Tumor Mutational Burden as a Predictive Biomarker in Solid Tumors

Proteogenomic Analysis Unveils the HLA Class I-Presented Immunopeptidome in Melanoma and EGFR-Mutant Lung Adenocarcinoma

Immune checkpoint inhibitors and adoptive lymphocyte transfer–based therapies have shown great therapeutic potential in cancers with high tumor mutational burden (TMB), such as melanoma, but not in cancers with low TMB, such as mutant epidermal growth factor receptor (EGFR)–driven lung adenocarcinoma. Precision immunotherapy is an unmet need for most cancers, particularly for cancers that respond inadequately to immune checkpoint inhibitors. Here, we employed large-scale MS-based proteogenomic profiling to identify potential immunogenic human leukocyte antigen (HLA) class I-presented peptides in melanoma and EGFR-mutant lung adenocarcinoma. Similar numbers of peptides were identified from both tumor types. Cell line and patient-specific databases (DBs) were constructed using variants identified from whole-exome sequencing. A de novo search algorithm was used to interrogate the HLA class I immunopeptidome MS data. We identified 12 variant peptides and several classes of tumor-associated antigen-derived peptides. We constructed a cancer germ line (CG) antigen DB with 285 antigens. This allowed us to identify 40 class I-presented CG antigen–derived peptides. The class I immunopeptidome comprised more than 1000 post-translationally modified (PTM) peptides representing 58 different PTMs, underscoring the critical role PTMs may play in HLA binding. Finally, leveraging de novo search algorithm and an annotated long noncoding RNA (lncRNA) DB, we developed a novel lncRNA-encoded peptide discovery pipeline to identify 44 lncRNA-derived peptides that are presented by class I. We validated tandem MS spectra of select variant, CG antigen, and lncRNA-derived peptides using synthetic peptides and performed HLA class I-binding assays to demonstrate binding to class I proteins. In summary, we provide direct evidence of HLA class I presentation of a large number of variant and tumor-associated peptides in both low and high TMB cancer. These results can potentially be useful for precision immunotherapies, such as vaccine or adoptive cell therapies in melanoma and EGFR-mutant lung cancers.

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Proteogenomics identified ∼35,000 class I-presented peptides.

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CG antigen and PTM peptides identified in melanoma and lung cancer.

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De novo search identified variant and lncRNA-derived peptides.

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A new strategy to identify class I-presented lncRNA-derived peptides developed.

Intrapulmonic Cavity or Necrosis on Baseline CT Scan Serves as an Efficacy Predictor of Anti-PD-(L)1 Inhibitor in Advanced Lung Squamous Cell Carcinoma

Background

Predictive markers for guidance and monitoring of immunotherapy in lung squamous cell carcinoma (LSCC) are an interesting topic but have yet to be fully explored. A primary characteristic of LSCC is tumor necrosis that results in extensive immune suppression in patients. We sought to assess whether tumor necrosis or cavity on baseline CT could effectively predict the efficacy of immune checkpoint inhibitors (ICIs) in advanced LSCC.

Methods

Advanced LSCC cases undergoing pre-treatment chest CT imaging and receiving ICIs were retrospectively collected. All CT images were reviewed by an independent chest radiologist blinded to any previous diagnosis to confirm morphological alterations in necrosis or cavity. We performed Logistic regression and developed Cox proportional hazards models to assess the predictive performance of baseline necrosis or cavity characteristics in advanced LSCC. Survival estimates were observed using Kaplan–Meier curves.

Results

Ninety-three patients were eligible for analysis, predominantly consisting of patients with ECOG performance status of 0 or 1 (97.8%), male patients (95.7%), and heavy smokers (92.5%). Intrapulmonic necrosis or cavity on CT scan was present in 52.7% of all patients. Generally, the objective response rate (ORR) in patients with necrosis or cavity to ICI treatment was significantly worse versus those without (30.6% vs 54.5%, p = 0.020), with the subgroup ORRs as follows: ICI monotherapy (necrosis vs non-necrosis: 10.0% vs 36.8%, p =0.047) and ICI combination therapy (44.8% vs 68.0%, p =0.088). Multivariable analysis identified intrapulmonic necrosis or cavity at baseline as a major risk factor for advanced LSCC (HR 4.042, 95% CI1.149–10.908, p = 0.006). Multivariate Cox analysis showed that baseline necrosis or cavity and ICI monotherapy were unfavorable factors for progression-free survival (HR 1.729; 95% CI1.203–2.484, p =0.003).

