Tumor neoantigens: from basic research to clinical applications

Antibody-Drug Conjugates in Uro-Oncology

Currently available treatment options for patients with refractory metastatic prostate, bladder, or kidney cancers are limited with the prognosis remaining poor. Advances in the pathobiology of tumors has led to the discovery of cancer antigens that may be used as the target for cancer treatment. Antibody-drug conjugates (ADCs) are a relatively new concept in cancer treatment that broaden therapeutic landscape. ADCs are examples of a 'drug delivery into the tumor' system composed of an antigen-directed antibody linked to a cytotoxic drug that may release cytotoxic components after binding to the antigen located on the surface of tumor cells. The clinical properties of drugs are influenced by every component of ADCs. Regarding uro-oncology, enfortumab vedotin (EV) and sacituzumab govitecan (SG) are currently registered for patients with locally advanced or metastatic urothelial cancer following previous treatment with an immune checkpoint inhibitor (iCPI; programmed death receptor-1 [PD-1] or programmed death-ligand 1 [PD-L1]) inhibitor) and platinum-containing chemotherapy. The EV-301 trial showed that EV significantly prolonged the overall survival compared with classic chemotherapy. The TROPHY-U-01 trial conducted to evaluate SG demonstrated promising results as regards the objective response rate and duration of response. The safety and efficacy of ADCs in monotherapy and polytherapy (mainly with iCPIs) for different cancer stages and tumor types are assessed in numerous ongoing clinical trials. The aim of this review is to present new molecular biomarkers, specific mechanisms of action, and ongoing clinical trials of ADCs in genitourinary cancers. In the expert discussion, we assess the place of ADCs in uro-oncology and discuss their clinical value.

Activation of the chemokine receptor 3 pathway leads to a better response to immune checkpoint inhibitors in patients with metastatic urothelial carcinoma

Immune checkpoint inhibitors (ICIs) have made important breakthrough in anti-tumor therapy, however, no single biomarker can accurately predict their efficacy. Studies have found that tumor microenvironment is a key factor for determining the response to ICI therapy. Cytokine receptor 3 (C-X-C Motif Chemokine Receptor 3, CXCR3) pathway has been reported to play an important role in the migration, activation, and response of immune cells. We analyzed survival data, genomics, and clinical data from patients with metastatic urothelial carcinoma (mUC) who received ICI treatment to explore the relationship between CXCR3 pathway activation and the effectiveness of ICIs. The Cancer Genome Atlas Bladder Urothelial Carcinoma cohort and six other cohorts receiving ICI treatment were used for mechanism exploration and validation. In the ICI cohort, we performed univariate and multivariate COX analyses and discovered that patients in the CXCR3-high group were more sensitive to ICI treatment. A Kaplan–Meier analysis demonstrated that patients in the high CXCR3-high group had a better prognosis than those in the CXCR3-low group (P = 0.0001, Hazard Ratio = 0.56; 95% CI 0.42−0.75). CIBERSORT analysis found that mUC patients in the CXCR3-high group had higher levels of activated CD8+ T cells, M1 macrophages, and activated NK cells and less regulatory T cell (Treg) infiltration. Immunogenicity analysis showed the CXCR3-high group had higher tumor neoantigen burden (TNB). Our study suggests that CXCR3 pathway activation may be a novel predictive biomarker for the effectiveness of immunotherapy in mUC patients.

Role of CD68 in tumor immunity and prognosis prediction in pan-cancer

CD68 plays a critical role in promoting phagocytosis; however, the function of CD68 in tumor immunity and prognosis remains unknown. We analyzed CD68 expression among 33 tumor and normal tissues from The Cancer Genome Atlas and Genotype-Tissue Expression datasets. The relationship between CD68 expression and cancer prognosis, immune infiltration, checkpoint markers, and drug response was explored. Upregulated CD68 levels were observed in various cancer types, which were verified through tumor tissue chips using immunohistochemistry. High levels of CD68 in tumor samples correlated with an adverse prognosis in glioblastoma, kidney renal clear cell carcinoma, lower-grade glioma, liver hepatocellular carcinoma, lung squamous cell carcinoma, thyroid carcinoma, and thymoma and a favorable prognosis in kidney chromophobe. The top three negatively enriched Kyoto Encyclopedia of Genes and Genomes terms in the high CD68 subgroup were chemokine signaling pathway, cytokine-cytokine receptor interaction, and cell adhesion molecule cams. The top negatively enriched HALLMARK terms included complement, allograft rejection, and inflammatory response. A series of targeted drugs and small-molecule drugs with promising therapeutic effects were predicted. The clinical prognosis and immune infiltration of high expression levels of CD68 differ across tumor types. Inhibiting CD68-dependent signaling could be a promising therapeutic strategy for immunotherapy in many tumor types.

CAD v1.0: Cancer Antigens Database Platform for Cancer Antigen Algorithm Development and Information Exploration

Cancer vaccines have gradually attracted attention for their tremendous preclinical and clinical performance. With the development of next-generation sequencing technologies and related algorithms, pipelines based on sequencing and machine learning methods have become mainstream in cancer antigen prediction; of particular focus are neoantigens, mutation peptides that only exist in tumor cells that lack central tolerance and have fewer side effects. The rapid prediction and filtering of neoantigen peptides are crucial to the development of neoantigen-based cancer vaccines. However, due to the lack of verified neoantigen datasets and insufficient research on the properties of neoantigens, neoantigen prediction algorithms still need to be improved. Here, we recruited verified cancer antigen peptides and collected as much relevant peptide information as possible. Then, we discussed the role of each dataset for algorithm improvement in cancer antigen research, especially neoantigen prediction. A platform, Cancer Antigens Database (CAD, http://cad.bio-it.cn/), was designed to facilitate users to perform a complete exploration of cancer antigens online.

dbPepNeo2.0: A Database for Human Tumor Neoantigen Peptides From Mass Spectrometry and TCR Recognition

Neoantigens are widely reported to induce T-cell response and lead to tumor regression, indicating a promising potential to immunotherapy. Previously, we constructed an open-access database, i.e., dbPepNeo, providing a systematic resource for human tumor neoantigens to storage and query. In order to expand data volume and application scope, we updated dbPepNeo to version 2.0 (http://www.biostatistics.online/dbPepNeo2). Here, we provide about 801 high-confidence (HC) neoantigens (increased by 170%) and 842,289 low-confidence (LC) HLA immunopeptidomes (increased by 107%). Notably, 55 class II HC neoantigens and 630 neoantigen-reactive T-cell receptor-β (TCRβ) sequences were firstly included. Besides, two new analytical tools are developed, DeepCNN-Ineo and BLASTdb. DeepCNN-Ineo predicts the immunogenicity of class I neoantigens, and BLASTdb performs local alignments to look for sequence similarities in dbPepNeo2.0. Meanwhile, the web features and interface have been greatly improved and enhanced.

PD-L1 siRNA-hyaluronic acid conjugate for dual-targeted cancer immunotherapy

"Foreignization" of tumor cells via delivery of a non-self foreign antigen (Ag) into tumors is an appealing strategy to initiate anti-tumor immunity that can facilitate tumor rejection by pre-existing foreign-Ag-reactive T cells. However, the immune-suppressive factors in the tumor microenvironment (TME) limit the durable and potent immune response of these cells against tumor antigens, stressing the need for improved tumor-foreignization strategies. Here, we demonstrate that blockade of programmed cell death ligand 1 (PD-L1) on both tumor cells and dendritic cells (DCs) can markedly potentiate the induction of tumor-reactive T cells, thereby strengthening the anti-tumor immunity ignited by tumor-foreignization. Specifically, we developed a polymeric nanoconjugate (PEG-HA-OVA/PPLs), consisting of siPD-L1-based polyplexes, PEGylated hyaluronic acid as the CD44-targeting moiety, and ovalbumin (OVA) as a model foreign antigen. Notably, PEG-HA-OVA/PPLs were simultaneously delivered into CD44^high tumor cells and CD44^high DCs, leading to efficient cross-presentation of OVA and downregulation of PD-L1 in both cell types. Importantly, the nanoconjugate not only allowed OVA-specific T cells to vigorously reject the foreignized tumor cells but also reprogrammed the TME to elicit robust T-cell responses specific to the endogenous tumor Ags, eventually generating long-lasting protective immunity. Thus, our combination strategy represents an innovative approach for the induction of potent tumor immunity via a two-step consecutive immune boost against exogenous and endogenous tumor Ags.

