Neoantigen Load, Antigen Presentation Machinery, and Immune Signatures Determine Prognosis in Clear Cell Renal Cell Carcinoma

Novel Immune Checkpoint Inhibitor Targets in Advanced or Metastatic Renal Cell Carcinoma: State of the Art and Future Perspectives

Immune checkpoint inhibitors (ICI) have become the cornerstone of treatment in renal cell carcinoma (RCC), for both metastatic disease and in an adjuvant setting. However, an adaptive resistance from cancer cells may arise during ICI treatment, therefore many studies are focusing on additional immune checkpoint inhibitor pathways. Promising targets of immunotherapeutic agents under investigation include T cell immunoglobulin and ITIM domain (TIGIT), immunoglobulin-like transcript 4 (ILT4), lymphocyte activation gene-3 (LAG-3), vaccines, T cell immunoglobulin and mucin domain-containing protein 3 (TIM-3), and chimeric antigen receptor (CAR) T cells. In this review of the literature, we recollect the current knowledge of the novel treatment strategies in the field of immunotherapy that are being investigated in RCC and analyze their mechanism of action, their activity and the clinical studies that are currently underway.

Stemness related lncRNAs signature for the prognosis and tumor immune microenvironment of ccRCC patients

Long non-coding RNAs (lncRNAs) and cancer stem cells (CSCs) are crucial for the growth, migration, recurrence, and medication resistance of tumors. However, the impact of lncRNAs related to stemness on the outcome and tumor immune microenvironment (TIME) in clear cell renal cell carcinoma (ccRCC) is still unclear. In this study, we aimed to predict the outcome and TIME of ccRCC by constructing a stem related lncRNAs (SRlncRNAs) signature. We firstly downloaded ccRCC patients' clinical data and RNA sequencing data from UCSC and TCGA databases, and abtained the differentially expressed lncRNAs highly correlated with stem index in ccRCC through gene expression differential analysis and Pearson correlation analysis. Then, we selected suitable SRlncRNAs for constructing a prognostic signature of ccRCC patients by LASSO Cox regression. Further, we used nomogram and Kaplan Meier curves to evaluate the SRlncRNA signature for the prognose in ccRCC. At last, we used ssGSEA and GSVA to evaluate the correlation between the SRlncRNAs signature and TIME in ccRCC. Finally, We obtained a signtaure based on six SRlncRNAs, which are correlated with TIME and can effectively predict the ccRCC patients' prognosis. The SRlncRNAs signature may be a noval prognostic indicator in ccRCC.

Highly expressed of BID indicates poor prognosis and mediates different tumor microenvironment characteristics in clear cell renal cell carcinoma

BACKGROUND

Studies have found that BH3 interacting domain death agonist (BID) is closely related to the occurrence and development of many kinds of tumors. However, little attention has been paid to the situation of BID in clear cell renal cell carcinoma (ccRCC). So, our aim was to explore the effect of BID in ccRCC.

METHODS

Survival analysis, ROC curve, correlation analysis and Cox regression analysis were executed to analyze the prognostic value and clinical correlation of BID in ccRCC. The risk prognosis model was constructed in the training cohort and further validated in the internal testing cohort, ICGC cohort, and GEO cohort. Transcriptome sequencing and immunohistochemical staining of clinical specimens were used to validate the results of bioinformatics analysis. The GSEA, ESTIMATE algorithm, CIBERSORT algorithm, ssGSEA, TIDE score, correlation and difference analysis were used to analyze the effects of BID on immune infiltration in tumor microenvironment (TME).

RESULTS

BID was highly expressed in ccRCC tissues, which was verified by transcriptome sequencing and immunohistochemical staining of clinical specimens. Patients with high expression of BID had a worse prognosis. BID is an independent prognostic factor for ccRCC. The prognostic model based on BID can accurately predict the prognosis of patients in different cohorts. In addition, the expression levels of BID was closely related to immunomodulatory molecules such as PD-1, LAG3, and CTLA4. Enrichment analysis indicated that BID was significantly enriched in immune-related responses and cancer-related pathways. The change of BID expression mediates different characteristics of immune infiltration in TME.

CONCLUSIONS

BID is highly expressed in ccRCC, which is a reliable biomarker of ccRCC prognosis. It is closely related to TME, and may be a potential target for immunotherapy in patients with ccRCC.

Recent advances in personalized cancer immunotherapy with immune checkpoint inhibitors, T cells and vaccines

The results of genomic and molecular profiling of cancer patients can be effectively applied to immunotherapy agents, including immune checkpoint inhibitors, to select the most appropriate treatment. In addition, accurate prediction of neoantigens facilitates the development of individualized cancer vaccines and T-cell therapy. This review summarizes the biomarker(s) predicting responses to immune checkpoint inhibitors and focuses on current strategies to identify and isolate neoantigen-reactive T cells as well as the clinical development of neoantigen-based therapeutics. The results suggest that maximal T-cell stimulation and expansion can be achieved with combination therapies that enhance antigen-presenting cells' function and optimal T-cell priming in lymph nodes.

Long-Term Survival of Patients with Stage T1N0M1 Renal Cell Carcinoma

Metastatic renal cell carcinoma (RCC) is among the most lethal urological malignancies. However, small, localized RCCs (≤7 cm, stage T1) have an excellent prognosis. There is a rare patient subgroup diagnosed with synchronous distant metastasis (T1N0M1), of which very little is known in terms of survival outcomes and underlying disease biology. Herein, we examined the long-term survival of 27 patients with clear cell RCC (ccRCC) stage T1N0M1 in comparison to 18 patients without metastases (T1N0M0). Tumor tissue was stained by immunohistochemistry for CD8+ tumor infiltrating lymphocytes (TILs). As expected, patients with stage T1N0M1 showed a significantly worse median cancer specific survival (CSS; 2.8 years) than patients with stage T1N0M0 (17.7 years; HR 0.077; 95% CI, 0.022-0.262). However, eight patients (29.6%) with ccRCC stage T1N0M1 survived over five years, and three of those patients (11.1%) survived over a decade. Some of these patients benefitted from an intensified, multimodal treatment including metastasis-directed therapy. The number of CD8+ TILs was substantially higher in stage T1N0M1 ccRCCs than in stage T1N0M0 ccRCCs, suggesting a more aggressive tumor biology. In conclusion, long-term survival is possible in patients with ccRCC stage T1N0M1, with some patients benefitting from an intensified, multimodal treatment approach.

Antigenic targets in clear cell renal cell carcinoma

Immune checkpoint inhibitors (ICIs) have transformed the management of advanced renal cell carcinoma (RCC), but most patients still do not receive a long-term benefit from these therapies, and many experience off-target, immune-related adverse effects. RCC is also different from many other ICI-responsive tumors, as it has only a modest mutation burden, and total neoantigen load does not correlate with ICI response. In order to improve the efficacy and safety of immunotherapies for RCC, it is therefore critical to identify the antigens that are targeted in effective anti-tumor immunity. In this review, we describe the potential classes of target antigens, and provide examples of previous and ongoing efforts to investigate and target antigens in RCC, with a focus on clear cell histology. Ultimately, we believe that a concerted antigen discovery effort in RCC will enable an improved understanding of response and resistance to current therapies, and lay a foundation for the future development of "precision" antigen-directed immunotherapies.

Identification of DNA repair gene signature and potential molecular subtypes in hepatocellular carcinoma

DNA repair is a critical factor in tumor progression as it impacts tumor mutational burden, genome stability, PD-L1 expression, immunotherapy response, and tumor-infiltrating lymphocytes (TILs). In this study, we present a prognostic model for hepatocellular carcinoma (HCC) that utilizes genes related to the DNA damage response (DDR). Patients were stratified based on their risk score, and groups with lower risk scores demonstrated better survival rates compared to those with higher risk scores. The prognostic model's accuracy in predicting 1-, 3-, and 5-year survival rates for HCC patients was analyzed using receiver operator curve analysis (ROC). Results showed good accuracy in predicting survival rates. Additionally, we evaluated the prognostic model's potential as an independent factor for HCC prognosis, along with tumor stage. Furthermore, nomogram was employed to determine the overall survival year of patients with HCC based on this independent factor. Gene set enrichment analysis (GSEA) revealed that in the high-risk group, apoptosis, cell cycle, MAPK, mTOR, and WNT cascades were highly enriched. We used training and validation datasets to identify potential molecular subtypes of HCC based on the expression of DDR genes. The two subtypes differed in terms of checkpoint receptors for immunity and immune cell filtration capacity.Collectively, our study identified potential biomarkers of HCC prognosis, providing novel insights into the molecular mechanisms underlying HCC.