Conclusion

LSCC patients with intrapulmonic cavity or necrosis on baseline CT scan may respond poorly to anti-PD-(L)1-treatment, monotherapy and combination therapy alike.

Assigning evidence to actionability: An introduction to variant interpretation in precision cancer medicine

Modern concepts in precision cancer medicine are based on increasingly complex genomic analyses and require standardized criteria for the functional evaluation and reporting of detected genomic alterations in order to assess their clinical relevance. In this article, we propose and address the necessary steps in systematic variant evaluation consisting of bioinformatic analysis, functional annotation and clinical interpretation, focusing on the latter two aspects. We discuss the role and clinical application of current variant classification systems and point out their scope and limitations. Finally, we highlight the significance of the molecular tumor board as a platform for clinical decision-making based on genomic analyses.

Pharmacologic modulation of RNA splicing enhances anti-tumor immunity

Although mutations in DNA are the best-studied source of neoantigens that determine response to immune checkpoint blockade, alterations in RNA splicing within cancer cells could similarly result in neoepitope production. However, the endogenous antigenicity and clinical potential of such splicing-derived epitopes have not been tested. Here, we demonstrate that pharmacologic modulation of splicing via specific drug classes generates bona fide neoantigens and elicits anti-tumor immunity, augmenting checkpoint immunotherapy. Splicing modulation inhibited tumor growth and enhanced checkpoint blockade in a manner dependent on host T cells and peptides presented on tumor MHC class I. Splicing modulation induced stereotyped splicing changes across tumor types, altering the MHC I-bound immunopeptidome to yield splicing-derived neoepitopes that trigger an anti-tumor T cell response in vivo. These data definitively identify splicing modulation as an untapped source of immunogenic peptides and provide a means to enhance response to checkpoint blockade that is readily translatable to the clinic.

RBM10 Deficiency Is Associated With Increased Immune Activity in Lung Adenocarcinoma

Introduction

RBM10 is one of the frequently mutated genes in lung adenocarcinoma (LUAD). Previous studies have confirmed that RBM10 could suppress the disease progression and cell proliferation in LUAD, but its loss-of-function mutations are more frequent in early-stage disease and decrease with the advancement of the clinical stage. This is contradictory to its role of tumor suppressor. Here, we conducted a systematic analysis to elucidate whether there was other potential biological significance of RBM10 deficiency during the progression of LUAD.

Materials and Methods

The whole exome sequencing data of 39 tumor samples from early-stage LUADs (GGN cohort) and genomic and transcriptome data of the Cancer Genome Atlas (TCGA) LUAD cohort (TCGA_LUAD cohort) and a Chinese LUAD cohort (CHOICE_ADC cohort) were first obtained. Systematic bioinformatic analyses were then conducted to determine gene expression signature, immune infiltration levels and predicted immunotherapy response. Immunohistochemistry (IHC) was also conducted to validate the result of immune infiltration.

Results

The mutation rate of RBM10 was significantly higher in the GGN cohort than that in the TCGA_LUAD and CHOICE_ADC cohorts. In both TCGA_LUAD and CHOICE_ADC cohorts, multiple immune related pathways were markedly enriched in RBM10 deficient group. Further analyses showed that tumors with RBM10 mutations displayed higher TMB, and LUADs with RBM10 deficiency also showed higher HLA expression levels, including many HLA class I and II molecules. Additionally, many immune cells, including myeloid dendritic cells, macrophages, neutrophils and CD8+T cells, showed higher infiltration levels in LUADs with RBM10 deficiency. Finally, some immune checkpoint molecules, such as PD-L1 and TIM-3, were highly expressed in RBM10 deficient population and the predicted immunotherapy response was calculated through TIDE algorithm, showing that IFNG expression, MSI score and CD8 expression were higher in RBM10 deficient group, while MDSC and M2 macrophage were lower in RBM10 deficient group.

Conclusion

Our study demonstrates that RBM10 deficient LUADs show higher HLA expression and immune cell infiltration, and some immune checkpoint molecules are also highly expressed. In brief, RBM10 deficiency could enhance anti-tumor immunity in LUAD.