The Role of Long Non-Coding RNAs in the Tumor Immune Microenvironment

Tumorigenesis is a complicated process caused by successive genetic and epigenetic alterations. The past decades demonstrated that the immune system affects tumorigenesis, tumor progression, and metastasis. Although increasing immunotherapies are revealed, only a tiny proportion of them are effective. Long non-coding RNAs (lncRNAs) are a class of single-stranded RNA molecules larger than 200 nucleotides and are essential in the molecular network of oncology and immunology. Increasing researches have focused on the connection between lncRNAs and cancer immunotherapy. However, the in-depth mechanisms are still elusive. In this review, we outline the latest studies on the functions of lncRNAs in the tumor immune microenvironment. Via participating in various biological processes such as neutrophil recruitment, macrophage polarization, NK cells cytotoxicity, and T cells functions, lncRNAs regulate tumorigenesis, tumor invasion, epithelial-mesenchymal transition (EMT), and angiogenesis. In addition, we reviewed the current understanding of the relevant strategies for targeting lncRNAs. LncRNAs-based therapeutics may represent promising approaches in serving as prognostic biomarkers or potential therapeutic targets in cancer, providing ideas for future research and clinical application on cancer diagnosis and therapies.

Reframing How Physical Activity Reduces The Incidence of Clinically-Diagnosed Cancers: Appraising Exercise-Induced Immuno-Modulation As An Integral Mechanism

Undertaking a high volume of physical activity is associated with reduced risk of a broad range of clinically diagnosed cancers. These findings, which imply that physical activity induces physiological changes that avert or suppress neoplastic activity, are supported by preclinical intervention studies in rodents demonstrating that structured regular exercise commonly represses tumour growth. In Part 1 of this review, we summarise epidemiology and preclinical evidence linking physical activity or regular structured exercise with reduced cancer risk or tumour growth. Despite abundant evidence that physical activity commonly exerts anti-cancer effects, the mechanism(s)-of-action responsible for these beneficial outcomes is undefined and remains subject to ongoing speculation. In Part 2, we outline why altered immune regulation from physical activity - specifically to T cells - is likely an integral mechanism. We do this by first explaining how physical activity appears to modulate the cancer immunoediting process. In doing so, we highlight that augmented elimination of immunogenic cancer cells predominantly leads to the containment of cancers in a 'precancerous' or 'covert' equilibrium state, thus reducing the incidence of clinically diagnosed cancers among physically active individuals. In seeking to understand how physical activity might augment T cell function to avert cancer outgrowth, in Part 3 we appraise how physical activity affects the determinants of a successful T cell response against immunogenic cancer cells. Using the cancer immunogram as a basis for this evaluation, we assess the effects of physical activity on: (i) general T cell status in blood, (ii) T cell infiltration to tissues, (iii) presence of immune checkpoints associated with T cell exhaustion and anergy, (iv) presence of inflammatory inhibitors of T cells and (v) presence of metabolic inhibitors of T cells. The extent to which physical activity alters these determinants to reduce the risk of clinically diagnosed cancers - and whether physical activity changes these determinants in an interconnected or unrelated manner - is unresolved. Accordingly, we analyse how physical activity might alter each determinant, and we show how these changes may interconnect to explain how physical activity alters T cell regulation to prevent cancer outgrowth.

Comprehensive Analysis of Microsatellite-Related Transcriptomic Signature and Identify Its Clinical Value in Colon Cancer

Background

Microsatellite has been proved to be an important prognostic factor and a treatment reference in colon cancer. The transcriptome profile and tumor microenvironment of different microsatellite statuses are different. Metastatic colon cancer patients with microsatellite instability-high (MSI-H) are sensitive to immune checkpoint inhibitors (ICIs), but not fluorouracil. Efforts have been devoted to identify the predictive factors of immunotherapy.

Methods

We analyzed the transcriptome profile of different microsatellite statuses in colon cancer by using single-cell and bulk transcriptome data from publicly available databases. The immune cells in the tumor microenvironment were analyzed by the ESTIMATION algorithm. The microsatellite-related gene signature (MSRS) was constructed by the least absolute shrinkage and selection operator (LASSO) Cox regression based on the differentially expressed genes (DEGs) and its prognostic value and predictive value of response to immunotherapy were assessed. The prognostic value of the MSRS was also validated in another cohort.

Results

The MSI-H cancers cells were clustered differentially in the dimension reduction plot. Most of the immune cells have a higher proportion in the tumor immune microenvironment, except for CD56 bright natural killer cells. A total of 238 DEGs were identified. Based on the 238 DEGs, a neural network was constructed with a Kappa coefficient of 0.706 in the testing cohort. The MSRS is a favorable prognostic factor of overall survival, which was also validated in another cohort (GSE39582). Besides, MSRS is correlated with tumor mutation burden in MSI-H colon cancer. However, the MSRS is a barely satisfactory factor in predicting immunotherapy with the area under the curve (AUC) of 0.624.

Conclusion

We developed the MSRS, which is a robust prognostic factor of overall survival in spite of a barely satisfactory immunotherapy predictor. Further studies may need to improve the predictive ability.

Efficient Radiomics-Based Classification of Multi-Parametric MR Images to Identify Volumetric Habitats and Signatures in Glioblastoma: A Machine Learning Approach

Simple Summary

Glioblastomas carry a poor prognosis and usually presents with heterogeneous regions in the brain tumor. Multi-parametric MR images can show morphological characteristics. Radiomics features refer to the extraction of a large number of quantitative measurements that describe the geometry, intensity, and texture which were extracted from contrast-enhanced T1-weighted images from anatomical MRI and metabolic features from PET. It also provides a qualitative image interpretation as well as cellular, molecular, and tumor properties. Thus, it derives additional information about the entire tumor volume which is generally of irregular shape and size from routinely evaluated “non-invasive” imaging biomarkers techniques. We demonstrated volumetric habitats and signatures in necrosis, solid tumor, peritumoral tissue, and edema with key biological processes and phenotype features. This provides physicians with key information on how the disease is progressing in the brain and can also give an indication of how well treatment is working.

Abstract

Glioblastoma (GBM) is a fast-growing and aggressive brain tumor of the central nervous system. It encroaches on brain tissue with heterogeneous regions of a necrotic core, solid part, peritumoral tissue, and edema. This study provided qualitative image interpretation in GBM subregions and radiomics features in quantitative usage of image analysis, as well as ratios of these tumor components. The aim of this study was to assess the potential of multi-parametric MR fingerprinting with volumetric tumor phenotype and radiomic features to underlie biological process and prognostic status of patients with cerebral gliomas. Based on efficiently classified and retrieved cerebral multi-parametric MRI, all data were analyzed to derive volume-based data of the entire tumor from local cohorts and The Cancer Imaging Archive (TCIA) cohorts with GBM. Edema was mainly enriched for homeostasis whereas necrosis was associated with texture features. The proportional volume size of the edema was about 1.5 times larger than the size of the solid part tumor. The volume size of the solid part was approximately 0.7 times in the necrosis area. Therefore, the multi-parametric MRI-based radiomics model reveals efficiently classified tumor subregions of GBM and suggests that prognostic radiomic features from routine MRI examination may also be significantly associated with key biological processes as a practical imaging biomarker.

Targeting the tumor mutanome for personalized vaccination in a TMB low non-small cell lung cancer

BACKGROUND

Cancer is characterized by an accumulation of somatic mutations, of which a significant subset can generate cancer-specific neoepitopes that are recognized by autologous T cells. Such neoepitopes are emerging as important targets for cancer immunotherapy, including personalized cancer vaccination strategies.

