Novel algorithmic approach predicts tumor mutation load and correlates with immunotherapy clinical outcomes using a defined gene mutation set

The future of affordable cancer immunotherapy

The treatment of cancer was revolutionized within the last two decades by utilizing the mechanism of the immune system against malignant tissue in so-called cancer immunotherapy. Two main developments boosted cancer immunotherapy: 1) the use of checkpoint inhibitors, which are characterized by a relatively high response rate mainly in solid tumors; however, at the cost of serious side effects, and 2) the use of chimeric antigen receptor (CAR)-T cells, which were shown to be very efficient in the treatment of hematologic malignancies, but failed to show high clinical effectiveness in solid tumors until now. In addition, active immunization against individual tumors is emerging, and the first products have reached clinical approval. These new treatment options are very cost-intensive and are not financially compensated by health insurance in many countries. Hence, strategies must be developed to make cancer immunotherapy affordable and to improve the cost-benefit ratio. In this review, we discuss the following strategies: 1) to leverage the antigenicity of "cold tumors" with affordable reagents, 2) to use microbiome-based products as markers or therapeutics, 3) to apply measures that make adoptive cell therapy (ACT) cheaper, e.g., the use of off-the-shelf products, 4) to use immunotherapies that offer cheaper platforms, such as RNA- or peptide-based vaccines and vaccines that use shared or common antigens instead of highly personal antigens, 5) to use a small set of predictive biomarkers instead of the "sequence everything" approach, and 6) to explore affordable immunohistochemistry markers that may direct individual therapies.

Utility of Tumor Mutational Burden as a Biomarker for Response to Immune Checkpoint Inhibition in the VA Population

PURPOSE

Immune checkpoint inhibitors (ICIs) are used for an increasing number of indications across various tumor types, as well as several tumor-agnostic indications in patients with advanced cancer. Although many patients benefit from ICI therapy, others do not, highlighting a need for better predictive biomarkers. Tumor mutational burden (TMB) reflects the global number of mutations within a tumor and has been widely explored as a predictive biomarker of ICI response. The current tumor type-agnostic US Food and Drug Administration approval of pembrolizumab for metastatic solid tumors defines high TMB (TMB-H) as ≥10 mut/Mb as measured by FoundationOne CDx. This fixed cutoff may not be the ideal value across all solid tumors.

METHODS

We performed a retrospective analysis of the association of survival outcomes with TMB in patients treated with ICI for five major cancer types, using real-world data from the VA. Survival was measured from initiation of ICI, and Kaplan-Meier survival curves were compared by log-rank test.

RESULTS

Overall survival (OS) was significantly longer for patients with TMB-H versus TMB low tumors in non-small-cell lung cancer (NSCLC; n = 1,593), head and neck (H&N) cancer (n = 222), and urothelial cancer (n = 332). OS was not significantly different based on TMB status in melanoma (n = 207) or esophageal/gastric cancer (n = 248).

CONCLUSION

Consistent with previous studies, a predictive value of TMB ≥10 mut/Mb for ICI response was found in NSCLC and H&N, but not in esophageal/gastric cancer. Although inconclusive in the literature, significant association was found in urothelial cancer. The predictive value of TMB in melanoma was inconclusive. Our analysis does not support the use of a fixed threshold for TMB as a standalone predictive biomarker for ICI across all solid tumors.

Japanese Society of Medical Oncology/Japan Society of Clinical Oncology/Japanese Society of Pediatric Hematology/Oncology-led clinical recommendations on the diagnosis and use of immunotherapy in patients with high tumor mutational burden tumors

The development of novel antitumor agents and accompanying biomarkers has improved survival across several tumor types. Previously, we developed recommendations for tumor-agnostic treatments in patients with solid tumors with DNA mismatch repair deficient or neurotrophic receptor tyrosine kinase fusions. Recently, immune checkpoint inhibitors have shown efficacy in patient with tumor mutation burden-high (TMB-H) solid tumors and have been established as a third tumor-agnostic agent, making it necessary to develop the guideline prioritized for these patients. Clinical questions regarding medical care were formulated for patients with TMB-H advanced solid tumors. Relevant publications were searched by PubMed and Cochrane Database. Critical publications and conference reports were added manually. Systematic reviews were performed for each clinical question for the purpose of developing clinical recommendations. The committee members identified by Japan Society of Clinical Oncology (JSCO), Japanese Society of Medical Oncology (JSMO), and Japanese society of pediatric hematology/oncology (JSPHO) voted to determine the level of each recommendation considering the strength of evidence, expected risks and benefits to patients, and other related factors. Thereafter, a peer review by experts nominated from JSCO, JSMO, and JSPHO, and the public comments among all societies' members was done. The current guideline describes three clinical questions and seven recommendations for whom, when, and how TMB should be tested, and what is recommended for patients with TMB-H advanced solid tumors. In this guideline, the committee proposed seven recommendations for performing TMB testing properly to select patients who are likely to benefit from immunotherapy.