A Signature-Based Classification of Gastric Cancer That Stratifies Tumor Immunity and Predicts Responses to PD-1 Inhibitors

Gastric cancer is a leading cause of cancer-related deaths with considerable heterogeneity among patients. Appropriate classifications are essential for prognosis prediction and individualized treatment. Although immunotherapy showed potential efficacy in a portion of patients with gastric cancer, few studies have tried to classify gastric cancer specifically based on immune signatures. In this study, we established a 3-subtype cluster with low (C_LIM), medium (C_MIM), and high (C_HIM) enrichment of immune signatures based on immunogenomic profiling. We validated the classification in multiple independent datasets. The C_HIM subtype exhibited a relatively better prognosis and showed features of “hot tumors”, including low tumor purity, high stromal components, overexpression of immune checkpoint molecules, and enriched tumor-infiltrated immune cells (activated T cells and macrophages). In addition, C_HIM tumors were also characterized by frequent ARID1A mutation, rare TP53 mutation, hypermethylation status, and altered protein expression (HER2, β-catenin, Cyclin E1, PREX1, LCK, PD-L1, Transglutaminase, and cleaved Caspase 7). By Gene Set Variation Analysis, “TGFβ signaling pathway” and “GAP junction” were enriched in C_LIM tumors and inversely correlated with CD8⁺ and CD4⁺ T cell infiltration. Of note, the C_HIM patients showed a higher response rate to immunotherapy (44.4% vs. 11.1% and 16.7%) and a more prolonged progression-free survival (4.83 vs. 1.86 and 2.75 months) than C_MIM and C_LIM patients in a microsatellite-independent manner. In conclusion, the new immune signature-based subtypes have potential therapeutic and prognostic implications for gastric cancer management, especially immunotherapy.

Prognostic and immunological role of CD36: A pan-cancer analysis

CD36 plays a critical role in lipid metabolism, which is closely associated with human immunity. However, the role of CD36 in cancer remains unclear. We performed a pan-cancer analysis to elucidate the potential role of CD36 in cancer by investigating its prognostic value and current predictors for the efficacy of immune checkpoint inhibitors (ICIs) in multiple cancer types. CD36 expression in cancer cell lines, tumor tissue, and their adjacent normal tissues displayed heterogeneity among different cancers. Immunohistochemistry was used to detect CD36 expression and confirmed the results. CD36 expression significantly affects prognosis in the six cancer types. High CD36 expression was marginally associated with poorer prognosis in four of them and improved prognosis in the remaining two types. CD36 expression was significantly correlated with the 6 immune infiltrates in most cancer types. In addition, CD36 gene expression was positively correlated with Stromal score, Immune score, and ESTIMATE score. A total of 47 immune checkpoint genes were collected and their relationship with CD36 expression was analyzed. CD36 expression was significantly associated with multiple stimulatory and inhibitory checkpoint molecules with a disease-specific pattern. As to the genes reported to positively relate to the efficacy of ICIs, CD36 expression was positively correlated with most of them but negatively associated with a small proportion of cancer type-specific patterns. Concerning the genes negatively related to the efficacy of ICIs, CD36 expression was positively correlated with NRP1 and TNFSF15 in multiple cancers. CD36 expression was negatively correlated with tumor neoantigen burden in most cancer types. However, CD36 expression was negatively correlated with tumor mutation burden in most cancer types. The correlation between CD36 expression and the four methyltransferases was also significant in multiple cancers, but also with a cancer type-specific pattern. In summary, the current study found CD36 expression and its prognostic value in multiple cancer types. In addition, the expression of CD36 was significantly associated with current predictors for the efficacy of ICIs. The practical application value of CD36 is disease specific.

Are Molecular Alterations Linked to Genetic Instability Worth to Be Included as Biomarkers for Directing or Excluding Melanoma Patients to Immunotherapy?

The improvement of the immunotherapeutic potential in most human cancers, including melanoma, requires the identification of increasingly detailed molecular features underlying the tumor immune responsiveness and acting as disease-associated biomarkers. In recent past years, the complexity of the immune landscape in cancer tissues is being steadily unveiled with a progressive better understanding of the plethora of actors playing in such a scenario, resulting in histopathology diversification, distinct molecular subtypes, and biological heterogeneity. Actually, it is widely recognized that the intracellular patterns of alterations in driver genes and loci may also concur to interfere with the homeostasis of the tumor microenvironment components, deeply affecting the immune response against the tumor. Among others, the different events linked to genetic instability—aneuploidy/somatic copy number alteration (SCNA) or microsatellite instability (MSI)—may exhibit opposite behaviors in terms of immune exclusion or responsiveness. In this review, we focused on both prevalence and impact of such different types of genetic instability in melanoma in order to evaluate whether their use as biomarkers in an integrated analysis of the molecular profile of such a malignancy may allow defining any potential predictive value for response/resistance to immunotherapy.