METHODS

We used whole-exome and RNA sequencing analysis to identify potential neoantigens for a patient with non-small cell lung cancer. Thereafter, we assessed the autologous T-cell reactivity to the candidate neoantigens using a long peptide approach in a cultured interferon gamma ELISpot and tracked the neoantigen-specific T-cells in the tumor by T-cell receptor (TCR) sequencing. In parallel, identified gene variants were incorporated into a Modified Vaccinia Ankara-based vaccine, which was evaluated in the human leucocyte antigen A*0201 transgenic mouse model (HHD).

RESULTS

Sequencing revealed a tumor with a low mutational burden: 2219 sequence variants were identified from the primary tumor, of which 23 were expressed in the transcriptome, involving 18 gene products. We could demonstrate spontaneous T-cell responses to 5/18 (28%) mutated gene variants, and further analysis of the TCR repertoire of neoantigen-specific CD4+ and CD8+ T cells revealed TCR clonotypes that were expanded in both blood and tumor tissue. Following vaccination of HHD mice, de novo T-cell responses were generated to 4/18 (22%) mutated gene variants; T cells reactive against two variants were also evident in the autologous setting. Subsequently, we determined the major histocompatibility complex restriction of the T-cell responses and used in silico prediction tools to determine the likely neoepitopes.

CONCLUSIONS

Our study demonstrates the feasibility of efficiently identifying tumor-specific neoantigens that can be targeted by vaccination in tumors with a low mutational burden, promising successful clinical exploitation, with trials currently underway.

A candidate triple-negative breast cancer vaccine design by targeting clinically relevant cell surface markers: an integrated immuno and bio-informatics approach

Triple-negative breast cancer (TNBC) is an aggressive, metastatic/invasive sub-class of breast cancer (BCa). Cell surface protein-derived multi-epitope vaccine-mediated targeting of TNBC cells could be a better strategy against the disease. Literature-based identified potential cell surface markers for TNBC cells were subjected to expression pattern and survival analysis in BCa patient sample using TCGA database. The cytotoxic and helper T-lymphocytes antigenic epitopes in the test proteins were identified, selected and fused together with the appropriate linkers and an adjuvant, to construct the multi-epitope vaccine (MEV). The immune profile, physiochemical property (PP) and world population coverage of the MEV was studied. Immune simulation, cloning in a suitable vector, molecular docking (against Toll-like receptors, MHC (I/II) molecules), and molecular dynamics simulations of the MEV was performed. Cell surface markers were differentially expressed in TNBC samples and showed poor survival in TNBC patients. Satisfactory PP and WPC (up to 89 and 99%) was observed. MEV significant stable binding with the immune molecules and induced the immune cells in silico. The designed vaccine has capability to elicit immune response which could be utilized to target TNBC alone/combination with other therapy. The experimental studies are required to check the efficacy of the vaccine.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s13205-022-03140-3.

Identification of Neoantigens in Cancer Cells as Targets for Immunotherapy

The clinical benefits of immune checkpoint blockage (ICB) therapy have been widely reported. In patients with cancer, researchers have demonstrated the clinical potential of antitumor cytotoxic T cells that can be reinvigorated or enhanced by ICB. Compared to self-antigens, neoantigens derived from tumor somatic mutations are believed to be ideal immune targets in tumors. Candidate tumor neoantigens can be identified through immunogenomic or immunopeptidomic approaches. Identification of neoantigens has revealed several points of the clinical relevance. For instance, tumor mutation burden (TMB) may be an indicator of immunotherapy. In various cancers, mutation rates accompanying neoantigen loads may be indicative of immunotherapy. Furthermore, mismatch repair-deficient tumors can be eradicated by T cells in ICB treatment. Hence, immunotherapies using vaccines or adoptive T-cell transfer targeting neoantigens are potential innovative strategies. However, significant efforts are required to identify the optimal epitopes. In this review, we summarize the recent progress in the identification of neoantigens and discussed preclinical and clinical studies based on neoantigens. We also discuss the issues remaining to be addressed before clinical applications of these new therapeutic strategies can be materialized.

Shedding light on the hidden human proteome expands immunopeptidome in cancer

Unrestrained cellular growth and immune escape of a tumor are associated with the incidental errors of the genome and transcriptome. Advances in next-generation sequencing have identified thousands of genomic and transcriptomic aberrations that generate variant peptides that assemble the hidden proteome, further expanding the immunopeptidome. Emerging next-generation sequencing technologies and a number of computational methods estimated the abundance of immune infiltration from bulk transcriptome have advanced our understanding of tumor microenvironments. Here, we will characterize several major types of tumor-specific antigens arising from single-nucleotide variants, insertions and deletions, gene fusion, alternative splicing, RNA editing and non-coding RNAs. Finally, we summarize the current state-of-the-art computational and experimental approaches or resources and provide an integrative pipeline for the identification of candidate tumor antigens. Together, the systematic investigation of the hidden proteome in cancer will help facilitate the development of effective and durable immunotherapy targets for cancer.

Ferroptosis Mediation Patterns Reveal Novel Tool to Implicate Immunotherapy and Multi-Omics Characteristics in Bladder Cancer

Background: The regulatory role of ferroptosis in malignant tumours has been recently demonstrated. However, the potential roles of ferroptosis mediation patterns in bladder cancer remain elusive. Materials and Methods: The ferroptosis mediation patterns of 889 bladder cancer samples were comprehensively evaluated based on ferroptosis-related genes. The underlying correlations between these mediation patterns and multi-omic characteristics of bladder cancer were systematically analysed. The ferroptosis mediation patterns of individual samples were quantified by ferropscore using the principal component analysis algorithm. The typical ferroptosis-related genes with prognostic roles were further randomly validated using immunohistochemical staining, real-time polymerase chain reaction and western blotting. Results: Three different ferroptosis mediation patterns were identified. The abundance of infiltration of 23 immune cells was different among the three mediation patterns. The quantification of ferroptosis mediation patterns in individual samples served as a promising tool for predicting patient survival outcomes; immune cell infiltration abundance; tumour mutation burden; oncogenic mutation status and tumour grade, stage and molecular subtypes. Low ferropscore combined with high tumour mutation burden was associated with the best survival prognosis. Expressions of PD-L1 (p < 0.001), PD-1 (p = 0.002) and CTLA-4 (p = 0.003) were all significantly upregulated in the high ferropscore group. Low ferropscores also predicted good immunotherapy response for anti-CTLA4 strategy. The mRNA and protein levels of FADS2, a typical ferroptosis-related gene used in the study, were higher in bladder cancer cell lines than in controlled SV-HUC-1 cells. In addition, immunohistochemical staining revealed significantly higher expression levels of FADS2 in human bladder cancer tumour tissues than in normal tissues. Conclusion: This study identified three distinct ferroptosis mediation patterns in bladder cancer. Quantification of ferroptosis mediation patterns in individual samples may help to improve the understanding of multiomic characteristics and guide future immunotherapy responses to bladder cancer.

Development of antigen-prediction algorithm for personalized neoantigen vaccine using human leukocyte antigen transgenic mouse

Immunotherapy is currently recognized as the fourth modality in cancer therapy. CTLs can detect cancer cells via complexes involving human leukocyte antigen (HLA) class I molecules and peptides derived from tumor antigens, resulting in antigen-specific cancer rejection. The peptides may be predicted in silico using machine learning-based algorithms. Neopeptides, derived from neoantigens encoded by somatic mutations in cancer cells, are putative immunotherapy targets, as they have high tumor specificity and immunogenicity. Here, we used our pipeline to select 278 neoepitopes with high predictive "SCORE" from the tumor tissues of 46 patients with hepatocellular carcinoma or metastasis of colorectal carcinoma. We validated peptide immunogenicity and specificity by in vivo vaccination with HLA-A2, A24, B35, and B07 transgenic mice using ELISpot assay, in vitro and in vivo killing assays. We statistically evaluated the power of our prediction algorithm and demonstrated the capacity of our pipeline to predict neopeptides (area under the curve = 0.687, p < 0.0001). We also analyzed the potential of long peptides containing the predicted neoepitopes to induce CTLs. Our study indicated that the short peptides predicted using our algorithm may be intrinsically present in tumor cells as cleavage products of long peptides. Thus, we empirically demonstrated that the accuracy and specificity of our prediction tools may be potentially improved in vivo using the HLA transgenic mouse model. Our data will help to feedback algorithms to improve in silico prediction, potentially allowing researchers to predict peptides for personalized immunotherapy.