Netie: inferring the evolution of neoantigen-T cell interactions in tumors

Neoantigens are the key targets of antitumor immune responses from cytotoxic T cells and play a critical role in affecting tumor progressions and immunotherapy treatment responses. However, little is known about how the interaction between neoantigens and T cells ultimately affects the evolution of cancerous masses. Here, we develop a hierarchical Bayesian model, named neoantigen-T cell interaction estimation (netie) to infer the history of neoantigen-CD8⁺ T cell interactions in tumors. Netie was systematically validated and applied to examine the molecular patterns of 3,219 tumors, compiled from a panel of 18 cancer types. We showed that tumors with an increase in immune selection pressure over time are associated with T cells that have an activation-related expression signature. We also identified a subset of exhausted cytotoxic T cells postimmunotherapy associated with tumor clones that newly arise after treatment. These analyses demonstrate how netie enables the interrogation of the relationship between individual neoantigen repertoires and the tumor molecular profiles. We found that a T cell inflammation gene expression profile (TIGEP) is more predictive of patient outcomes in the tumors with an increase in immune pressure over time, which reveals a curious synergy between T cells and neoantigen distributions. Overall, we provide a new tool that is capable of revealing the imprints left by neoantigens during each tumor's developmental process and of predicting how tumors will progress under further pressure of the host's immune system.

Current and Future Biomarkers for Immune Checkpoint Inhibitors in Head and Neck Squamous Cell Carcinoma

With the introduction of immunotherapy, significant improvement has been made in the treatment of head and neck squamous cell carcinoma (HNSCC). However, only a small subset of patients with HNSCC benefit from immunotherapy. The current biomarker, a programmed cell death protein ligand 1 (PD-L1) expression that is widely used in treatment decision making for advanced HNSCC, has only a moderate predictive value. Additionally, PD-L1-based assay has critical inherent limitations due to its highly dynamic nature and lack of standardization. With the advance in molecular techniques and our understanding of biology, more reliable, reproducible, and practical novel biomarkers are being developed. These include but are not limited to neoantigen/mutation characteristics, immune transcriptomes, tumor-infiltrating immune cell composition, cancer epigenomic, proteomics and metabolic characteristics, and plasma-based and organoid assays.

m6A Methylation Patterns and Tumor Microenvironment Infiltration Characterization in Clear-Cell Renal Cell Carcinoma

Increasing evidence suggests the essential regulation of RNA N6-methyladenosine (m6A) modification in carcinogenesis and immune response. Nevertheless, the potential impacts of these modifications on the tumor microenvironment (TME) immune cell infiltration characteristics in clear-cell renal cell carcinoma (ccRCC) remain unclear. Utilizing a consensus clustering algorithm, we determined three m6A modification patterns and identified three m6A-related gene clusters among 569 ccRCC samples, which were associated with different biological functions and clinical outcomes. Thereafter, the m6A score was constructed using m6A-associated signature genes to accurately exploit the m6A modification patterns within individual tumors. The m6A score was further demonstrated to be noticeably related to ccRCC prognosis. In addition, the m6A score was found to be strongly correlated with tumor mutational burden (TMB), microsatellite instability, immune infiltration, immune checkpoint expression, and immunotherapy response, which was also validated in the pan-cancer analyses. Our findings thoroughly elucidated that m6A modification contributes to tumor microenvironment immune-infiltrating characteristics and prognosis in ccRCC. Assessing the m6A modification patterns of individual patients with ccRCC will offer novel insights into TME infiltration and help develop more effective treatment strategies.

Elevated SNRPA1, as a Promising Predictor Reflecting Severe Clinical Outcome via Effecting Tumor Immunity for ccRCC, Is Related to Cell Invasion, Metastasis, and Sunitinib Sensitivity

Clear cell renal cell carcinoma (ccRCC) is the most common subtype of renal carcinoma and is associated with poor prognosis and notorious for its immune dysfunction characteristic. SNRPA1 is a spliceosome component responsible for processing pre-mRNA into mRNA, while the biological effect of SNRPA1 in ccRCC remains elusive. The aim of this study was to decipher the effect of SNRPA1 on clinical effect and tumor immunity for ccRCC patients. Multi-databases were collected to evaluate the different expression, prognostic value, DNA methylation, tumor immune microenvironment, and drug sensitivity of SNRPA1 on ccRCC. IHC was utilized to validate the expression and prognostic value of SNRPA1 in ccRCC patients from the SMMU cohort. The knockout expression of SNRPA by sgRNA plasmid inhibited the cell proliferation, migration, and metastasis ability and significantly increased the sensitivity of sunitinib treatment. In addition, we explored the role of SNRPA1 in pan-cancer level. The results indicated that SNRPA1 was differentially expressed in most cancer types. SNRPA1 may significantly influence the prognosis of multiple cancer types, especially in ccRCC patients. Notably, SNRPA1 was significantly correlated with immune cell infiltration and immune checkpoint inhibitory genes. In addition, the aggressive and immune inhibitory effects shown in SNRPA1 overexpression and the effect of SNRPA1 on ccRCC cell line invasion, metastasis, and drug sensitivity in vitro were observed. Moreover, SNRPA1 was related to Myc, MTORC, G2M, E2F, and DNA repair pathways in various cancer types. In all, SNRPA1 may prove to be a new biomarker for prognostic prediction, effect tumor immunity, and drug susceptibility in ccRCC.

Prognostic Value of Neoantigen Load in Immune Checkpoint Inhibitor Therapy for Cancer

Immune checkpoint inhibitors (ICIs) have made great progress in the field of tumors and have become a promising direction of tumor treatment. With advancements in genomics and bioinformatics technology, it is possible to individually analyze the neoantigens produced by somatic mutations of each patient. Neoantigen load (NAL), a promising biomarker for predicting the efficacy of ICIs, has been extensively studied. This article reviews the research progress on NAL as a biomarker for predicting the anti-tumor effects of ICI. First, we provide a definition of NAL, and summarize the detection methods, and their relationship with tumor mutation burden. In addition, we describe the common genomic sources of NAL. Finally, we review the predictive value of NAL as a tumor prediction marker based on various clinical studies. This review focuses on the predictive ability of NAL’s ICI efficacy against tumors. In melanoma, lung cancer, and gynecological tumors, NAL can be considered a predictor of treatment efficacy. In contrast, the use of NAL for urinary system and liver tumors requires further research. When NAL alone is insufficient to predict efficacy, its combination with other indicators can improve prediction efficiency. Evaluating the response of predictive biomarkers before the treatment initiation is essential for guiding the clinical treatment of cancer. The predictive power of NAL has great potential; however, it needs to be based on more accurate sequencing platforms and technologies.

Neoantigen Cancer Vaccines: Generation, Optimization, and Therapeutic Targeting Strategies

Alternatives to conventional cancer treatments are highly sought after for high-risk malignancies that have a poor response to established treatment modalities. With research advancing rapidly in the past decade, neoantigen-based immunotherapeutic approaches represent an effective and highly tolerable therapeutic option. Neoantigens are tumor-specific antigens that are not expressed in normal cells and possess significant immunogenic potential. Several recent studies have described the conceptual framework and methodologies to generate neoantigen-based vaccines as well as the formulation of appropriate clinical trials to advance this approach for patient care. This review aims to describe some of the key studies in the recent literature in this rapidly evolving field and summarize the current advances in neoantigen identification and selection, vaccine generation and delivery, and the optimization of neoantigen-based therapeutic strategies, including the early data from pivotal clinical studies.

