We then developed an ICI therapy response predictive model using a transcriptomic profile of CD8+ TOXPHOS cells. This model is capable of discerning responders from nonresponders using either tumor or peripheral blood CD8 T cells with high accuracy in multiple validation cohorts. In sum, CD8+ TOXPHOS cells represent a critical immune population to assess ICI response with the potential to be a new target to improve outcomes in melanoma patients.

Proportional Tumor Infiltration of T Cells via Circulation Duplicates the T Cell Receptor Repertoire in a Bilateral Tumor Mouse Model

Temporal analysis of the T cell receptor (TCR) repertoire has been used to monitor treatment-induced changes in antigen-specific T cells in patients with cancer. However, the lack of experimental models that allow a temporal analysis of the TCR repertoire in the same individual in a homogeneous population limits the understanding of the causal relationship between changes in TCR repertoire and antitumor responses. A bilateral tumor model, where tumor cells were inoculated bilaterally into the backs of mice, could be used for temporal analysis of the TCR repertoire. This study examined the prerequisite for this strategy: the TCR repertoire is conserved between bilateral tumors that grow symmetrically. Bilateral tumors and draining lymph nodes (dLNs) were collected 13 days after tumor inoculation to analyze the TCR repertoire of CD4⁺ and CD8⁺ T cells. The tumor-infiltrating T-cell clones were highly similar between the bilateral tumors and expanded to a similar extent. In addition, the differences of TCR repertoire between the bilateral tumors were equivalent to Intra-tumoral heterogeneity on one side. On the other hand, the similarity of the TCR repertoire in the bilateral dLNs was markedly lower than that in the tumor, suggesting that tumor-reactive T cell clones induced independently in each dLN are mixed during recirculation and then proportionally infiltrated the bilateral tumors. These findings provide the basis for future analysis of temporal and treatment-induced changes in tumor-reactive T cell clones using this bilateral tumor model.

Synergy between Toxoplasma gondii type I ΔGRA17 immunotherapy and PD-L1 checkpoint inhibition triggers the regression of targeted and distal tumors

Background

In this study, we hypothesize that the ability of the protozoan Toxoplasma gondii to modulate immune response within the tumor might improve the therapeutic effect of immune checkpoint blockade. We examined the synergetic therapeutic activity of attenuated T. gondii RH ΔGRA17 strain and programmed death ligand-1 (PD-L1) treatment on both targeted and distal tumors in mice.

Methods

The effects of administration of T. gondii RH ΔGRA17 strain on the tumor volume and survival rate of mice bearing flank B16-F10, MC38, or LLC tumors were studied. We characterized the effects of ΔGRA17 on tumor biomarkers’ expression, PD-L1 expression, immune cells infiltrating the tumors, and expression of immune-related genes by using immunohistochemistry, immunofluorescence, flow cytometry, NanoString platform, and real-time quantitative PCR, respectively. The role of immune cells in the efficacy of ΔGRA17 plus PD-L1 blockade therapy was determined via depletion of immune cell subtypes.

Results

Treatment with T. gondii ΔGRA17 tachyzoites and anti-PD-L1 therapy significantly extended the survival of mice and suppressed tumor growth in preclinical mouse models of melanoma, Lewis lung carcinoma, and colon adenocarcinoma. Attenuation of the tumor growth was detected in the injected and distant tumors, which was associated with upregulation of innate and adaptive immune pathways. Complete regression of tumors was underpinned by late interferon-gamma-producing CD8⁺ cytotoxic T cells.

Conclusion

The results from these models indicate that intratumoral injection of ΔGRA17 induced a systemic effect, improved mouse immune response, and sensitized immunologically ‘cold’ tumors and rendered them sensitive to immune checkpoint blockade therapy.