Neoadjuvant immunotherapy facilitates resection of surgically-challenging lung squamous cell cancer

Background

Locally-advanced lung squamous cell carcinoma represents a special subset that is challenging to resect completely with surgery alone. Immunotherapy has achieved great success in treating late-stage lung cancer. However, whether neoadjuvant immunotherapy can facilitate resection of initially locally-advanced and surgically-difficult locally-advanced lung squamous cell carcinoma remains to be investigated.

Methods

We retrospectively collected clinical records of locally-advanced lung squamous cell carcinoma patients who received neoadjuvant immunotherapy followed by surgery between 2018 and 2020 at a large academic thoracic cancer center.

Results

A total of 23 patients (22 males, 1 female) with locally-advanced locally-advanced lung squamous cell carcinoma were included, initially clinically staged at IIIA (16, 69.6%), IIIB (n=4, 17.4%), IIB (n=2, 8.7%) and IIIC (n=1, 4.3%). The median interval between final treatment to surgery was 36 days (range, 25-93 days), without treatment-related delay in surgery. The neoadjuvant treatment resulted in a high rate of radical resection (n=20, 87.0%). The final histopathological examination demonstrated 6 (26.1%) cases with pathological complete response and 8 (34.8%) with pathological major response. Comparing with the computed tomography scan-based response, we observed a very low consistency (weighted kappa =0.122, P=0.315) between the computed tomography scan-based and final pathological evaluation. The median follow-up time was 510 days (range, 217-920 days). At the end of the follow-up, 1 patient died.

Conclusions

Our findings showed the clinical promise of neoadjuvant immunotherapy plus surgery for locally-advanced lung squamous cell carcinoma. Computed tomography scan displays a poor role in assessing the resectability after neoadjuvant immunotherapy.

Rare Occurrence of Aristolochic Acid Mutational Signatures in Oro-Gastrointestinal Tract Cancers

BACKGROUND

Aristolochic acids (AAs) are potent mutagens commonly found in herbal plant-based remedies widely used throughout Asian countries.

PATIENTS AND METHODS

To understand whether AA is involved in the tumorigenesis of the oro-gastrointestinal tract, we used whole-exome sequencing to profile 54 cases of four distinct types of oro-gastrointestinal tract cancer (OGITC) from Taiwan.

RESULTS

A diverse landscape of mutational signatures including those from DNA mismatch repair and reactive oxygen species was observed. APOBEC mutational signatures were observed in 60% of oral squamous cell carcinomas. Only one sample harbored AA mutational signatures, contradictory to prior reports of cancers from Taiwan. The metabolism of AA in the liver and urinary tract, transient exposure time, and high cell turnover rates at OGITC sites may explain our findings.

CONCLUSION

AA signatures in OGITCs are rare and unlikely to be a major contributing factor in oro-gastrointestinal tract tumorigenesis.

[Research Progress of Immunotherapy Biomarkers for Non-small Cell Lung Cancer]

Lung cancer is one of the most prevalent malignancies with the highest morbidity and mortality rates worldwide. In recent years, with the development of immune-oncology research and several therapeutic antibodies have reach the clinic, many breakthroughs have been made in immunotherapy. The advent of immunotherapy has revolutionized the treatment of NSCLC, but the response and durable clinical benefit are only observed in a small subset of patients. Therefore, strategies to screen the potential beneficial population and improve the efficacy of immunotherapy remain an essential topic. In the current article, the author review the biomarkers that have potential to better predict responders to immunotherapy and to provide ideas for the clinical application of immunotherapy.
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Comprehensive Analysis of N6-methyladenosine Modification Patterns Associated With Multiomic Characteristics of Bladder Cancer

Purpose: To comprehensively analyze N6-methyladenosine modification patterns in bladder tumors and to further systematically explore the inherent relationships between these modification patterns and multiomic tumor characteristics. Materials and Methods: A total of 901 bladder tumor samples, including 405 samples from TCGA database, 188 samples from GSE13507 and 308 samples from GSE32894, were included in this systematic analysis. The N6-methyladenosine modification patterns were identified utilizing unsupervised clustering analysis. To quantify N6-methyladenosine modification patterns, the m6Ascore of individual sample was developed using principal component analysis algorithms. Relationships among immune infiltration, tumor mutation burden, various clinical characteristics, molecular subtypes, and the m6Ascore were systematically analyzed. The guiding value of m6Ascore in immunotherapy was further validated in an external trial cohort. Genomics of Drug Sensitivity in Cancer expression references were also utilized to perform drug sensitivity analysis for patients with distinct m6A modification patterns. Results: We determined three different N6-methyladenosine modification patterns for 901 bladder tumors. The quantitative m6Ascore of individual sample derived from N6-methyladenosine modification patterns could play a significant role in predicting overall survival, immune cell infiltration, and classic oncogene mutations. A low m6Ascore combined with high tumor mutation burden indicated better survival outcomes (p < 0.001). A higher m6Ascore also indicated a higher grade, higher T and N stage, elder ages, higher death rate, and higher PD1/PDL1/CTLA4 expressions (p < 0.01). The Basal type tended to exhibit significantly higher m6Ascores than the Luminal and Neuronal subtypes. External immunotherapy cohorts demonstrated that no difference in therapeutic effects was noted between the high and low m6Ascore groups when anti-PD1 immunotherapy was exclusively administered. When anti-PD1 and anti-CTLA4 immunotherapy were simultaneously administered, the high m6Ascore group had a significantly better prognosis than the low m6Ascore group (p < 0.001). High m6A groups were potentially sensitive to various medical treatments including Bleomycin, Bortezomib, Cisplatin, Cyclopamine, Dasatinib, Docetaxe, Rapamycin, and Vinblastine in this study. Conclusions: This study systematically revealed the important roles of m6A methylation modification patterns in bladder tumors. Detailed quantification of m6A modification patterns could improve our understanding of the bladder tumor microenvironments and could provide guidance for future immunotherapy strategies.

Therapeutic Implications of Tumor Microenvironment in Lung Cancer: Focus on Immune Checkpoint Blockade

In the last decade, the treatment of non-small cell lung cancer (NSCLC) has been revolutionized by the introduction of immune checkpoint inhibitors (ICI) directed against programmed death protein 1 (PD-1) and its ligand (PD-L1), or cytotoxic T lymphocyte antigen 4 (CTLA-4). In spite of these improvements, some patients do not achieve any benefit from ICI, and inevitably develop resistance to therapy over time. Tumor microenvironment (TME) might influence response to immunotherapy due to its prominent role in the multiple interactions between neoplastic cells and the immune system. Studies investigating lung cancer from the perspective of TME pointed out a complex scenario where tumor angiogenesis, soluble factors, immune suppressive/regulatory elements and cells composing TME itself participate to tumor growth. In this review, we point out the current state of knowledge involving the relationship between tumor cells and the components of TME in NSCLC as well as their interactions with immunotherapy providing an update on novel predictors of benefit from currently employed ICI or new therapeutic targets of investigational agents. In first place, increasing evidence suggests that TME might represent a promising biomarker of sensitivity to ICI, based on the presence of immune-modulating cells, such as Treg, myeloid derived suppressor cells, and tumor associated macrophages, which are known to induce an immunosuppressive environment, poorly responsive to ICI. Consequently, multiple clinical studies have been designed to influence TME towards a pro-immunogenic state and subsequently improve the activity of ICI. Currently, the mostly employed approach relies on the association of "classic" ICI targeting PD-1/PD-L1 and novel agents directed on molecules, such as LAG-3 and TIM-3. To date, some trials have already shown promising results, while a multitude of prospective studies are ongoing, and their results might significantly influence the future approach to cancer immunotherapy.