Expression of immune-related genes as prognostic biomarkers for the assessment of osteosarcoma clinical outcomes

Cancer immunotherapy is a promising therapeutic approach, but the prognostic value of immune-related genes in osteosarcoma (OS) is unknown. Here, Target-OS RNA-seq data were analyzed to detect differentially expressed genes (DEGs) between OS subgroups, followed by functional enrichment analysis. Cox proportional risk regression was performed for each immune-related gene, and a risk score model to predict the prognosis of patients with OS was constructed. The risk scores were calculated using the risk signature to divide the training set into high-risk and low-risk groups, and validation was performed with GSE21257. We identified two immune-associated clusters, C1 and C2. C1 was closely related to immunity, and the immune score was significantly higher in C1 than in C2. Furthermore, we validated 6 immune cell hub genes related to the prognosis of OS: CD8A, KIR2DL1, CD79A, APBB1IP, GAL, and PLD3. Survival analysis revealed that the prognosis of the high-risk group was significantly worse than that of the low-risk group. We also explored whether the 6-gene prognostic risk model was effective for survival prediction. In conclusion, the constructed a risk score model based on immune-related genes and the survival of patients with OS could be a potential tool for targeted therapy.

Characterization of Molecular Heterogeneity Associated With Tumor Microenvironment in Clear Cell Renal Cell Carcinoma to Aid Immunotherapy

Clear cell renal cell carcinoma (ccRCC) is the most common type of kidney cancer and has strong immunogenicity. A systematically investigation of the tumor microenvironment (TME) in ccRCC could contribute to help clinicians develop personalized treatment and facilitate clinical decision-making. In this study, we analyzed the immune-related subtype of ccRCC on the basis of immune-related gene expression data in The Cancer Genome Atlas (TCGA, N = 512) and E-MTAB-1980 (N = 101) dataset, respectively. As a result, two subtypes (C1 and C2) were identified by performing non-negative matrix factorization clustering. Subtype C1 was characterized by increased advance ccRCC cases and immune-related pathways. A higher immune score, stromal score, TMB value, Tumor Immune Dysfunction and Exclusion (TIDE) prediction score, and immune checkpoint genes expression level were also observed in C1. In addition, the C1 subtype might benefit from chemotherapy and immunotherapy. The patients in subtype C2 had more metabolism-related pathways, higher tumor purity, and a better prognosis. Moreover, some small molecular compounds for the treatment of ccRCC were identified between the two subtypes by using the Connectivity Map (CMap) database. Finally, we constructed and validated an immune-related (IR) score to evaluate immune modification individually. A high IR score corresponded to a favorable prognosis compared to a low IR score, while more advanced tumor stage and grade cases were enriched in the low IR score group. The two IR score groups also showed a distinct divergence among immune status, TME, and chemotherapy. The external validation dataset (E-MTAB-1980) and another immunotherapy cohort (IMvigor 210) demonstrated that patients in the high IR score group had a significantly prolonged survival time and clinical benefits compared to the low IR score group. Together, characterization of molecular heterogeneity and IR signature may help develop new insights into the TME of ccRCC and provide new strategies for personalized treatment.

Development and validation of a PBRM1-associated immune prognostic model for clear cell renal cell carcinoma

Alteration in the polybromo‐1 (PBRM1) protein encoding gene PBRM1 is the second most frequent mutation in clear cell renal cell carcinoma (ccRCC). It causes a series of changes in the tumorigenesis, progression, prognosis, and immune response of ccRCC patients. This study explored the PBRM1‐associated immunological features and identified the immune‐related genes (IRGs) linked to PBRM1 mutation using bioinformatics methods. A total of 37 survival IRGs associated with PBRM1 mutation in ccRCC patients were identified. To further explore the role of these IRGs in ccRCC and their association with immune status, eight IRGs with remarkable potential as individual targets were selected. An immune model that was constructed showed good performance in stratifying patients into different subgroups, showing clinical application potential compared to traditional clinical factors. Patients in the high‐risk group were inclined to have more advanced stage and higher grade tumors with node metastasis, distant metastasis, and poorer prognosis. Furthermore, these patients had high percentages of regulatory T cells, follicular helper T cells, and M0 macrophages and exhibited high expression levels of immune checkpoints proteins, such as CTLA‐4, PD‐1, LAG‐3, TIGIT, and CD47. Finally, a nomogram integrating the model and clinical factors for clinical application showed a more robust predictive performance for prognosis. The prediction model associated with PBRM1 mutation status and immunity can serve as a promising tool to stratify patients depending upon their immune status, thus facilitating immunotherapy in the future.

Tumor-infiltrating CD8+ T cells recognize a heterogeneously expressed functional neoantigen in clear cell renal cell carcinoma

Immune checkpoint inhibitors (ICIs) are used in cancer immunotherapy to block programmed death-1 and cytotoxic T-lymphocyte antigen 4, but the response rate for ICIs is still low and tumor cell heterogeneity is considered to be responsible for resistance to immunotherapy. Tumor-infiltrating lymphocytes (TILs) have an essential role in the anti-tumor effect of cancer immunotherapy; however, the specificity of TILs in renal cell carcinoma (RCC) is elusive. In this study, we analyzed a 58-year-old case with clear cell RCC (ccRCC) with the tumor showing macroscopic and microscopic heterogeneity. The tumor was composed of low-grade and high-grade ccRCC. A tumor cell line (1226 RCC cells) and TILs were isolated from the high-grade ccRCC lesion, and a TIL clone recognized a novel neoantigen peptide (YVVPGSPCL) encoded by a missense mutation of the tensin 1 (TNS1) gene in a human leukocyte antigen-C*03:03-restricted fashion. The TNS1 gene mutation was not detected in the low-grade ccRCC lesion and the TIL clone did not recognized low-grade ccRCC cells. The missense mutation of TNS1 encoding the S1309Y mutation was found to be related to cell migration by gene over-expression. These findings suggest that macroscopically and microscopically heterogenous tumors might show heterogenous gene mutations and reactivity to TILs.

Integrated analysis of immune-related gene subtype and immune index for immunotherapy in clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most common type of renal cell carcinoma (RCC) with high immunogenicity. Research on immune-related gene (IRG) is of great significance in ccRCC in identifying new therapeutic targets and improving patient prognosis. In this study, the IRG patterns of ccRCC were investigated and correlated these patterns with tumor microenvironment infiltrating characteristics in immunotherapy. Moreover, an IRG score was constructed to quantify the pattern of individual tumors through the principal component analysis algorithm. Two distinct molecular subtypes (C1 and C2) were identified based on the IRGs expression profile. Subtype C1 was characterized with significantly high level of immune-checkpoint, immune score, stromal score, showed high drug sensitivity in Sorafenib, Sunitinib, Cisplatin, Vinblastine, Vinorelbine, Vorinostat, and Gemcitabine. Cytokine-cytokine receptor pathway, chemokine signaling pathway, and JAK signaling pathways were found enriched in the subtype C1 account for the poor prognosis. Subtype C2 was linked to a better survival outcome. By using the Connective Map database, subtype specific small molecular drugs identified that could facilitate the treatment of ccRCC patients. In addition, A immune index that used to evaluated the immune modification patterns and further validated in the other types RCC dataset, such as papillary renal cell carcinoma (pRCC) and chromophobe renal cell carcinoma (chRCC). Together, this study identified two distinct molecular subtypes with immune index, aid to the treatment of ccRCC and enhancing our cognition of the tumor microenvironment infiltration characterization in ccRCC immunotherapy.