A genomic mutation signature predicts the clinical outcomes of immunotherapy and characterizes immunophenotypes in gastrointestinal cancer

The association between genetic variations and immunotherapy benefit has been widely recognized, while such evidence in gastrointestinal cancer remains limited. We analyzed the genomic profile of 227 immunotherapeutic gastrointestinal cancer patients treated with immunotherapy, from the Memorial Sloan Kettering (MSK) Cancer Center cohort. A gastrointestinal immune prognostic signature (GIPS) was constructed using LASSO Cox regression. Based on this signature, patients were classified into two subgroups with distinctive prognoses (p < 0.001). The prognostic value of the GIPS was consistently validated in the Janjigian and Pender cohort (N = 54) and Peking University Cancer Hospital cohort (N = 92). Multivariate analysis revealed that the GIPS was an independent prognostic biomarker. Notably, the GIPS-high tumor was indicative of a T-cell-inflamed phenotype and immune activation. The findings demonstrated that GIPS was a powerful predictor of immunotherapeutic survival in gastrointestinal cancer and may serve as a potential biomarker guiding immunotherapy treatment decisions.

Characteristics of Pan-Cancer Patients With Ultrahigh Tumor Mutation Burden

Background

Tumor mutation burden has been proven to be a good predictor for the efficacy of immunotherapy, especially in patients with hypermutation. However, most research focused on the analysis of hypermutation in individual tumors, and there is a lack of integrated research on the hypermutation across different cancers. This study aimed to characterize hypermutated patients to distinguish between these patients and non-hypermutated patients.

Methods

A total of 5,980 tumor samples involving 23 types of solid tumors from the in-house database were included in the study. Based on the cutoff value of tumor mutation burden (TMB), all samples were divided into hypermutated or non-hypermutated groups. Microsatellite instability status, PD-L1 expression and other mutation-related indicators were analyzed.

Results

Among the 5,980 tumor samples, 1,164 were selected as samples with hypermutation. Compared with the non-hypermutated group, a significant increase in the mutation rates of DNA mismatch repair genes and polymerase genes was detected in the hypermutated group, and there was an overlap between high TMB and high microsatellite instability or high PD-L1. In addition, we found that EGFR, KRAS and PIK3CA had a high frequency of both single nucleotide variation and copy number variation mutations. These identified mutant genes were enriched in the oncogenic signaling pathway and the DNA damage repair pathway. At the same time, the somatic cell characteristics and distribution of the two groups were significantly different.

Conclusions

This study identified genetic and phenotypic characteristics of hypermutated tumors and demonstrated that DNA damage repair is critically involved in hypermutation.

Cross-oncopanel study reveals high sensitivity and accuracy with overall analytical performance depending on genomic regions

BACKGROUND

Targeted sequencing using oncopanels requires comprehensive assessments of accuracy and detection sensitivity to ensure analytical validity. By employing reference materials characterized by the U.S. Food and Drug Administration-led SEquence Quality Control project phase2 (SEQC2) effort, we perform a cross-platform multi-lab evaluation of eight Pan-Cancer panels to assess best practices for oncopanel sequencing.

RESULTS

All panels demonstrate high sensitivity across targeted high-confidence coding regions and variant types for the variants previously verified to have variant allele frequency (VAF) in the 5-20% range. Sensitivity is reduced by utilizing VAF thresholds due to inherent variability in VAF measurements. Enforcing a VAF threshold for reporting has a positive impact on reducing false positive calls. Importantly, the false positive rate is found to be significantly higher outside the high-confidence coding regions, resulting in lower reproducibility. Thus, region restriction and VAF thresholds lead to low relative technical variability in estimating promising biomarkers and tumor mutational burden.

CONCLUSION

This comprehensive study provides actionable guidelines for oncopanel sequencing and clear evidence that supports a simplified approach to assess the analytical performance of oncopanels. It will facilitate the rapid implementation, validation, and quality control of oncopanels in clinical use.