Challenges for Vaccinologists in the First Half of the Twenty-First Century

The COVID-19 pandemic of 2020-2021 has highlighted the importance of vaccines and vaccination in human health. The pandemic has resulted in social distancing, travel restrictions, decreased trade, high unemployment, commodity price decline, and financial stress that has impacted the global economy. Since December 2020, a massive vaccination campaign is undergoing in every country on the planet to protect against SARS-CoV-2. Vaccination is the cheapest health-care interventions that can save more lives than any other drugs or therapies. Some of the common diseases of the twentieth century including smallpox and polio are seldom reported due to intense vaccination programs that eradicated it. Smallpox is completely eradicated globally; whereas, polio is confined to only a couple of countries. Vaccination has not only improved the health of man but also improved food security by preventing diseases in farm animals and aquacultured fish. Awareness of the principles of immunology and novel vaccines has led to effective vaccination strategies. Climate change could lead to generation of new strains of infectious microorganisms that would require development of novel vaccines. Recent years have seen the increase in incidence of brain-eating amoeba and flesh-eating bacteria (necrotizing fasciitis). There are no vaccines for these diseases. Though vaccination programs have eradicated several diseases and increased the quality of life, there are several diseases that have no effective vaccines. Currently there are no vaccines for cancer, neurodegenerative diseases, autoimmune diseases, as well as infectious diseases like tuberculosis, AIDS, and parasitic diseases including malaria. Spontaneous evolution of pathogenic microorganisms may lead to pandemics that impact the health of not only humanity but also other animals. Hence, the challenge to vaccinologists is the development of novel vaccines and vaccination strategies within limited time period and using minimum resources. In addition, the vaccine developed should be administered globally within a short duration so as to prevent generation of pathogenic variants more lethal than the parent strain.

A Darwinian perspective on tumor immune evasion

Evading immune-mediated destruction is a critical step of tumor evolution and the immune system is one of the strongest selective pressures during tumorigenesis. Analyzing tumor immune evasion from a Darwinian perspective may provide critical insight into the mechanisms of primary immune escape and acquired resistance to immunotherapy. Here, we review the steps required to mount an anti-tumor immune response, describe how each of these steps is disrupted during tumorigenesis, list therapeutic strategies to restore anti-tumor immunity, and discuss each mechanism of immune and therapeutic evasion from a Darwinian perspective.

Emerging biomaterial-based strategies for personalized therapeutic in situ cancer vaccines

Landmark successes in oncoimmunology have led to development of therapeutics boosting the host immune system to eradicate local and distant tumors with impactful tumor reduction in a subset of patients. However, current immunotherapy modalities often demonstrate limited success when involving immunologically cold tumors and solid tumors. Here, we describe the role of various biomaterials to formulate cancer vaccines as a form of cancer immunotherapy, seeking to utilize the host immune system to activate and expand tumor-specific T cells. Biomaterial-based cancer vaccines enhance the cancer-immunity cycle by harnessing cellular recruitment and activation against tumor-specific antigens. In this review, we discuss biomaterial-based vaccine strategies to induce lymphocytic responses necessary to mediate anti-tumor immunity. We focus on strategies that selectively attract dendritic cells via immunostimulatory gradients, activate them against presented tumor-specific antigens, and induce effective cross-presentation to T cells in secondary lymphoid organs, thereby generating immunity. We posit that personalized cancer vaccines are promising targets to generate long-term systemic immunity against patient- and tumor-specific antigens to ensure long-term cancer remission.

KRAS and MET in non-small-cell lung cancer: two of the new kids on the 'drivers' block

Non-small-cell lung cancer (NSCLC) is a heterogeneous disease, and therapeutic management has advanced to identify various critical oncogenic mutations that promote lung cancer tumorigenesis. Subsequent studies have developed targeted therapies against these oncogenes in the hope of personalized treatment based on the tumor's molecular genomics. This review presents a comprehensive review of the biology, new therapeutic interventions, and resistance patterns of two well-defined subgroups, tumors with KRAS and MET alterations. We also discuss the status of molecular testing practices for these two key oncogenic drivers, considering the progressive introduction of next-generation sequencing (NGS) and RNA sequencing in regular clinical practice.

Igniting Hope for Tumor Immunotherapy: Promoting the “Hot and Cold” Tumor Transition

The discovery of immune checkpoint inhibitors (ICIs) has ushered a new era for immunotherapy against malignant tumors through the killing effects of cytotoxic T lymphocytes in the tumor microenvironment (TME), resulting in long-lasting tumor suppression and regression. Nevertheless, given that ICIs are highly dependent on T cells in the TME and that most tumors lack T-cell infiltration, promoting the conversion of such immunosuppressive “cold” tumors to “hot” tumors is currently a key challenge in tumor immunotherapy. Herein, we systematically outlined the mechanisms underlying the formation of the immunosuppressive TME in cold tumors, including the role of immunosuppressive cells, impaired antigen presentation, transforming growth factor-β, STAT3 signaling, adenosine, and interferon-γ signaling. Moreover, therapeutic strategies for promoting cold tumors to hot tumors with adequate T-cell infiltration were also discussed. Finally, the prospects of therapeutic tools such as oncolytic viruses, nanoparticles, and photothermal therapy in restoring immune activity in cold tumors were thoroughly reviewed.

OUP accepted manuscript

Alternative splicing is frequently involved in the diversification of protein function and can also be modulated for therapeutic purposes. Here we develop a predictive model, called Exon ByPASS (predicting Exon skipping Based on Protein amino acid SequenceS), to assess the criticality of exon inclusion based solely on information contained in the amino acid sequence upstream and downstream of the exon junctions. By focusing on protein sequence, Exon ByPASS predicts exon skipping independent of tissue and species in the absence of any intronic information. We validate model predictions using transcriptomic and proteomic data and show that the model can capture exon skipping in different tissues and species. Additionally, we reveal potential therapeutic opportunities by predicting synthetically skippable exons and neo-junctions arising in cancer cells.

A Pan-Cancer Analysis of Predictive Methylation Signatures of Response to Cancer Immunotherapy

Recently, tumor immunotherapy based on immune checkpoint inhibitors (ICI) has been introduced and widely adopted for various tumor types. Nevertheless, tumor immunotherapy has a few drawbacks, including significant uncertainty of outcome, the possibility of severe immune-related adverse events for patients receiving such treatments, and the lack of effective biomarkers to determine the ICI treatments' responsiveness. DNA methylation profiles were recently identified as an indicator of the tumor immune microenvironment. They serve as a potential hot spot for predicting responses to ICI treatment for their stability and convenience of measurement by liquid biopsy. We demonstrated the possibility of DNA methylation profiles as a predictor for responses to the ICI treatments at the pan-cancer level by analyzing DNA methylation profiles considered responsive and non-responsive to the treatments. An SVM model was built based on this differential analysis in the pan-cancer levels. The performance of the model was then assessed both at the pan-cancer level and in specific tumor types. It was also compared to the existing gene expression profile-based method. DNA methylation profiles were shown to be predictable for the responses to the ICI treatments in the TCGA cases in pan-cancer levels. The proposed SVM model was shown to have high performance in pan-cancer and specific cancer types. This performance was comparable to that of gene expression profile-based one. The combination of the two models had even higher performance, indicating the potential complementarity of the DNA methylation and gene expression profiles in the prediction of ICI treatment responses.

Smart biomaterials to enhance the efficiency of immunotherapy in glioblastoma: State of the art and future perspectives

Glioblastoma multiform (GBM) is considered as the most lethal tumor among CNS malignancies. Although immunotherapy has achieved remarkable advances in cancer treatment, it has not shown satisfactory results in GBM patients. Biomaterial science, along with nanobiotechnology, is able to optimize the efficiency of immunotherapy in these patients. They can be employed to provide the specific activation of immune cells in tumor tissue and combinational therapy as well as preventing systemic adverse effects resulting from hyperactivation of immune responses and off-targeting effect. Advance biomaterials in this field are classified into targeting nanocarriers and localized delivery systems. This review will offer an overview of immunotherapy strategies for glioblastoma and advance delivery systems for immunotherapeutics that may have a high potential in glioblastoma treatment.