Landscape of immune cell infiltration in clear cell renal cell carcinoma to aid immunotherapy

The tumor microenvironment, comprised of tumor cells and tumor-infiltrating immune cells, is closely associated with the clinical outcome of clear cell renal cell carcinoma (ccRCC) patients. However, the landscape of immune infiltration in ccRCC has not been fully elucidated. Herein, we applied multiple computational methods and various datasets to reveal the immune infiltrative landscape of ccRCC patients. The tumor immune infiltration (TII) levels of 525 ccRCC patients using a single-sample gene were examined and further categorized into immune infiltration subgroups. The TII score was characterized by distinct clinical traits and showed a significant divergence based on gender, grade, and stage. A high TII score was associated with the ERBB signaling pathway, the TGF-β signaling pathway, and the MTOR signaling pathway, as well as a better prognosis. Furthermore, patients with high TII scores exhibited greater sensitivity to pazopanib. The low TII score was characterized by a high immune infiltration level of CD8+ T cells, T follicular helper cells, and regulatory T cells (Tregs). Moreover, the immune check point genes, including CTLA-4, LAG3, PD-1, and IDO1, presented a high expression level in the low TII score group. Patients in the high TII score group demonstrated significant therapeutic advantages and clinical benefits. The findings in this study have the potential to assist in the strategic design of immunotherapeutic treatments for ccRCC.

Renal cell carcinoma pathology in 2021: 'new need for renal cancer immune profiling'

PURPOSE OF REVIEW

The aim of this review is to outline characteristics of the renal cell carcinoma (RCC) tumor immune microenvironment (TIME), the potential impact of tumor intrinsic alterations on the TIME and the value of metastatic tissue assessment in this context.

RECENT FINDINGS

According to the latest European Association of Urology, European Society for Medical Oncology and National Comprehensive Cancer Network guidelines immune checkpoint inhibition represents a new core treatment strategy in advanced clear cell RCC (ccRCC). Despite its success, the prognosis of many RCC patients remains unsatisfactory most likely because of resistance mechanisms within the TIME. Moreover, most studies assess the primary tumor even though the advanced metastatic disease is targeted. Overall, metastatic RCC has hardly been investigated. First insights into the complexity of the genomic and immune landscape in RCC were recently provided. The functional impact of tumor intrinsic alterations on the TIME has just been described potentially contributing to therapy response in RCC.

SUMMARY

The complexity of the RCC TIME and its potential interdependence with tumor intrinsic alterations has only just been recognized. A deeper understanding of the TIME may reveal predictive and prognostic biomarkers long-awaited in RCC, improve RCC patient stratification and could possibly be most instructive if assessed in metastatic tissue.

Differentiation and Regulation of TH Cells: A Balancing Act for Cancer Immunotherapy

Current success of immunotherapy in cancer has drawn attention to the subsets of T_H cells in the tumor which are critical for activation of anti-tumor response either directly by themselves or by stimulating cytotoxic T cell activity. However, presence of immunosuppressive pro-tumorigenic T_H subsets in the tumor milieu further contributes to the complexity of regulation of T_H cell-mediated immune response. In this review, we present an overview of the multifaceted positive and negative effects of T_H cells, with an emphasis on regulation of different T_H cell subtypes by various immune cells, and how a delicate balance of contradictory signals can influence overall success of cancer immunotherapy. We focus on the regulatory network that encompasses dendritic cell-induced activation of CD4⁺ T_H1 cells and subsequent priming of CD8⁺ cytotoxic T cells, along with intersecting anti-inflammatory and pro-tumorigenic T_H2 cell activity. We further discuss how other tumor infiltrating immune cells such as immunostimulatory T_H9 and T_fh cells, immunosuppressive T_reg cells, and the duality of T_H17 function contribute to tip the balance of anti- vs pro-tumorigenic T_H responses in the tumor. We highlight the developing knowledge of CD4⁺ T_H1 immune response against neoantigens/oncodrivers, impact of current immunotherapy strategies on CD4⁺ T_H1 immunity, and how opposing action of T_H cell subtypes can be explored further to amplify immunotherapy success in patients. Understanding the nuances of CD4⁺ T_H cells regulation and the molecular framework undergirding the balancing act between anti- vs pro-tumorigenic T_H subtypes is critical for rational designing of immunotherapies that can bypass therapeutic escape to maximize the potential of immunotherapy.

Beyond Tumor Mutation Burden: Tumor Neoantigen Burden as a Biomarker for Immunotherapy and Other Types of Therapy

Immunotherapy has significantly improved the clinical outcome of patients with cancer. However, the immune response rate varies greatly, possibly due to lack of effective biomarkers that can be used to distinguish responders from non-responders. Recently, clinical studies have associated high tumor neoantigen burden (TNB) with improved outcomes in patients treated with immunotherapy. Therefore, TNB has emerged as a biomarker for immunotherapy and other types of therapy. In the present review, the potential application of TNB as a biomarker was evaluated. The methods of neoantigen prediction were summarized and the mechanisms involved in TNB were investigated. The impact of high TNB and increased number of infiltrating immune cells on the efficacy of immunotherapy was also addressed. Finally, the future challenges of TNB were discussed.

Comprehensive characterization of alternative splicing in renal cell carcinoma

Irregular splicing was associated with tumor formation and progression in renal cell carcinoma (RCC) and many other cancers. By using splicing data in the TCGA SpliceSeq database, RCC subtype classification was performed and splicing features and their correlations with clinical course, genetic variants, splicing factors, pathways activation and immune heterogeneity were systemically analyzed. In this research, alternative splicing was found useful for classifying RCC subtypes. Splicing inefficiency with upregulated intron retention and cassette exon was associated with advanced conditions and unfavorable overall survival of patients with RCC. Splicing characteristics like splice site strength, guanine and cytosine content and exon length may be important factors disrupting splicing balance in RCC. Other than cis-acting and trans-acting regulation, alternative splicing also differed in races and tissue types and is also affected by mutation conditions, pathway settings and the response to environmental changes. Severe irregular splicing in tumor not only indicated terrible intra-cellular homeostasis, but also changed the activity of cancer-associated pathways by different splicing effects including isoforms switching and expression regulation. Moreover, irregular splicing and splicing-associated antigens were involved in immune reprograming and formation of immunosuppressive tumor microenvironment. Overall, we have described several clinical and molecular features in RCC splicing subtypes, which may be important for patient management and targeting treatment.

Advances in the development of personalized neoantigen-based therapeutic cancer vaccines

Within the past decade, the field of immunotherapy has revolutionized the treatment of many cancers with the development and regulatory approval of various immune-checkpoint inhibitors and chimeric antigen receptor T cell therapies in diverse indications. Another promising approach to cancer immunotherapy involves the use of personalized vaccines designed to trigger de novo T cell responses against neoantigens, which are highly specific to tumours of individual patients, in order to amplify and broaden the endogenous repertoire of tumour-specific T cells. Results from initial clinical studies of personalized neoantigen-based vaccines, enabled by the availability of rapid and cost-effective sequencing and bioinformatics technologies, have demonstrated robust tumour-specific immunogenicity and preliminary evidence of antitumour activity in patients with melanoma and other cancers. Herein, we provide an overview of the complex process that is necessary to generate a personalized neoantigen vaccine, review the types of vaccine-induced T cells that are found within tumours and outline strategies to enhance the T cell responses. In addition, we discuss the current status of clinical studies testing personalized neoantigen vaccines in patients with cancer and considerations for future clinical investigation of this novel, individualized approach to immunotherapy.

Advances in the development of personalized neoantigen-based therapeutic cancer vaccines

Within the past decade, the field of immunotherapy has revolutionized the treatment of many cancers with the development and regulatory approval of various immune-checkpoint inhibitors and chimeric antigen receptor T cell therapies in diverse indications. Another promising approach to cancer immunotherapy involves the use of personalized vaccines designed to trigger de novo T cell responses against neoantigens, which are highly specific to tumours of individual patients, in order to amplify and broaden the endogenous repertoire of tumour-specific T cells. Results from initial clinical studies of personalized neoantigen-based vaccines, enabled by the availability of rapid and cost-effective sequencing and bioinformatics technologies, have demonstrated robust tumour-specific immunogenicity and preliminary evidence of antitumour activity in patients with melanoma and other cancers. Herein, we provide an overview of the complex process that is necessary to generate a personalized neoantigen vaccine, review the types of vaccine-induced T cells that are found within tumours and outline strategies to enhance the T cell responses. In addition, we discuss the current status of clinical studies testing personalized neoantigen vaccines in patients with cancer and considerations for future clinical investigation of this novel, individualized approach to immunotherapy.