Identification of an Immune-Related LncRNA Signature in Gastric Cancer to Predict Survival and Response to Immune Checkpoint Inhibitors

Immune microenvironment in gastric cancer is closely associated with patient’s prognosis. Long non-coding RNAs (lncRNAs) are emerging as key regulators of immune responses. In this study, we aimed to construct a prognostic model based on immune-related lncRNAs (IRLs) to predict the overall survival and response to immune checkpoint inhibitors (ICIs) of gastric cancer (GC) patients. The IRL signature was constructed through a bioinformatics method, and its predictive capability was validated. A stratification analysis indicates that the IRL signature can distinguish different risk patients. A nomogram based on the IRL and other clinical variables efficiently predicted the overall survival of GC patients. The landscape of tumor microenvironment and mutation status partially explain this signature’s predictive capability. We found the level of cancer-associated fibroblasts, endothelial cells, M2 macrophages, and stroma cells was high in the high-risk group, while the number of CD8⁺ T cells and T follicular helper cells was high in the low-risk group. Immunophenoscore (IPS) is validated for ICI response, and the IRL signature low-risk group received higher IPS, representing a more immunogenic phenotype that was more inclined to respond to ICIs. In addition, we found RNF144A-AS1 was highly expressed in GC patients and promoted the proliferation, migration, and invasive capacity of GC cells. We concluded that the IRL signature represents a novel useful model for evaluating GC survival outcomes and could be implemented to optimize the selection of patients to receive ICI treatment.

Distinct mutational profile and immune microenvironment in microsatellite-unstable and POLE-mutated tumors

INTRODUCTION

Mismatch repair (MMR)-deficient and DNA polymerase epsilon (POLE)-mutated tumors exhibit a high tumor mutation burden (TMB) and have been proven to be associated with good responses to immune checkpoint inhibitor treatments. However, the relationship between mutational characteristics of MMR-deficient and POLE-mutated tumors and the spatial architecture of tumor-infiltrating lymphocytes (TILs) has not been fully evaluated.

METHODS

We retrieved microsatellite instability-high (MSI-high, N=20) and POLE-mutated (N=47) cases from the clinical next-generation sequencing cohort at Asan Medical Center. Whole-slide immunostaining for CD3, CD4, CD8, FoxP3 and PD-1 were performed with tissue samples of colorectal and gastric cancer (N=24) and the tumor-positive TIL cell densities were correlated with the tumor's mutational features. The findings were compared with the results of similar analyses in The Cancer Genome Atlas-Colorectal Adenocarcinoma (TCGA-COADREAD) cohort (N=592).

RESULTS

The MSI-high group showed significantly higher overall TMBs with a number of insertion/deletion (indel) mutations relative to the POLE-mutated group (median TMB; 83.6 vs 12.5/Mb). Oncogenic/likely-oncogenic POLE mutations were identified with ultrahypermutations (≥100 mutations/Mb) (2/47, 4.3%). Concurrent POLE mutations of unknown significance and MSI-high cases were identified in eight cases (8/67, 11%), and two of these colorectal cancers had multiple POLE mutations, showing an ultramutated phenotype (378.1 and 484.4/Mb) and low indel mutation burdens with complete loss of MSH-6 or PMS-2, which was similar to the mutational profile of the POLE-inactivated tumors. Intratumoral CD3-positive, CD4-positive, CD8-positive, FoxP3-positive and PD-1-positive TIL cell densities were more strongly correlated with the indel mutation burden than with the total TMB (correlation coefficient, 0.61-0.73 vs 0.23-0.38). In addition, PI3K/AKT/mTOR pathway mutations were commonly found in MSI-high tumors (75%) but not in POLE-mutated tumors.

CONCLUSIONS

Indel mutation burden rather than total TMB could serve as a predictor of high TILs in both MSI-high and POLE-mutated tumors. Multiple uncharacterized/non-pathogenic POLE mutations occurring via MMR deficiency within MSI-high tumors may have combined pathogenic roles. A mutated PI3K/AKT/mTOR pathway may be a biomarker that can be used to stratify patients with advanced MSI-high tumors for immune therapy.

Network for Biomarker Immunoprofiling for Cancer Immunotherapy: Cancer Immune Monitoring and Analysis Centers and Cancer Immunologic Data Commons (CIMAC-CIDC)

PURPOSE

Immunoprofiling to identify biomarkers and integration with clinical trial outcomes are critical to improving immunotherapy approaches for patients with cancer. However, the translational potential of individual studies is often limited by small sample size of trials and the complexity of immuno-oncology biomarkers. Variability in assay performance further limits comparison and interpretation of data across studies and laboratories.