Gene expression and immune infiltration in melanoma patients with different mutation burden

BACKGROUND

Immunotherapy is a vital component in cancer treatment. However, due to the complex genetic bases of cancer, a clear prediction index for efficacy has not been established. Tumor mutation burden (TMB) is one of the essential factors that affect immunotherapeutic efficacies, but it has not been determined whether the mutation is associated with the survival of Skin Cutaneous Melanoma (SKCM) patients. This study aimed at evaluating the correlation between TMB and immune infiltration.

METHODS

Somatic mutation profiles (n = 467), transcriptome data (n = 471), and their clinical information (n = 447) of all SKCM samples were downloaded from The Cancer Genome Atlas (TCGA) database. For each sample, TMB was calculated as the number of variants per megabase. Based on K-M survival analysis, they were allocated into the high-TMB and low-TMB groups (the optimal cutoff was determined by the 'surv_cutpoint' algorithm of survival R package). Then, Gene ontology (GO) and Gene Set Enrichment Analyses (GSEA) were performed, with immune-associated biological pathways found to be significantly enriched in the low-TMB group. Therefore, immune genes that were differentially expressed between the two groups were evaluated in Cox regression to determine their prognostic values, and a four-gene TMB immune prognostic model (TMB-IP) was constructed.

RESULTS

Elevated TMB levels were associated with better survival outcomes in SKCM patients. Based on the cutoff value in OS analysis, they were divided into high-TMB and low-TMB groups. GSEA revealed that the low-TMB group was associated with immunity while intersection analysis revealed that there were 38 differentially expressed immune-related genes between the two groups. Four TMB-associated immune genes were used to construct a TMB-IP model. The AUC of the ROC curve of this model reached a maximum of 0.75 (95%CI, 0.66-0.85) for OS outcomes. Validation in each clinical subgroup confirmed the efficacy of the model to distinguish between high and low TMB-IP score patients.

CONCLUSIONS

In SKCM patients, low TMB was associated with worse survival outcomes and enriched immune-associated pathways. The four TMB-associated immune genes model can effectively distinguish between high and low-risk patients.

High tumor mutation burden fails to predict immune checkpoint blockade response across all cancer types

BACKGROUND

High tumor mutation burden (TMB-H) has been proposed as a predictive biomarker for response to immune checkpoint blockade (ICB), largely due to the potential for tumor mutations to generate immunogenic neoantigens. Despite recent pan-cancer approval of ICB treatment for any TMB-H tumor, as assessed by the targeted FoundationOne CDx assay in nine tumor types, the utility of this biomarker has not been fully demonstrated across all cancers.

PATIENTS AND METHODS

Data from over 10 000 patient tumors included in The Cancer Genome Atlas were used to compare approaches to determine TMB and identify the correlation between predicted neoantigen load and CD8 T cells. Association of TMB with ICB treatment outcomes was analyzed by both objective response rates (ORRs, N = 1551) and overall survival (OS, N = 1936).

RESULTS

In cancer types where CD8 T-cell levels positively correlated with neoantigen load, such as melanoma, lung, and bladder cancers, TMB-H tumors exhibited a 39.8% ORR to ICB [95% confidence interval (CI) 34.9-44.8], which was significantly higher than that observed in low TMB (TMB-L) tumors [odds ratio (OR) = 4.1, 95% CI 2.9-5.8, P < 2 × 10^-16]. In cancer types that showed no relationship between CD8 T-cell levels and neoantigen load, such as breast cancer, prostate cancer, and glioma, TMB-H tumors failed to achieve a 20% ORR (ORR = 15.3%, 95% CI 9.2-23.4, P = 0.95), and exhibited a significantly lower ORR relative to TMB-L tumors (OR = 0.46, 95% CI 0.24-0.88, P = 0.02). Bulk ORRs were not significantly different between the two categories of tumors (P = 0.10) for patient cohorts assessed. Equivalent results were obtained by analyzing OS and by treating TMB as a continuous variable.

CONCLUSIONS

Our analysis failed to support application of TMB-H as a biomarker for treatment with ICB in all solid cancer types. Further tumor type-specific studies are warranted.