Personalized neoantigen-based immunotherapy for advanced collecting duct carcinoma: case report

BACKGROUND

Collecting duct carcinoma (CDC) of the kidney is a rare and highly aggressive malignant tumor with the worst prognosis among all renal cancers. Nevertheless, the first-line treatments, including chemotherapy and target therapy, usually show poor response to CDC. Recent studies have suggested that immunotherapy targeting personal tumor-specific neoantigens could be a promising strategy for several solid cancers. However, whether it has therapeutic potential in CDC remains unclear.

CASE PRESENTATION

Here, we report a case of an Asian patient who underwent personalized neoantigen-based immunotherapy. The patient was diagnosed with metastatic CDC and suffered extensive tumor progression following sorafenib treatment. Based on the patient's own somatic mutational profile, a total of 13 neoantigens were identified and corresponding long-peptide vaccine and neoantigen-reactive T cells (NRTs) were prepared. After six cycles of neoantigen-based vaccination and T-cell immunotherapy, the patient was reported with stable disease status in tumor burden and significant alleviation of bone pain. Ex vivo interferon-γ enzyme-linked immunospot assay proved the reactivity to 12 of 13 neoantigens in peripheral blood mononuclear cells collected after immunotherapy, and the preferential reactivity to mutant peptides compared with corresponding wild-type peptides was also observed for 3 of the neoantigens. Surprisingly, biopsy sample collected from CDC sites after 3 months of immunotherapy showed decreased mutant allele frequency corresponding to 92% (12/13) of the neoantigens, indicating the elimination of tumor cells carrying these neoantigens.

CONCLUSIONS

Our case report demonstrated that the combined therapy of neoantigen peptide vaccination and NRT cell infusion showed certain efficacy in this CDC case, even when the patient carried only a relatively low tumor mutation burden. These results indicated that the personalized neoantigen-based immunotherapy was a promising new strategy for advanced CDC.

TRIAL REGISTRATION NUMBER

ChiCTR1800017836.

Underlying mechanisms and drug intervention strategies for the tumour microenvironment

Cancer occurs in a complex tissue environment, and its progression depends largely on the tumour microenvironment (TME). The TME has a highly complex and comprehensive system accompanied by dynamic changes and special biological characteristics, such as hypoxia, nutrient deficiency, inflammation, immunosuppression and cytokine production. In addition, a large number of cancer-associated biomolecules and signalling pathways are involved in the above bioprocesses. This paper reviews our understanding of the TME and describes its biological and molecular characterization in different stages of cancer development. Furthermore, we discuss in detail the intervention strategies for the critical points of the TME, including chemotherapy, targeted therapy, immunotherapy, natural products from traditional Chinese medicine, combined drug therapy, etc., providing a scientific basis for cancer therapy from the perspective of key molecular targets in the TME.

Roles of the Dynamic Tumor Immune Microenvironment in the Individualized Treatment of Advanced Clear Cell Renal Cell Carcinoma

Immune checkpoint inhibitors (ICIs) are currently a first-line treatment option for clear cell renal cell carcinoma (ccRCC). However, recent clinical studies have shown that a large number of patients do not respond to ICIs. Moreover, only a few patients achieve a stable and durable response even with combination therapy based on ICIs. Available studies have concluded that the response to immunotherapy and targeted therapy in patients with ccRCC is affected by the tumor immune microenvironment (TIME), which can be manipulated by targeted therapy and tumor genomic characteristics. Therefore, an in-depth understanding of the dynamic nature of the TIME is important for improving the efficacy of immunotherapy or combination therapy in patients with advanced ccRCC. Here, we explore the possible mechanisms by which the TIME affects the efficacy of immunotherapy and targeted therapy, as well as the factors that drive dynamic changes in the TIME in ccRCC, including the immunomodulatory effect of targeted therapy and genomic changes. We also describe the progress on novel therapeutic modalities for advanced ccRCC based on the TIME. Overall, this review provides valuable information on the optimization of combination therapy and development of individualized therapy for advanced ccRCC.

High Tumor Mutation Burden and Other Immunotherapy Response Predictors in Breast Cancers: Associations and Therapeutic Opportunities

BACKGROUND

The recent development of effective immunotherapies with immune checkpoint inhibitors for the treatment of cancer has rekindled the interest for the immune system and its activation for an anti-cancer response. At the same time, it has become evident that not all types of cancers respond equally to these treatments, and even within the same tumor type only a subset of patients derive clinical benefit. Biomarkers predictive of response to immunotherapy have been sought and in certain occasions incorporated in the indication for treatment. These include expression of PD-L1 and defects in DNA mismatch repair (MMR).

OBJECTIVE

Tumor mutation burden (TMB) has been associated with response to immune checkpoint inhibitors. The current investigation examines TMB as a biomarker of response to immunotherapy in breast cancer.

PATIENTS AND METHODS

Publicly available data from the breast cancer study of The Cancer Genome Atlas (TCGA) and the METABRIC study were analyzed. Parameters examined included the TMB and specific mutations that may impact on TMB. In addition, correlations with breast cancer sub-types were investigated.

RESULTS

The percentage of breast cancers with high TMB (more than 192 mutations per sample) was low (3.5-4.6%) in luminal and triple-negative cancers and higher (14.1%) in the HER2-positive subset. Almost all cancers with high TMB had defects in MMR proteins or the replicative polymerases POLE and POLD1.

CONCLUSIONS

Small sub-sets of breast cancers with high TMB exist and may present an opportunity for effective immunotherapeutic targeting.

Comprehensive Analysis of CDCAs Methylation and Immune Infiltrates in Hepatocellular Carcinoma

Background

As essential components of cycle growth, the cell division cycle-associated family genes (CDCAs) have crucial roles in tumor development and progression, especially in hepatocellular carcinoma (HCC). However, due to the tumor heterogeneity of HCC, little is known about the methylation variability of CDCAs in mediating phenotypic changes (e.g., immune infiltrates) in HCC. Presently, we aim to comprehensively explore the expression and prognosis of CDCAs methylation with regard to immune infiltrates of HCC.

Methods

We first identified the correlating differentially expressed genes (co-DEGs) among 19 different types of cancer cohorts (a total of 7,783 patients) and then constructed the weighted gene co-expressed and co-methylated networks. Applying the clustering analysis, significant modules of DEGs including CDCAs were selected and their functional bioinformatics analyses were performed. Besides, using DiseaseMeth and TIMER, the correlation between the methylation levels of CDCAs and tumor immune infiltrates was also analyzed. In final, to assess the influence of CDCAs methylation on clinical prognosis, Kaplan-Meier and Cox regression analysis were carried out.

Result

A total of 473 co-DEGs are successfully identified, while seven genes of CDCAs (CDCA1–3 and CDCA5–8) have significant over-expression in HCC. Co-expressed and co-methylated networks reveal the strong positive correlations in mRNA expression and methylation levels of CDCAs. Besides, the biological enrichment analysis of CDCAs demonstrates that they are significantly related to the immune function regulation of infiltrating immune cells in HCC. Also, the methylation analysis of CDCAs depicts the strong association with the tumor immunogenicity, i.e., low-methylation of CDCA1, CDCA2, and CDCA8 dramatically reduced the immune infiltrate levels of T cells and cytotoxic lymphocytes. Additionally, CDCA1–6 and CDCA8 with low-methylation levels significantly deteriorate the overall survival of patients in HCC.

Conclusions

The co-expressed and co-methylated gene networks of CDCAs show a powerful association with immune function regulation. And the methylation levels of CDCAs suggesting the prognostic value and infiltrating immune differences could be a novel and predictive biomarker for the response of immunotherapy.