EXPERIMENTAL DESIGN

To enable a systematic approach to biomarker identification and correlation with clinical outcome across trials, the Cancer Immune Monitoring and Analysis Centers and Cancer Immunologic Data Commons (CIMAC-CIDC) Network was established through support of the Cancer MoonshotSM Initiative of the National Cancer Institute (NCI) and the Partnership for Accelerating Cancer Therapies (PACT) with industry partners via the Foundation for the NIH.

RESULTS

The CIMAC-CIDC Network is composed of four academic centers with multidisciplinary expertise in cancer immunotherapy that perform validated and harmonized assays for immunoprofiling and conduct correlative analyses. A data coordinating center (CIDC) provides the computational expertise and informatics platforms for the storage, integration, and analysis of biomarker and clinical data.

CONCLUSIONS

This overview highlights strategies for assay harmonization to enable cross-trial and cross-site data analysis and describes key elements for establishing a network to enhance immuno-oncology biomarker development. These include an operational infrastructure, validation and harmonization of core immunoprofiling assays, platforms for data ingestion and integration, and access to specimens from clinical trials. Published in the same volume are reports of harmonization for core analyses: whole-exome sequencing, RNA sequencing, cytometry by time of flight, and IHC/immunofluorescence.

Development of preclinical and clinical models for immune-related adverse events following checkpoint immunotherapy: a perspective from SITC and AACR

Recent advances in cancer immunotherapy have completely revolutionized cancer treatment strategies. Nonetheless, the increasing incidence of immune-related adverse events (irAEs) is now limiting the overall benefits of these treatments. irAEs are well-recognized side effects of some of the most effective cancer immunotherapy agents, including antibody blockade of the cytotoxic T-lymphocyte-associated protein 4 and programmed death protein 1/programmed-death ligand 1 pathways. To develop an action plan on the key elements needed to unravel and understand the key mechanisms driving irAEs, the Society for Immunotherapy for Cancer and the American Association for Cancer Research partnered to bring together research and clinical experts in cancer immunotherapy, autoimmunity, immune regulation, genetics and informatics who are investigating irAEs using animal models, clinical data and patient specimens to discuss current strategies and identify the critical next steps needed to create breakthroughs in our understanding of these toxicities. The genetic and environmental risk factors, immune cell subsets and other key immunological mediators and the unique clinical presentations of irAEs across the different organ systems were the foundation for identifying key opportunities and future directions described in this report. These include the pressing need for significantly improved preclinical model systems, broader collection of biospecimens with standardized collection and clinical annotation made available for research and integration of electronic health record and multiomic data with harmonized and standardized methods, definitions and terminologies to further our understanding of irAE pathogenesis. Based on these needs, this report makes a set of recommendations to advance our understanding of irAE mechanisms, which will be crucial to prevent their occurrence and improve their treatment.

Liquid Biopsy in Hepatocellular Carcinoma: Opportunities and Challenges for Immunotherapy

Hepatocellular carcinoma (HCC) is one of the deadliest cancer types worldwide. HCC is often diagnosed at a late stage when the therapeutic options are very limited. However, even at the earlier stages, the best treatment is liver transplantation, surgical resection or ablation. Surgical resection and ablation may carry a high risk of tumor recurrence. The recent introduction of immunotherapies resulted in clinical responses for a subgroup of patients, but there were still no effective predictive markers for response to immunotherapy or for recurrence after surgical therapy. The identification of biomarkers that could correlate and predict response or recurrence would require close monitoring of the patients throughout and after the completion of treatment. However, this would not be performed efficiently by repeated and invasive tissue biopsies. A better approach would be to use liquid biopsies including circulating tumor DNA (ctDNA), circulating RNA (e.g., microRNAs), circulating tumor cells (CTC) and extracellular vesicles (EVs) (e.g., exosomes) for disease monitoring in a non-invasive manner. In this review, we discuss the currently available technology that can enable the use of liquid biopsy as a diagnostic and prognostic tool. Moreover, we discuss the opportunities and challenges of the clinical application of liquid biopsy for immunotherapy of HCC.