Harnessing the immune system against cancer: current immunotherapy approaches and therapeutic targets

Cancer immunotherapy is a rapidly evolving concept that has been given the tag "fifth pillar" of cancer therapy while radiation therapy, chemotherapy, surgery and targeted therapy remain the other four pillars. This involves the stimulation of the immune system to control tumor growth and it specifically targets the neoplastic cells rather than the normal cells. Conventional chemotherapy has many limitations which include drug resistance, recurrence of cancer and severe adverse effects. Immunology has made major treatment breakthroughs for several cancers such as colorectal cancer, prostate cancer, breast cancer, lung cancer, liver cancer, kidney cancer, stomach cancer, acute lymphoblastic leukaemia etc. Currently, therapeutic strategies harnessing the immune system involve Checkpoint inhibitors, Chimeric antigen receptor T cells (CAR T cells), Monoclonal antibodies, Cancer vaccines, Cytokines, Radio-immunotherapy and Oncolytic virus therapy. The molecular characterization of several tumor antigens (TA) indicates that these TA can be utilized as promising candidates in cancer immunotherapy strategies. Here in this review, we highlight and summarize the different categories of emerging cancer immunotherapies along with the immunologically recognized tumor antigens involved in the tumor microenvironment.

Kidney Cancer and Chronic Kidney Disease: Too Close for Comfort

Kidney cancer and chronic kidney disease are two renal pathologies with very different clinical management strategies and therapeutical options. Nonetheless, the cellular and molecular mechanisms underlying both conditions are closely related. Renal physiology is adapted to operate with a limited oxygen supply, making the kidney remarkably equipped to respond to hypoxia. This tightly regulated response mechanism is at the heart of kidney cancer, leading to the onset of malignant cellular phenotypes. Although elusive, the role of hypoxia in chronic kidney diseases is emerging as related to fibrosis, a pivotal factor in decaying renal function. The present review offers a perspective on the common biological traits shared between kidney cancer and chronic kidney disease and the available and prospective therapies for both conditions.

The Coevolution of Placentation and Cancer

Analogies between placentation, in particular the behavior of trophoblast cells, and cancer have been noted since the beginning of the twentieth century. To what degree these can be explained as a consequence of the evolution of placentation has been unclear. In this review, we conclude that many similarities between trophoblast and cancer cells are shared with other, phylogenetically older processes than placentation. The best candidates for cancer hallmarks that can be explained by the evolution of eutherian placenta are mechanisms of immune evasion. Another dimension of the maternal accommodation of the placenta with an impact on cancer malignancy is the evolution of endometrial invasibility. Species with lower degrees of placental invasion tend to have lower vulnerability to cancer malignancy. We finally identify several areas in which one could expect to see coevolutionary changes in placental and cancer biology but that, to our knowledge, have not been explored. Expected final online publication date for the Annual Review of Animal Biosciences, Volume 10 is February 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Key Activating and Inhibitory Ligands Involved in the Mobilization of Natural Killer Cells for Cancer Immunotherapies

Natural killer (NK) cells are the most potent arm of the innate immune system and play an important role in immunity, alloimmunity, autoimmunity, and cancer. NK cells recognize “altered-self” cells due to oncogenic transformation or stress due to viral infection and target to kill them. The effector functions of NK cells depend on the interaction of the activating and inhibitory receptors on their surface with their cognate ligand expressed on the target cells. These activating and inhibitory receptors interact with major histocompatibility complex I (MHC I) expressed on the target cells and make decisions to mount an immune response. NK cell immune response includes cytolytic activity and secretion of cytokines to help with the ongoing immune response. The advancement of our knowledge on the expression of inhibitory and activating molecules led us to exploit these molecules in the treatment of cancer. This review discusses the importance of activating and inhibitory receptors on NK cells and their clinical importance in cancer immunotherapy.

Smoking signature is superior to programmed death-ligand 1 expression in predicting pathological response to neoadjuvant immunotherapy in lung cancer patients

Background

There is a paucity of biomarkers that can predict the degree of pathological response [e.g., pathological complete response (pCR) or major response (pMR)] to immunotherapy. Neoadjuvant immunotherapy provides an ideal setting for exploring responsive biomarkers because the pathological responses can be directly and accurately evaluated.

Methods

We retrospectively collected the clinicopathological characteristics and treatment outcomes of non-small cell lung cancer (NSCLC) patients who received neoadjuvant immunotherapy or chemo-immunotherapy followed by surgery between 2018 and 2020 at a large academic thoracic cancer center. Clinicopathological factors associated with pathological response were analyzed.

Results

A total of 39 patients (35 males and 4 females) were included. The most common histological subtype was lung squamous cell carcinoma (LUSC) (n=28, 71.8%), followed by lung adenocarcinoma (LUAD) (n=11, 28.2%). After neoadjuvant treatment, computed tomography (CT) scan-based evaluation showed poor agreement with the postoperatively pathological examination (weighted kappa =0.0225; P=0.795), suggesting the poor performance of CT scans in evaluating the response to immunotherapy. Importantly, we found that the smoking signature displayed a better performance than programmed death-ligand 1 (PD-L1) expression in predicting the pathological response (area under the curve: 0.690 vs. 0.456; P=0.0259), which might have resulted from increased tumor mutational burden (TMB) and/or microsatellite instability (MSI) relating to smoking exposure.

Conclusions

These findings suggest that CT scan-based evaluation is not able to accurately reflect the pathological response to immunotherapy and that smoking signature is a superior marker to PD-L1 expression in predicting the benefit of immunotherapy in NSCLC patients.

Towards an updated view on the clinical management of pancreatic adenocarcinoma: Current and future perspectives

Pancreatic cancer has a dire prognosis and will represent the second leading cause of cancer death in the next 10 years. The multifactorial approach represents one of the main issues in controlling the extension of this neoplasm. In recent years, the characteristics of the tumor microenvironment, metastasis mechanisms and the relationship between immune system and neoplastic cells have been described, which has made it possible to understand the pathophysiology of pancreatic adenocarcinoma. Currently, there is a failure to provide an effective preventive method or early detection, so patients present with an advanced stage at the time of diagnosis. Despite numerous efforts, little progress has been made in clinical outcome and in improving survival in long term. Therefore, in the recent years, diverse diagnostic tests, treatments and possible approaches have been developed in the fields of radiotherapy, chemotherapy and surgery to find a combination of them that improves life expectancy in patients diagnosed with pancreatic cancer. At the moment, numerous clinical trials are being conducted to evaluate preventive diagnostic procedures such as serological markers or perfecting available imaging tests. On the other hand, implementation of immunotherapy is being studied in a neoplasm that has lagged in the application of this procedure since present possible treatments do not substantially improve quality of life. Therefore, the purpose of our study is to summarize the main progresses that have been made in the diagnosis, treatment and screening of this disease, explaining the limitations that have been observed and analyzing future prospects in the management of this illness.

Integrating single cell sequencing with a spatial quantitative systems pharmacology model spQSP for personalized prediction of triple-negative breast cancer immunotherapy response

Response to cancer immunotherapies depends on the complex and dynamic interactions between T cell recognition and killing of cancer cells that are counteracted through immunosuppressive pathways in the tumor microenvironment. Therefore, while measurements such as tumor mutational burden provide biomarkers to select patients for immunotherapy, they neither universally predict patient response nor implicate the mechanisms that underlie immunotherapy resistance. Recent advances in single-cell RNA sequencing technology measure cellular heterogeneity within cells of an individual tumor but have yet to realize the promise of predictive oncology. In addition to data, mechanistic multiscale computational models are developed to predict treatment response. Incorporating single-cell data from tumors to parameterize these computational models provides deeper insights into prediction of clinical outcome in individual patients. Here, we integrate whole-exome sequencing and scRNA-seq data from Triple-Negative Breast Cancer patients to model neoantigen burden in tumor cells as input to a spatial Quantitative System Pharmacology model. The model comprises a four-compartmental Quantitative System Pharmacology sub-model to represent a whole patient and a spatial agent-based sub-model to represent tumor volumes at the cellular scale. We use the high-throughput single-cell data to model the role of antigen burden and heterogeneity relative to the tumor microenvironment composition on predicted immunotherapy response. We demonstrate how this integrated modeling and single-cell analysis framework can be used to relate neoantigen heterogeneity to immunotherapy treatment outcomes. Our results demonstrate feasibility of merging single-cell data to initialize cell states in multiscale computational models such as the spQSP for personalized prediction of clinical outcomes to immunotherapy.