Benchmarking HLA genotyping and clarifying HLA impact on survival in tumor immunotherapy

Human leukocyte antigen (HLA) genotyping gains intensive attention due to its critical role in cancer immunotherapy. It is still a challenging issue to generate reliable HLA genotyping results through in silico tools. In addition, the survival impact of HLA alleles in tumor prognosis and immunotherapy remains controversial. In this study, the benchmarking of HLA genotyping on TCGA is performed and a ‘Gun‐Bullet’ model which helps to clarify the survival impact of HLA allele is presented. The performance of HLA class I genotyping is generally better than class II. POLYSOLVER, OptiType, and xHLA perform generally better at HLA class I calling with an accuracy of 0.954, 0.949, and 0.937, respectively. HLA‐HD obtained the highest accuracy of 0.904 on HLA class II alleles calling. Each HLA genotyping tool displayed specific error patterns. The ensemble HLA calling from the top‐3 tools is superior to any individual one. HLA alleles show distinct survival impact among cancers. Cytolytic activity (CYT) was proposed as the underlying mechanism to interpret the survival impact of HLA alleles in the ‘Gun‐Bullet’ model for fighting cancer. A strong HLA allele plus a high tumor mutation burden (TMB) could stimulate intensive immune CYT, leading to extended survival. We established an up to now most reliable TCGA HLA benchmark dataset, composing of concordance alleles generated from eight prevalently used HLA genotyping tools. Our findings indicate that reliable HLA genotyping should be performed based on concordance alleles integrating multiple tools and incorporating TMB background with HLA genotype, which helps to improve the survival prediction compared to HLA genotyping alone.

Identification of WDFY3 Neoantigens as Prognostic Markers in Longterm Survivors of Extrahepatic Cholangiocarcinoma

BACKGROUND

Neoantigens are newly formed antigens that have not been previously recognized by the immune system. They may arise from altered tumor proteins that form as a result of mutations. Although neoantigens have recently been linked to antitumor immunity in long-term survivors of cancers, such as melanoma and colorectal cancer, their prognostic and immune-modulatory role in many cancer types remains undefined.

OBJECTIVE

The purpose of this study is to identify prognostic markers for long-term extrahepatic cholangiocarcinoma (EHCC) survival.

METHODS

We investigated neoantigens in EHCC, a rare, aggressive cancer with a 5-year overall survival rate lower than 10%, using a combination of whole-exome sequencing (WES), RNA sequencing (RNA-seq), computational biophysics, and immunohistochemistry.

RESULTS

Our analysis revealed a decreased neutrophil infiltration-related trend of high-quality neoantigen load with IC50 <500 nM (r=-0.445, P=0.043). Among 24 EHCC patients examined, we identified four long-term survivors with WDFY3 neoantigens and none with WDFY3 neoantigens in the short-term survivors. The WDFY3 neoantigens are associated with a lower infiltration of neutrophils (p=0.013), lower expression of CCL5 (p=0.025), CXCL9 (p=0.036) and TIGIT (p=0.016), and less favorable prognosis (p=0.030). In contrast, the prognosis was not significantly associated with tumor mutation burden, neoantigen load, or immune cell infiltration.

CONCLUSION

We suggest that the WDFY3 neoantigens may affect prognosis by regulating antitumor immunity and that the WDFY3 neoantigens may be harnessed as potential targets for immunotherapy of EHCC.

Selecting Target Antigens for Cancer Vaccine Development

One of the principal goals of cancer immunotherapy is the development of efficient therapeutic cancer vaccines that are able to elicit an effector as well as memory T cell response specific to tumor antigens. In recent years, the attention has been focused on the personalization of cancer vaccines. However, the efficacy of therapeutic cancer vaccines is still disappointing despite the large number of vaccine strategies targeting different tumors that have been evaluated in recent years. While the preclinical data have frequently shown encouraging results, clinical trials have not provided satisfactory data to date. The main reason for such failures is the complexity of identifying specific target tumor antigens that should be unique or overexpressed only by the tumor cells compared to normal cells. Most of the tumor antigens included in cancer vaccines are non-mutated overexpressed self-antigens, eliciting mainly T cells with low-affinity T cell receptors (TCR) unable to mediate an effective anti-tumor response. In this review, the target tumor antigens employed in recent years in the development of therapeutic cancer vaccine strategies are described, along with potential new classes of tumor antigens such as the human endogenous retroviral elements (HERVs), unconventional antigens, and/or heteroclitic peptides.

Neoantigen-based immunotherapy in pancreatic ductal adenocarcinoma (PDAC)

Neoantigens generated in neoplasms are a type of protein completely absent in healthy tissues. Therefore, anti-tumor immunity targeting neoantigens is highly specific, which provides an optional approach to boost tumor immunotherapy. Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignancies in humans, with few efficient treatments to improve its prognosis. Therefore, immunotherapies reinforced by neoantigen-based strategies should be considered. In PDAC, the mutational burden is intermediate compared with other common malignancies, while the naturally formed tumor immunity is significantly inferior. Moreover, the high mutation load in PDAC correlates with a poor clinical prognosis, although the combination of a large mutation repertoire and competent T cell population is indispensable for long-term survival. In clinical practice, three strategies have been mainly used: peptide or tumor cell vaccines, neo-epitope-coding nucleotide vaccines, and dendritic cell vaccines. However, three major problems remain to be addressed, including (1) highly personalized protocols after sampling, (2) insufficient neoantigen quantity, and (3) ineffective immunotherapy of PDAC. In summary, neoantigen-based therapy of PDAC is increasing and the treatment methods are accompanied by great challenges. Currently, extensive development is needed for effective neoantigen-based therapy.

Unique TP53 neoantigen and the immune microenvironment in long-term survivors of Hepatocellular carcinoma

Neoantigens are T-cell antigens derived from protein-coding mutations in tumor cells. Although neoantigens have recently been linked to anti-tumor immunity in long-term survivors of cancers such as melanoma, their prognostic and immune-modulatory role in many cancer types remain unexplored. We investigate neoantigens in hepatocellular carcinoma (HCC) through a combination of whole exome sequencing (WES), RNA sequencing (RNA-seq), computational bioinformation, and immunohistochemistry. Our analysis reveals that patients carried with TP53 neoantigen have a longer overall survival than others (p = 0.0371) and they showed higher Immune score (p = 0.0441), higher cytotoxic lymphocytes infiltration (p = 0.0428), and higher CYT score (p = 0.0388). In contrast, the prognosis is not associated with TMB and neoantigen load. Our study draws a preliminary conclusion that it is not TMB or neoantigen load but the TP53 specific neoantigen is related to overall survival of HCC patients. We suggest that the TP53 neoantigen may affect prognosis by regulating anti-tumor immunity and that the TP53 neoantigen may be harnessed as potential targets for immunotherapies of HCC.

Progress in Neoantigen Targeted Cancer Immunotherapies

Immunotherapies that harness the immune system to kill cancer cells have showed significant therapeutic efficacy in many human malignancies. A growing number of studies have highlighted the relevance of neoantigens in recognizing cancer cells by intrinsic T cells. Cancer neoantigens are a direct consequence of somatic mutations presenting on the surface of individual cancer cells. Neoantigens are fully cancer-specific and exempt from central tolerance. In addition, neoantigens are important targets for checkpoint blockade therapy. Recently, technological innovations have made neoantigen discovery possible in a variety of malignancies, thus providing an impetus to develop novel immunotherapies that selectively enhance T cell reactivity for the destruction of cancer cells while leaving normal tissues unharmed. In this review, we aim to introduce the methods of the identification of neoantigens, the mutational patterns of human cancers, related clinical trials, neoantigen burden and sensitivity to immune checkpoint blockade. Moreover, we focus on relevant challenges of targeting neoantigens for cancer treatment.