Identification of Notch signaling pathway gene mutations as a prognostic biomarker for bladder cancer

Purpose: The authors aimed to identify Notch signaling pathway gene mutations as a prognostic biomarker for bladder cancer. Methods: First, critical Notch signaling pathway genes were screened using The Cancer Genome Atlas and validation sets. Second, immune infiltration, protein-protein interaction network, Kyoto Encyclopedia of Genes and Genomes and Gene Set Enrichment Analysis analyses were performed. Finally, potential immunotherapy drug targets were screened using T-cell receptors, B-cell receptors and CERES scores for bladder cancer. Results: The NOTCH7 gene was identified, with a significant difference in immune infiltration level between mutant and wild type in bladder cancer, mainly related to T cells. NOTCH7 was an immunotherapy prognostic factor, and IRF1 and B2M were the potential drug targets for NOTCH7 mutation in bladder cancer. Conclusion: NOTCH7 gene mutation can be used as an immunotherapy biomarker for bladder cancer.

Tutorial: best practices and considerations for mass-spectrometry-based protein biomarker discovery and validation

Mass-spectrometry-based proteomic analysis is a powerful approach for discovering new disease biomarkers. However, certain critical steps of study design such as cohort selection, evaluation of statistical power, sample blinding and randomization, and sample/data quality control are often neglected or underappreciated during experimental design and execution. This tutorial discusses important steps for designing and implementing a liquid-chromatography-mass-spectrometry-based biomarker discovery study. We describe the rationale, considerations and possible failures in each step of such studies, including experimental design, sample collection and processing, and data collection. We also provide guidance for major steps of data processing and final statistical analysis for meaningful biological interpretations along with highlights of several successful biomarker studies. The provided guidelines from study design to implementation to data interpretation serve as a reference for improving rigor and reproducibility of biomarker development studies.

N2E4, a Monoclonal Antibody Targeting Neuropilin-2, Inhibits Tumor Growth and Metastasis in Pancreatic Ductal Adenocarcinoma via Suppressing FAK/Erk/HIF-1α Signaling

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy with extremely limited treatment; the effective targeting strategy stays an urgent unmet need. Neuropilin-2 (NRP2), a multifunctional transmembrane non-tyrosine-kinase glycoprotein, enhances various signal transduction pathways to modulate cancer progression. However, the application value of NRP2 as a therapeutic target in pancreatic cancer is still unclear. Here, we detected the elevated NRP2 was associated with the poor prognosis of pancreas carcinoma. The mouse monoclonal antibody targeting NRP2 (N2E4) that could specifically bind to PDAC cells was developed. Moreover, N2E4 inhibits PDAC proliferation, migration, and invasion in vitro, and repressed growth and metastasis in vivo. Mechanistically, the effect of N2E4 was mainly related to the blocking of interaction between NRP2 with integrinβ1 to inhibit FAK/Erk/HIF-1a/VEGF signaling. Therefore, N2E4 has the potential for targeting therapy of PDAC. This study lays a foundation for the future development of NRP2-based targeted therapy for PDAC.

Treatment with lentiviral vectors encoding shRNA against interleukin 10 modulates the immunosuppressive activity of murine colon carcinoma-associated myeloid-derived suppressor cells

Myeloid-derived suppressor cells (MDSCs) are potent suppressors of antitumor immunity and their accumulation is often associated with poor prognosis. The aim of the present study was to determine the mechanisms of action of lentiviral vectors encoding short hairpin (sh)RNA against interleukin-10 (IL-10), with particular emphasis on their influence on the activity of tumor-derived MDSCs. Lentiviral vectors encoding shRNA against IL-10 (shIL-10 LVs) were utilized to silence the expression of IL-10 either in MDSCs that were generated ex vivo from bone marrow cells cultured in the presence of supernatant from MC38 colon carcinoma cells, or in situ in the MC38 murine colon carcinoma environment. Although monocytic MDSCs (M-MDSCs) transduced with shIL-10 LVs exhibited increased suppressor activity, transduction of polymorphonuclear MDSCs (PMN-MDSCs) appeared to reduce their ability to inhibit T lymphocyte functions. Analysis of EGFP expression in MC38 tumors revealed that intratumorally inoculated shIL-10 LVs transduced tumor-infiltrating myeloid cells with the highest efficiency and, led to a decreased IL-10 level in the tumor microenvironment. However, the effect was accompanied by increased influx of PMN-MDSCs into tumors observed both on the 6th and on the 10th day after shIL-10 LV injections. Nevertheless, it was noted that suppressor activity of myeloid cells isolated from tumors was dependent on the efficiency of tumor-derived PMN-MDSC transduction with shIL-10 LVs. The increased percentage of transduced PMN-MDSCs on the 10th day was associated with diminished immunosuppressive activity of tumor-derived myeloid cells and an elevated ratio of cytotoxic T lymphocytes to M-MDSCs. The obtained data indicated that treatment with shIL-10 LVs may result in modulation of the immunosuppressive activity of MC38 colon carcinoma-derived MDSCs.