PD-L1 immunostaining: what pathologists need to know

BACKGROUND

Immune checkpoint proteins, especially PD-L1 and PD-1, play a crucial role in controlling the intensity and duration of the immune response, thus preventing the development of autoimmunity. These proteins play a vital role in enabling cancer cells to escape immunity, proliferate and progress.

METHODS

This brief review highlights essential points related to testing for immune checkpoint therapy that histopathologists need to know.

RESULTS

In recent years, several inhibitors of these proteins have been used to reactivate the immune system to fight cancer. Selection of patients for such therapy requires demonstration of PD-L1 activation on the tumor cells, best done by immunohistochemical staining of the tumor and immune cells using various antibodies with predetermined thresholds.

CONCLUSIONS

Immune checkpoint therapy appears to be promising and is rapidly expanding to include a large variety of cancers.

Bioinformatics Analyses Reveal the Prognostic Value and Biological Roles of SEPHS2 in Various Cancers

Purpose

Selenophosphate synthetase 2 (SEPHS2) has been shown to regulate selenoprotein biosynthesis by catalyzing the synthesis of active selenium donor selenophosphate. SEPHS2 influences the survival of tumor cells. However, few studies have explored the expression level and prognostic of SEPHS2 in various cancers.

Methods

The expression of SEPHS2 in human tumor tissues and normal adjacent tissues was analyzed in The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), Human Protein Atlas (HPA), and UALCAN databases. Cox regression analysis and Kaplan–Meier curve analysis were performed to analyze the association of SEPHS2 expression with the prognosis of cancer patients. The expression and prognosis of SEPHS2 in gliomas were further verified using the Chinese Glioma Genome Atlas (CGGA) dataset. The relationship between SEPHS2 and immune infiltration, tumor mutational burden (TMB), microsatellite instability (MSI), and neoantigens was comprehensively explored using a TCGA cohort. The mechanism by which SEPHS2 regulates tumor progression was explored by using the STRING database. A nomogram was constructed using the R software to predict the overall survival (OS) of patients with brain lower grade glioma (LGG).

Results

SEPHS2 was highly expressed in many cancers including LGG. Its high expression was significantly associated with poor OS, disease-free survival (DFS), and progression-free survival (PFS). Univariate and multivariate Cox analyses showed that SEPHS2 was an independent prognostic factor for LGG. Concordance index and calibration curves revealed that the nomogram had good predictive performance (concordance index: 0.791; 95% CI: 0.732–1). A significant correlation was found between SEPHS2 and immune infiltration, TMB, MSI, and tumor neoantigens across diverse cancers. Enrichment analysis showed that SEPHS2 may regulate the PPAR signaling pathway.

Conclusion

SEPHS2 expression regulates tumor development and it is a potential treatment target and prognostic biomarker, especially for lower grade glioma.

Abscopal Effect and Drug-Induced Xenogenization: A Strategic Alliance in Cancer Treatment?

The current state of cancer treatment is still far from being satisfactory considering the strong impairment of patients' quality of life and the high lethality of malignant diseases. Therefore, it is critical for innovative approaches to be tested in the near future. In view of the crucial role that is played by tumor immunity, the present review provides essential information on the immune-mediated effects potentially generated by the interplay between ionizing radiation and cytotoxic antitumor agents when interacting with target malignant cells. Therefore, the radiation-dependent abscopal effect (i.e., a biological effect of ionizing radiation that occurs outside the irradiated field), the influence of cancer chemotherapy on the antigenic pattern of target neoplastic cells, and the immunogenic cell death (ICD) caused by anticancer agents are the main topics of this presentation. It is widely accepted that tumor immunity plays a fundamental role in generating an abscopal effect and that anticancer drugs can profoundly influence not only the host immune responses, but also the immunogenic pattern of malignant cells. Remarkably, several anticancer drugs impact both the abscopal effect and ICD. In addition, certain classes of anticancer agents are able to amplify already expressed tumor-associated antigens (TAA). More importantly, other drugs, especially triazenes, induce the appearance of new tumor neoantigens (TNA), a phenomenon that we termed drug-induced xenogenization (DIX). The adoption of the abscopal effect is proposed as a potential therapeutic modality when properly applied concomitantly with drug-induced increase in tumor cell immunogenicity and ICD. Although little to no preclinical or clinical studies are presently available on this subject, we discuss this issue in terms of potential mechanisms and therapeutic benefits. Upcoming investigations are aimed at evaluating how chemical anticancer drugs, radiation, and immunotherapies are interacting and cooperate in evoking the abscopal effect, tumor xenogenization and ICD, paving the way for new and possibly successful approaches in cancer therapy.

Mathematical model of a personalized neoantigen cancer vaccine and the human immune system

Cancer vaccines are an important component of the cancer immunotherapy toolkit enhancing immune response to malignant cells by activating CD4⁺ and CD8⁺ T cells. Multiple successful clinical applications of cancer vaccines have shown good safety and efficacy. Despite the notable progress, significant challenges remain in obtaining consistent immune responses across heterogeneous patient populations, as well as various cancers. We present a mechanistic mathematical model describing key interactions of a personalized neoantigen cancer vaccine with an individual patient’s immune system. Specifically, the model considers the vaccine concentration of tumor-specific antigen peptides and adjuvant, the patient’s major histocompatibility complexes I and II copy numbers, tumor size, T cells, and antigen presenting cells. We parametrized the model using patient-specific data from a clinical study in which individualized cancer vaccines were used to treat six melanoma patients. Model simulations predicted both immune responses, represented by T cell counts, to the vaccine as well as clinical outcome (determined as change of tumor size). This model, although complex, can be used to describe, simulate, and predict the behavior of the human immune system to a personalized cancer vaccine.

Personalized cancer vaccines have gained attention in recent years due to the advances in sequencing techniques that have facilitated the identification of multiple tumor-specific mutations. This type of individualized immunotherapy has the potential to be specific, efficacious, and safe since it induces an immune response to protein targets not found on normal cells. This work focuses on understanding and analyzing important mechanisms involved in the activity of personalized cancer vaccines using a mechanistic mathematical model. This model describes the interactions of a personalized neoantigen peptide cancer vaccine, the human immune system and tumor cells operating at the molecular and cellular level. The molecular level captures the processing and presentation of neoantigens by dendritic cells to the T cells using cell surface proteins. The cellular level describes the differentiation of dendritic cells due to peptides and adjuvant concentrations in the vaccine, activation, and proliferation of T cells in response to treatment, and tumor growth. The model captures immune response behavior to a vaccine associated with patient-specific factors (e.g., different initial tumor burdens). This model enables the simulation of a complex biological system, the human immune system, by performing in silico experiments that may become the input for further analysis such as the identification of key parameters or mechanisms and/or interpretation of data.

The Role of Neoantigens in Cancer Immunotherapy

Somatic mutation-derived neoantigens, expressed only on tumor cells, may elicit antitumor T-cell responses in cancer immunotherapies with minimal immune tolerance. Neoantigens can be identified by multiple bioinformatics technologies, mainly based on whole-exome sequencing. Personalized cancer vaccines and adoptive T cell therapies are two primary treatment modalities targeting neoantigens, and both of them have shown promising therapeutic effects. This review, summarizes the history of neoantigen-related tumor control, introduces recent neoantigen screening and identification methods, and discusses the role of neoantigen in cancer immunotherapies. Moreover, we propose the challenges of targeting neoantigens for cancer treatment.