Immune Cell Infiltration and Identifying Genes of Prognostic Value in the Papillary Renal Cell Carcinoma Microenvironment by Bioinformatics Analysis

Papillary renal cell carcinoma (PRCC) is one of the most common histological subtypes of renal cell carcinoma. Type 1 and type 2 PRCC are reported to be clinically and biologically distinct. However, little is known about immune infiltration and the expression patterns of immune-related genes in these two histologic subtypes, thereby limiting the development of immunotherapy for PRCC. Thus, we analyzed the expression of 22 immune cells in type 1 and type 2 PRCC tissues by combining The Cancer Genome Atlas (TCGA) database with the ESTIMATE and CIBERSORT algorithms. Subsequently, we extracted a list of differentially expressed genes associated with the immune microenvironment. Multichip mRNA microarray data sets for PRCC were downloaded from the Gene Expression Omnibus (GEO) to further validate our findings. We found that the immune scores and stromal scores were associated with overall survival in patients with type 2 PRCC rather than type 1 PRCC. Tumor-infiltrating M1 and M2 macrophages could predict the clinical outcome by reflecting the host's immune capacity against type 2 PRCC. Furthermore, CCL19/CCR7, CXCL12/CXCR4, and CCL20/CCR6 were shown to be potential new targets for tumor gene therapy in type 2 PRCC. Our findings provide valuable resources for improving immunotherapy for PRCC.

Killing the "BAD": Challenges for immunotherapy in pancreatic cancer

Cancer regression often fails after systemic immune activation, especially for solid tumors due to their local immunosuppressive microenvironments. Among these, the pancreatic cancer microenvironment is unique and an important reason for resistance to anti-cancer treatments that include immunotherapy. In this review, the three main "BAD" characteristics that create and maintain this immunosuppressive microenvironment are discussed for effector T cells: Barriers to overcome, Attraction problems, and their Disabilities. These inhibit both effector T-cell activation and infiltration, reducing immunotherapy effectiveness. Combination approaches for killing the "BAD" aim to normalize the tumor microenvironment and are recommended to enhance anti-cancer immune-system efficacy in pancreatic cancer.

Tumor-Infiltrating T Cells From Clear Cell Renal Cell Carcinoma Patients Recognize Neoepitopes Derived From Point and Frameshift Mutations

Mutation-derived neoantigens are important targets for T cell-mediated reactivity toward tumors and, due to their unique tumor expression, an attractive target for immunotherapy. Neoepitope-specific T cells have been detected across a number of solid cancers with high mutational burden tumors, but neoepitopes have been mostly selected from single nucleotide variations (SNVs), and little focus has been given to neoepitopes derived from in-frame and frameshift indels, which might be equally important and potentially highly immunogenic. Clear cell renal cell carcinomas (ccRCCs) are medium-range mutational burden tumors with a high pan-cancer proportion of frameshift mutations. In this study, the mutational landscape of tumors from six RCC patients was analyzed by whole-exome sequencing (WES) of DNA from tumor fragments (TFs), autologous tumor cell lines (TCLs), and tumor-infiltrating lymphocytes (TILs, germline reference). Neopeptides were predicted using MuPeXI, and patient-specific peptide–MHC (pMHC) libraries were created for all neopeptides with a rank score < 2 for binding to the patient's HLAs. T cell recognition toward neoepitopes in TILs was evaluated using the high-throughput technology of DNA barcode-labeled pMHC multimers. The patient-specific libraries consisted of, on average, 258 putative neopeptides (range, 103–397, n = 6). In four patients, WES was performed on two different sources (TF and TCL), whereas in two patients, WES was performed only on TF. Most of the peptides were predicted from both sources. However, a fraction was predicted from one source only. Among the total predicted neopeptides, 16% were derived from frameshift indels. T cell recognition of 52 neoepitopes was detected across all patients (range, 4–18, n = 6) and spanning two to five HLA restrictions per patient. On average, 21% of the recognized neoepitopes were derived from frameshift indels (range, 0–43%, n = 6). Thus, frameshift indels are equally represented in the pool of immunogenic neoepitopes as SNV-derived neoepitopes. This suggests the importance of a broad neopeptide prediction strategy covering multiple sources of tumor material, and including different genetic alterations. This study, for the first time, describes the T cell recognition of frameshift-derived neoepitopes in RCC and determines their immunogenic profile.

Tumor neoantigenicity assessment with CSiN score incorporates clonality and immunogenicity to predict immunotherapy outcomes

Lack of responsiveness to checkpoint inhibitors is a central problem in the modern era of cancer immunotherapy. Tumor neoantigens are critical targets of the host antitumor immune response, and their presence correlates with the efficacy of immunotherapy treatment. Many studies involving assessment of tumor neoantigens principally focus on total neoantigen load, which simplistically treats all neoantigens equally. Neoantigen load has been linked with treatment response and prognosis in some studies but not others. We developed a Cauchy-Schwarz index of Neoantigens (CSiN) score to better account for the degree of concentration of immunogenic neoantigens in truncal mutations. Unlike total neoantigen load determinations, CSiN incorporates the effect of both clonality and MHC binding affinity of neoantigens when characterizing tumor neoantigen profiles. By analyzing the clinical responses in 501 treated patients with cancer (with most receiving checkpoint inhibitors) and the overall survival of 1978 patients with cancer at baseline, we showed that CSiN scores predict treatment response to checkpoint inhibitors and prognosis in patients with melanoma, lung cancer, and kidney cancer. CSiN score substantially outperformed prior genetics-based prediction methods of responsiveness and fills an important gap in research involving assessment of tumor neoantigen burden.

Identification of an immune-related risk signature for predicting prognosis in clear cell renal cell carcinoma

Immune status affects the initiation and progression of clear cell renal cell carcinoma (ccRCC), the most common subtype of renal cell carcinoma. In this study, we identified an immune-related, five-gene signature that improves survival prediction in ccRCC. Patients were classified as high- and low-risk based on the signature risk score. Survival analysis showed differential prognosis, while principal component analysis revealed distinctly different immune phenotypes between the two risk groups. High-risk patients tended to have advanced stage, higher grade disease, and poorer prognoses. Functional enrichment analysis showed that the signature genes were mainly involved in the cytokine-cytokine receptor interaction pathway. Moreover, we found that tumors from high-risk patients had higher relative abundance of T follicular helper cells, regulatory T cells, and M0 macrophages, and higher expression of PD-1, CTLA-4, LAG3, and CD47 than low-risk patients. This suggests our gene signature may not only serve as an indicator of tumor immune status, but may be a promising tool to select high-risk patients who may benefit from immune checkpoint inhibitor therapy. Multivariate Cox regression analysis showed that the signature remained an independent prognostic factor after adjusting for clinicopathological variables, while prognostic accuracy was further improved after integrating clinical parameters into the analysis.

Immunological analyses reveal an immune subtype of uveal melanoma with a poor prognosis

Uveal melanoma is an aggressive intraocular malignancy that often exhibits low immunogenicity. Metastatic uveal melanoma samples frequently exhibit monosomy 3 or BAP1 deficiency. In this study, we used bioinformatic methods to investigate the immune infiltration of uveal melanoma samples in public datasets. We first performed Gene Set Enrichment/Variation Analyses to detect immunological pathways that are altered in tumors with monosomy 3 or BAP1 deficiency. We then conducted an unsupervised clustering analysis to identify distinct immunologic molecular subtypes of uveal melanoma. We used CIBERSORT and ESTIMATE with RNA-seq data from The Cancer Genome Atlas and the GSE22138 microarray dataset to determine the sample-level immune subpopulations and immune scores of uveal melanoma samples. The Kaplan-Meier method and log-rank test were used to assess the prognostic value of particular immune cells and genes in uveal melanoma samples. Through these approaches, we discovered uveal melanoma-specific immunologic features, which may provide new insights into the tumor microenvironment and enhance the development of immunotherapies in the future.