Assessment of Immune Status in Dynamics for Patients with Cancer Undergoing Immunotherapy

Immunotherapy using immune checkpoint inhibitors has revolutionized the treatment, and many types of cancer show a response rate of 20–40% and a significant increase in five-year survival. However, immunotherapy is expensive and may cause serious adverse events. Therefore, a predictive method allowing identification of responding patients before starting the treatment would be very useful. In this study, we aimed to identify and implement other individual prognosis factors, factors that could lead to an improved clinical decision made in regard to the patient to establish an individualized treatment. Materials and Methods. All patients recruited from October 2018 to July 2019 were treated in OncoFort Hospital, Bucharest, with nivolumab or pembrolizumab. We investigated T lymphocyte CD3+, CD4+, CD8+, and CD4/CD8 cells by flow cytometry in patients before and after receiving treatment with anti-PD-1 agents. Results. We found that the responder group showed higher expression on CD4+ cells than the nonresponder group after the first cycle of immunotherapy. The prediction of the immunotherapeutic effect revealed that the elevation of T lymphocytes CD8+ and CD4+ after the first cycle of immunotherapy was followed by a decrease in their expression after the second cycle and was followed by a return almost to that one after the first administration. Conclusion. Our work indicates that the evaluation of the cells of the immune system in relation to the tumor and immunotherapy may lead to a better understanding of the pathogenic mechanisms and the identification of prognostic and predictive factors that will more effectively model the therapeutic approach.

Inmunoterapia personalizada contra el cáncer basada en neoantígenos. Revisión de la literatura

Introducción. Los avances que se han hecho en inmunoterapia contra el cáncer y la respuesta clínica de los pacientes que han recibido este tipo de terapia la han convertido en el cuarto pilar para el tratamiento del cáncer. Objetivo. Describir brevemente el fundamento biológico de la inmunoterapia personalizada contra el cáncer basada en neoantígenos, las perspectivas actuales de su desarrollo y algunos resultados clínicos de esta terapia. Materiales y métodos. Se realizó una búsqueda de la literatura en PubMed, Scopus y EBSCO utilizando la siguiente estrategia de búsqueda: tipo de artículos: estudios experimentales originales, ensayos clínicos y revisiones narrativas y sistemáticas sobre métodos de identificación de mutaciones generadas en los tumores y estrategias de inmunoterapia del cáncer con vacunas basadas en neoantígenos; población de estudio: humanos y modelos animales; periodo de publicación: enero 1989- diciembre 2019; idioma: inglés y español; términos de búsqueda: “Immunotherapy”, “Neoplasms”, “Mutation” y “Cancer Vaccines”. Resultados. La búsqueda inicial arrojó 1344 registros; luego de remover duplicados (n=176), 780 fueron excluidos luego de leer su resumen y título, y se evaluó el texto completo de 338 para verificar cuáles cumplían con los criterios de inclusión, seleccionándose finalmente 73 estudios para análisis completo. Todos los artículos recuperados se publicaron en inglés, y fueron realizados principalmente en EE. UU. (43.83%) y Alemania (23.65%). En el caso de los estudios originales (n=43), 20 se realizaron únicamente en humanos, 9 solo en animales, 2 en ambos modelos, y 12 usaron metodología in silico. Conclusión. La inmunoterapia personalizada contra el cáncer con vacunas basadas en neoantígenos tumorales se está convirtiendo de forma contundente en una nueva alternativa para tratar el cáncer. Sin embargo, para lograr su implementación adecuada, es necesario usarla en combinación con tratamientos convencionales, generar más conocimiento que contribuya a aclarar la inmunobiología del cáncer, y reducir los costos asociados con su producción.