N6-Methylandenosine-Related lncRNAs Predict Prognosis and Immunotherapy Response in Bladder Cancer

Both lncRNAs and the N6-methyladenosine (m6A) modification are key regulators of tumorigenesis and innate immunity. However, little is known about the m6A modification of lncRNAs and their clinical and immune relevance in bladder cancer. In this study, we identified m6A-related lncRNAs using Pearson correlation analysis in The Cancer Genome Atlas (TCGA) and the IMvigor210 datasets. Next, univariate Cox regression was performed using the TCGA dataset to filter prognostic m6A-related lncRNAs, which were further subjected to the least absolute shrinkage and selection operator (LASSO) Cox regression to establish a 12 m6A-related lncRNA prognostic score (m6A-LRS). The m6A-LRS was validated in the IMvigor210 dataset. In addition, high m6A-LRS tumors, characterized by decreased tumor mutation load and neoantigen load, showed poorer response to immunotherapy than those with low m6A-LRS in the IMvigor210 dataset. Further, we constructed an m6A-LRS-based nomogram that demonstrated a strong ability to predict overall survival in patients with bladder cancer. Moreover, enrichment analysis revealed that tumor-associated biological processes, oncogenic signaling, and tumor hallmarks were commonly associated with a high m6A-LRS. Gene set variation analysis also indicated that high m6A-LRS was associated with activation of canonical oncogenic signatures, such as the epithelial-to-mesenchymal transition, cell cycle regulators, and DNA replication, as well as activation of immunosuppressive signatures, such as the T-cell exhaustion and pan-fibroblast-TGF-β response signatures. Furthermore, we observed distinct tumor microenvironment cell infiltration characteristics between high- and low-risk tumors. High m6A-LRS tumors showed reduced infiltration of CD8+ T-cells and enhanced infiltration of macrophages and fibroblasts. Additionally, we established a competing endogenous RNA network based on the12 m6A-related lncRNAs. Finally, three lncRNAs (SNHG16, SBF2-AS1, and BDNF-AS) were selected for further validation. The qualitative PCR assay on 10 pairs of bladder cancer and adjacent normal control samples validated the differential expression, and methylated RNA immunoprecipitation (MeRIP) analysis demonstrated a robust m6A enrichment in T24 bladder cancer cells compared with normal uroepithelial cells (SVHUC-1). In conclusion, this study introduced an m6A-related lncRNA signature that identified a subgroup of patients with poor prognoses and suboptimal immune responses, thus providing novel approaches for treatment response prediction and patient stratification in bladder cancer.

Technological advances in cancer immunity: from immunogenomics to single-cell analysis and artificial intelligence

Immunotherapies play critical roles in cancer treatment. However, given that only a few patients respond to immune checkpoint blockades and other immunotherapeutic strategies, more novel technologies are needed to decipher the complicated interplay between tumor cells and the components of the tumor immune microenvironment (TIME). Tumor immunomics refers to the integrated study of the TIME using immunogenomics, immunoproteomics, immune-bioinformatics, and other multi-omics data reflecting the immune states of tumors, which has relied on the rapid development of next-generation sequencing. High-throughput genomic and transcriptomic data may be utilized for calculating the abundance of immune cells and predicting tumor antigens, referring to immunogenomics. However, as bulk sequencing represents the average characteristics of a heterogeneous cell population, it fails to distinguish distinct cell subtypes. Single-cell-based technologies enable better dissection of the TIME through precise immune cell subpopulation and spatial architecture investigations. In addition, radiomics and digital pathology-based deep learning models largely contribute to research on cancer immunity. These artificial intelligence technologies have performed well in predicting response to immunotherapy, with profound significance in cancer therapy. In this review, we briefly summarize conventional and state-of-the-art technologies in the field of immunogenomics, single-cell and artificial intelligence, and present prospects for future research.

Demystifying emerging bulk RNA-Seq applications: the application and utility of bioinformatic methodology

Significant innovations in next-generation sequencing techniques and bioinformatics tools have impacted our appreciation and understanding of RNA. Practical RNA sequencing (RNA-Seq) applications have evolved in conjunction with sequence technology and bioinformatic tools advances. In most projects, bulk RNA-Seq data is used to measure gene expression patterns, isoform expression, alternative splicing and single-nucleotide polymorphisms. However, RNA-Seq holds far more hidden biological information including details of copy number alteration, microbial contamination, transposable elements, cell type (deconvolution) and the presence of neoantigens. Recent novel and advanced bioinformatic algorithms developed the capacity to retrieve this information from bulk RNA-Seq data, thus broadening its scope. The focus of this review is to comprehend the emerging bulk RNA-Seq-based analyses, emphasizing less familiar and underused applications. In doing so, we highlight the power of bulk RNA-Seq in providing biological insights.

Targeting neoantigens for cancer immunotherapy

Neoantigens, a type of tumor-specific antigens derived from non-synonymous mutations, have recently been characterized as attractive targets for cancer immunotherapy. Owing to the development of next-generation sequencing and utilization of machine-learning algorithms, it has become feasible to computationally predict neoantigens by depicting genetic alterations, aberrant post-transcriptional mRNA processing and abnormal mRNA translation events within tumor tissues. Consequently, neoantigen-based therapies such as cancer vaccines have been widely tested in clinical trials and have demonstrated promising safety and efficacy, opening a new era for cancer immunotherapy. We systematically summarize recent advances in the identification of both personalized and public neoantigens, neoantigen formulations and neoantigen-based clinical trials in this review. Moreover, we discuss future techniques and strategies for neoantigen-based cancer treatment either as a monotherapy or as a combination therapy with radiotherapy, chemotherapy or immune checkpoint inhibitors.

The Clinical Application of Neoantigens in Esophageal Cancer

Esophageal cancer (EC) is a common malignant tumor with poor prognosis, and current treatments for patients with advanced EC remain unsatisfactory. Recently, immunotherapy has been recognized as a new and promising approach for various tumors. EC cells present a high tumor mutation burden and harbor abundant tumor antigens, including tumor-associated antigens and tumor-specific antigens. The latter, also referred to as neoantigens, are immunogenic mutated peptides presented by major histocompatibility complex class I molecules. While current genomics and bioinformatics technologies have greatly facilitated the identification of tumor neoantigens, identifying individual neoantigens systematically for successful therapies remains a challenging problem. Owing to the initiation of strong, specific tumor-killing cytotoxic T cell responses, neoantigens are emerging as promising targets to develop personalized treatment and have triggered the development of cancer vaccines, adoptive T cell therapies, and combination therapies. This review aims to give a current understanding of the clinical application of neoantigens in EC and provide direction for future investigation.

Development of neoantigens: from identification in cancer cells to application in cancer vaccines

Introduction: The discovery of neoantigens as mutated proteins specifically expressed in tumor cells but not in normal cells has led to improved cancer vaccines. Targeting neoantigens can induce anti-tumor T-cell responses to destroy tumors without damaging healthy cells. Extensive advances in genome sequencing technology and bioinformatics analysis have made it possible to discover and design effective neoantigens for use in therapeutic cancer vaccines. Neoantigens-based therapeutic personalized vaccines have shown promising results in cancer immunotherapy.Areas covered: We discuss the types of cancer neoantigens that can be recognized by the immune system in this review. We also summarize the detection, identification, and design of neoantigens and their appliction in developing cancer vaccines. Finally, clinical trials of neoantigen-based vaccines, their advantages, and their limitations are reviewed. From 2015 to 2020, the authors conducted a literature search of controlled randomized trials and laboratory investigations that that focused on neoantigens, their use in the design of various types of cancer vaccines.Expert opinion: Neoantigens are cancer cell-specific antigens, which their expression leads to the immune stimulation against tumor cells. The identification and delivery of specific neoantigens to antigen-presenting cells (APCs) with the help of anti-cancer vaccines promise novel and more effective cancer treatments.