Immune-Related Mutational Landscape and Gene Signatures: Prognostic Value and Therapeutic Impact for Head and Neck Cancer

Simple Summary

Immunotherapy has emerged as a standard-of-care for most human malignancies, including head and neck cancer, but only a limited number of patients exhibit a durable clinical benefit. An urgent medical need is the establishment of accurate response predictors, which is handicapped by the growing body of molecular, cellular and clinical variables that modify the complex nature of an effective anti-tumor immune response. This review summarizes more recent efforts to elucidate immune-related mutational landscapes and gene expression signatures by integrative analysis of multi-omics data, and highlights their potential therapeutic impact for head and neck cancer. A better knowledge of the underlying principles and relevant interactions could pave the way for rational therapeutic combinations to improve the efficacy of immunotherapy, in particular for those cancer patients at a higher risk for treatment failure.

Abstract

Immunotherapy by immune checkpoint inhibition has become a main pillar in the armamentarium to treat head and neck cancer and is based on the premise that the host immune system can be reactivated to successfully eliminate cancer cells. However, the response rate remains low and only a small subset of head and neck cancer patients achieves a durable clinical benefit. The availability of multi-omics data and emerging computational technologies facilitate not only a deeper understanding of the cellular composition in the tumor immune microenvironment but also enables the study of molecular principles in the complex regulation of immune surveillance versus tolerance. These knowledges will pave the way to apply immunotherapy more precisely and effectively. This review aims to provide a holistic view on how the immune landscape dictates the tumor fate and vice versa, and how integrative analysis of multi-omics data contribute to our current knowledge on the accuracy of predictive biomarkers and on a broad range of factors influencing the response to immunotherapy in head and neck cancer.

Biomarkers for Immunotherapy of Oral Squamous Cell Carcinoma: Current Status and Challenges

Oral squamous cell carcinoma (OSCC) forms a major health problem in many countries. For several decades the management of OSCC consisted of surgery with or without radiotherapy or chemoradiotherapy. Aiming to increase survival rate, recent research has underlined the significance of harnessing the immune response in treatment of many cancers. The promising finding of checkpoint inhibitors as a weapon for targeting metastatic melanoma was a key event in the development of immunotherapy. Furthermore, clinical trials have recently proven inhibitor of PD-1 for treatment of recurrent/metastatic head and neck cancer. However, some challenges (including patient selection) are presented in the era of immunotherapy. In this mini-review we discuss the emergence of immunotherapy for OSCC and the recently introduced biomarkers of this therapeutic strategy. Immune biomarkers and their prognostic perspectives for selecting patients who may benefit from immunotherapy are addressed. In addition, possible use of such biomarkers to assess the response to this new treatment modality of OSCC will also be discussed.

Identification of tumor antigens and immune subtypes of cholangiocarcinoma for mRNA vaccine development

BACKGROUND

The mRNA-based cancer vaccine has been considered a promising strategy and the next hotspot in cancer immunotherapy. However, its application on cholangiocarcinoma remains largely uncharacterized. This study aimed to identify potential antigens of cholangiocarcinoma for development of anti-cholangiocarcinoma mRNA vaccine, and determine immune subtypes of cholangiocarcinoma for selection of suitable patients from an extremely heterogeneous population.

METHODS

Gene expression profiles and corresponding clinical information were collected from GEO and TCGA, respectively. cBioPortal was used to visualize and compare genetic alterations. GEPIA2 was used to calculate the prognostic index of the selected antigens. TIMER was used to visualize the correlation between the infiltration of antigen-presenting cells and the expression of the identified antigens. Consensus clustering analysis was performed to identify the immune subtypes. Graph learning-based dimensionality reduction analysis was conducted to visualize the immune landscape of cholangiocarcinoma.

RESULTS

Three tumor antigens, such as CD247, FCGR1A, and TRRAP, correlated with superior prognoses and infiltration of antigen-presenting cells were identified in cholangiocarcinoma. Cholangiocarcinoma patients were stratified into two immune subtypes characterized by differential molecular, cellular and clinical features. Patients with the IS1 tumor had immune "hot" and immunosuppressive phenotype, whereas those with the IS2 tumor had immune "cold" phenotype. Interestingly, patients with the IS2 tumor had a superior survival than those with the IS1 tumor. Furthermore, distinct expression of immune checkpoints and immunogenic cell death modulators was observed between different immune subtype tumors. Finally, the immune landscape of cholangiocarcinoma revealed immune cell components in individual patient.

CONCLUSIONS

CD247, FCGR1A, and TRRAP are potential antigens for mRNA vaccine development against cholangiocarcinoma, specifically for patients with IS2 tumors. Therefore, this study provides a theoretical basis for the anti-cholangiocarcinoma mRNA vaccine and defines suitable patients for vaccination.