Harnessing Tumor Mutations for Truly Individualized Cancer Vaccines

T cells are key effectors of anticancer immunity. They are capable of distinguishing tumor cells from normal ones by recognizing major histocompatibility complex-bound cancer-specific peptides. Accumulating evidence suggests that peptides associated with T cell-mediated tumor rejection arise predominantly from somatically mutated proteins and are unique to every patient's tumor. Knowledge of an individual's cancer mutanome (the entirety of cancer mutations) allows harnessing this enormous tumor cell-specific repertoire of highly immunogenic antigens for individualized cancer vaccines. This review outlines the preclinical and clinical state of individualized cancer vaccine development and the challenges ahead.

High Somatic Mutation and Neoantigen Burden Do Not Correlate with Decreased Progression-Free Survival in HCC Patients not Undergoing Immunotherapy

Cancer genome instability leads to accumulation of mutations which may result into tumor-specific mutated “neoantigens”, not be affected by central T-cell tolerance. Such neoantigens are considered the optimal target for the patient’s anti-tumor T cell immunity as well as for personalized cancer immunotherapy strategies. However, only a minor fraction of predicted neoantigens are relevant to the clinical outcome. In the present study, a prediction algorithm was applied using datasets of RNA sequencing from all 377 Hepatocellular carcinoma (HCC) patients available at The Cancer Genome Atlas (TCGA), to predict neoantigens to be presented by each patient’s autologous HLA molecules. Correlation with patients’ survival was performed on the 115 samples for whom the exact date of death was known. A total of 30 samples were used for the training set, and 85 samples were used for the validation sets. Neither the somatic mutations nor the number nor the quality of the predicted neoantigens correlate as single parameter with survival of HCC patients who do not undergo immunotherapy treatment. Furthermore, the preferential presentation of such neoantigens in the context of one of the major histocompatibility complex MHC class I molecules does not have an impact on the survival. On the contrary, the expression of Granzyme A (GZMA) is significantly correlated with survival and, in the context of high GZMA, a direct correlation between number and quality of neoantigens with survival is observed. This is in striking contrast to results described in cancer patients undergoing immunotherapy, in which a strong correlation between Tumor Mutational Burden (TMB), number of predicted neoantigens and survival has been reported.

Integrated Proteogenomic Characterization of Clear Cell Renal Cell Carcinoma

To elucidate the deregulated functional modules that drive clear cell renal cell carcinoma (ccRCC), we performed comprehensive genomic, epigenomic, transcriptomic, proteomic, and phosphoproteomic characterization of treatment-naive ccRCC and paired normal adjacent tissue samples. Genomic analyses identified a distinct molecular subgroup associated with genomic instability. Integration of proteogenomic measurements uniquely identified protein dysregulation of cellular mechanisms impacted by genomic alterations, including oxidative phosphorylation-related metabolism, protein translation processes, and phospho-signaling modules. To assess the degree of immune infiltration in individual tumors, we identified microenvironment cell signatures that delineated four immune-based ccRCC subtypes characterized by distinct cellular pathways. This study reports a large-scale proteogenomic analysis of ccRCC to discern the functional impact of genomic alterations and provides evidence for rational treatment selection stemming from ccRCC pathobiology.

Systematic review and REMARK scoring of renal cell carcinoma prognostic circulating biomarker manuscripts

Background

No validated molecular biomarkers exist to help guide prognosis of renal cell carcinoma (RCC) patients. We seek to evaluate the quality of published prognostic circulating RCC biomarker manuscripts using the Reporting Recommendations for Tumor Marker Prognostic Studies (REMARK) guidelines.

Methods

The phrase “(renal cell carcinoma OR renal cancer OR kidney cancer OR kidney carcinoma) AND circulating AND (biomarkers OR cell free DNA OR tumor DNA OR methylated cell free DNA OR methylated tumor DNA)” was searched in Embase, Medline and PubMed March 2018. Relevant manuscripts were scored using 48 REMARK sub-criteria for a maximal score of 20 points.

Results

The search identified 535 publications: 33 were manuscripts of primary research and were analyzed. The mean REMARK score was 10.6 (range 6.42–14.2). All manuscripts stated their biomarker, study objectives and method of case selection. The lowest scoring criteria: time lapse between storage of blood/serum and marker assay (n = 2) and lack of flow diagram (n = 2). REMARK scores were significantly higher in publications stating adherence to REMARK guidelines (p = 0.0307) and reporting statistically significant results (p = 0.0318).

Conclusions

Most RCC prognostic biomarker manuscripts poorly adhere to the REMARK guidelines. Better designed studies and appropriate reporting are required to address this urgent unmet need.

Nuclear Mechanics and Cancer Cell Migration

As a cancer cell invades adjacent tissue, penetrates a basement membrane barrier, or squeezes into a blood capillary, its nucleus can be greatly constricted. Here, we examine: (1) the passive and active deformation of the nucleus during 3D migration; (2) the nuclear structures-namely, the lamina and chromatin-that govern nuclear deformability; (3) the effect of large nuclear deformation on DNA and nuclear factors; and (4) the downstream consequences of mechanically stressing the nucleus. We focus especially on recent studies showing that constricted migration causes nuclear envelope rupture and excess DNA damage, leading to cell cycle suppression, possibly cell death, and ultimately it seems to heritable genomic variation. We first review the latest understanding of nuclear dynamics during cell migration, and then explore the functional effects of nuclear deformation, especially in relation to genome integrity and potentially cancerous mutations.

Tumor Microenvironment Dynamics in Clear-Cell Renal Cell Carcinoma

Renal cell carcinoma stands out as one of the most immune-infiltrated tumors in pan-cancer comparisons. Features of the tumor microenvironment heavily affect disease biology and may affect responses to systemic therapy. With evolving frontline options in the metastatic setting, several immune checkpoint blockade regimens have emerged as efficacious, and there is growing interest in characterizing features of tumor biology that can reproducibly prognosticate patients and/or predict the likelihood of their deriving therapeutic benefit. Herein, we review pertinent characteristics of the tumor microenvironment with dedicated attention to candidate prognostic and predictive signatures as well as possible targets for future drug development. SIGNIFICANCE: Tumor microenvironment features broadly characterizing angiogenesis and inflammatory signatures have shown striking differences in response to immune checkpoint blockade and antiangiogenic agents. Integration of stromal and immune biomarkers may hence produce predictive and prognostic signatures to guide management with existing regimens as well as future drug development.

Cell death-related molecules and biomarkers for renal cell carcinoma targeted therapy

Renal cell carcinoma (RCC) is not sensitive to conventional radio- and chemotherapies and is at least partially resistant to impairments in cell death-related signaling pathways. The hallmarks of RCC formation include diverse signaling pathways, such as maintenance of proliferation, cell death resistance, angiogenesis induction, immune destruction avoidance, and DNA repair. RCC diagnosed during the early stage has the possibility of cure with surgery. For metastatic RCC (mRCC), molecular targeted therapy, especially antiangiogenic therapy (e.g., tyrosine kinase inhibitors, TKIs, such as sunitinib), is one of the main partially effective therapeutics. Various forms of cell death that may be associated with the resistance to targeted therapy because of the crosstalk between targeted therapy and cell death resistance pathways were originally defined and differentiated into apoptosis, necroptosis, pyroptosis, ferroptosis and autophagic cell death based on cellular morphology. Particularly, as a new form of cell death, T cell-induced cell death by immune checkpoint inhibitors expands the treatment options beyond the current targeted therapy. Here, we provide an overview of cell death-related molecules and biomarkers for the progression, prognosis and treatment of mRCC by targeted therapy, with a focus on apoptosis and T cell-induced cell death, as well as other forms of cell death.

Application of neoantigens in malignant tumor treatment and prognosis evaluation

In the last decade, there have been an endless number of cancer therapy strategies, and the study of tumor neoantigens provides a new direction for cancer immune therapy. With the development of deep sequencing, especially whole-exome sequencing, great opportunities have been provided to precise immune therapy of malignant tumors. This article systematically summarizes the research on tumor neoantigens in the past ten years and the challenges most likely to be encountered, describes the role of neoantigens in the treatment of malignant tumors, and discusses their possible clinical applications.