Cancer Immunotherapy Update: FDA-Approved Checkpoint Inhibitors and Companion Diagnostics

Immune checkpoint inhibitors (ICIs) are considered a new standard-of-care across many cancer indications. This review provides an update on ICIs approved by the Food and Drug Administration (FDA), with focus on monoclonal antibodies that target the programmed cell death 1 (PD-1) or its ligand, PD-1 ligand 1 (PD-L1), including information on their clinical indications and associated companion diagnostics. The information is further discussed with strategies for identifying predictive biomarkers to guide the clinical use of PD-1/PD-L1-targeted therapies.

CD96 Correlates With Immune Infiltration and Impacts Patient Prognosis: A Pan-Cancer Analysis

Background

Immunotherapy has significantly improved patient outcomes, but encountered obstacles recently. CD96, a novel immune checkpoint expressed on T cells and natural killer (NK) cells, is essential for regulating immune functions. However, how CD96 correlating with immune infiltration and patient prognosis in pan-cancer remains unclear.

Methods

HPA, TCGA, GEO, GTEx, Oncomine, TIMER2.0, PrognoScan, Linkedomics, Metascape, and GEPIA2 databases were used to analyze CD96 in cancers. Visualization of data was mostly achieved by R language, version 4.0.2.

Results

In general, CD96 was differentially expressed between most cancer and adjacent normal tissues. CD96 significantly impacted the prognosis of diverse cancers. Especially, high CD96 expression was associated with poorer overall survival (OS) and disease-specific survival (DSS) in the TCGA lower grade glioma (LGG) cohort (OS, HR = 2.18, 95% CI = 1.79–2.66, P < 0.001). The opposite association was significantly observed in skin cutaneous melanoma (SKCM) cohort (OS, HR = 0.96, 95% CI = 0.94–0.98, P < 0.001). Notably, SKCM samples demonstrated the highest CD96 mutation frequency among all cancer types. Furthermore, in most cancers, CD96 expression level was significantly correlated with expression levels of recognized immune checkpoints and abundance of multiple immune infiltrates including CD8+ T cells, dendric cells (DCs), macrophages, monocytes, NK cells, neutrophils, regulatory T cells (Tregs), and follicular helper T cells (Tfh). CD96 was identified as a risk factor, protective factor, and irrelevant variable in LGG, SKCM and adrenocortical carcinoma (ACC), respectively. CD96 related genes were involved in negative regulation of leukocyte in LGG, however, involved in multiple positive immune processes in SKCM. Furthermore, CD96 was significantly associated with particular immune marker subsets. Importantly, it strongly correlated with markers of type 1 helper T cell (Th1) in SKCM, but not in LGG or ACC either.

Conclusions

CD96 participates in diverse immune responses, governs immune cell infiltration, and impacts malignant properties of various cancer types, thus standing as a potential biomarker for determining patient prognosis and immune infiltration in multiple cancers, especially in glioma and melanoma.

Strength in numbers: predicting response to checkpoint inhibitors from large clinical datasets

The advent of immune checkpoint blockers for cancer therapy has spawned great interest in identifying molecular features reflecting the complexity of tumor immunity, which can subsequently be leveraged as predictive biomarkers. In a thorough big-data approach analyzing the largest series of homogenized molecular and clinical datasets, Litchfield et al. identified a set of genomic biomarkers that identifies immunotherapy responders across cancer types.

Prognostic and Predictive Values of Mismatch Repair Deficiency in Non-Metastatic Colorectal Cancer

Colorectal cancer (CRC) is the third most commonly diagnosed cancer worldwide. Universal MMR/MSI testing is standard of care for all patients with newly diagnosed CRC based on multi-society guidelines in the United States. Such testing is intended to identify patients with Lynch Syndrome due to a germline mutation in an MMR gene, but also detects those with sporadic dMMR/MSI-high CRCs. The prognostic utility of MMR/MSI status in non-metastatic colorectal cancer has been studied extensively, yet more limited data are available for its predictive utility. Results have not been entirely consistent due to potential stage-related differences and limited numbers of dMMR/MSI-H patients included in the studies. In this review, we summarize the current evidence for the prognostic and predictive value of dMMR/MSI-H in non-metastatic CRC, and discuss the use of this biomarker for patient management and treatment decisions in clinical practice.