In silico designed mRNA vaccines targeting CA-125 neoantigen in breast and ovarian cancer

Somatic mutation-derived neoantigens are associated with patient survival in breast and ovarian cancer. These neoantigens are targets for cancer, as shown by the implementation of neoepitope peptides as cancer vaccines. The success of cost-effective multi-epitope mRNA vaccines against SARS-Cov-2 in the pandemic established a model for reverse vaccinology. In this study, we aimed to develop an in silico pipeline designing an mRNA vaccine of the CA-125 neoantigen against breast and ovarian cancer, respectively. Using immuno-bioinformatics tools, we predicted cytotoxic CD8+ T cell epitopes based on somatic mutation-driven neoantigens of CA-125 in breast or ovarian cancer, constructed a self-adjuvant mRNA vaccine with CD40L and MHC-I -targeting domain to enhance cross-presentation of neoepitopes by dendritic cells. With an in silico ImmSim algorithm, we estimated the immune responses post-immunization, showing IFN-γ and CD8+ T cell response. The strategy described in this study may be scaled up and implemented to design precision multi-epitope mRNA vaccines by targeting multiple neoantigens.

Tumor Mutational Burden for Predicting Prognosis and Therapy Outcome of Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC), the primary hepatic malignancy, represents the second-highest cause of cancer-related death worldwide. Many efforts have been devoted to finding novel biomarkers for predicting both patients' survival and the outcome of pharmacological treatments, with a particular focus on immunotherapy. In this regard, recent studies have focused on unravelling the role of tumor mutational burden (TMB), i.e., the total number of mutations per coding area of a tumor genome, to ascertain whether it can be considered a reliable biomarker to be used either for the stratification of HCC patients in subgroups with different responsiveness to immunotherapy, or for the prediction of disease progression, particularly in relation to the different HCC etiologies. In this review, we summarize the recent advances on the study of TMB and TMB-related biomarkers in the HCC landscape, focusing on their feasibility as guides for therapy decisions and/or predictors of clinical outcome.

Cancer Resistance to Immunotherapy: Molecular Mechanisms and Tackling Strategies

Cancer immunotherapy has fundamentally altered cancer treatment; however, its efficacy is limited to a subset of patients in most clinical settings. The immune system plays a key role in cancer progression from tumor initiation to the metastatic state. Throughout the treatment course, communications between the immune cells in the tumor microenvironment and the immune macroenvironment, as well as interactions between the immune system and cancer cells, are dynamic and constantly evolving. To improve the clinical benefit for patients who do not respond completely to immunotherapy, the molecular mechanisms of resistance to immunotherapy must be elucidated in order to develop effective strategies to overcome resistance. In an attempt to improve and update the current understanding of the molecular mechanisms that hinder immunotherapy, we discuss the molecular mechanisms of cancer resistance to immunotherapy and the available treatment strategies.

DNA methylation regulators-related molecular patterns and tumor immune landscape in hepatocellular carcinoma

Increasing evidence showed that the dysregulation of DNA methylation regulators is a decisive feature of almost all cancer types and affects tumor progressions. However, few studies focused on the underlying influences of DNA methylation regulators-related genes (DMRegs) in immune cell-infiltration characteristics, tumor microenvironment (TME) and immunotherapy in HCC patients. In our study, the alterations of DNA methylation regulators modification patterns (DMRPs) were clustered from hepatocellular carcinoma (HCC) samples based on the expression of DNA methylation regulators as well as genetic and transcriptional features. In addition, based on molecular identification of three distinct molecular subtypes, we found that different DMRPs alterations were related to different clinicopathological characteristics, prognosis, and immune cells infiltration features. Moreover, we constructed and validated a DNA methylation regulators-related genes score (DMRegs_score) to predict the survival of HCC patients. A high DMRegs _score, which was characterized by more TP53 wild mutation, high expression of PD-1, CTLA-4, and remarkable immunity activation, was indicative of poor prognosis. Furthermore, we validated the expression of eight genes which were used for the prognostic signature in this risk score by RT-qPCR using tissues from our center. More importantly, DMRegs_score was highly correlated with targeted drug sensitivity. Additionally, we developed a highly accurate scoring system that could be used to improve the clinical applicability of DMRegs _score. In conclusion, these findings may contribute to a better understanding of DNA methylation regulators and provide new strategies for evaluating prognosis and developing more effective combination therapy for HCC patients.

Multi-modal molecular programs regulate melanoma cell state

Melanoma cells display distinct intrinsic phenotypic states. Here, we seek to characterize the molecular regulation of these states using multi-omic analyses of whole exome, transcriptome, microRNA, long non-coding RNA and DNA methylation data together with reverse-phase protein array data on a panel of 68 highly annotated early passage melanoma cell lines. We demonstrate that clearly defined cancer cell intrinsic transcriptomic programs are maintained in melanoma cells ex vivo and remain highly conserved within melanoma tumors, are associated with distinct immune features within tumors, and differentially correlate with checkpoint inhibitor and adoptive T cell therapy efficacy. Through integrative analyses we demonstrate highly complex multi-omic regulation of melanoma cell intrinsic programs that provide key insights into the molecular maintenance of phenotypic states. These findings have implications for cancer biology and the identification of new therapeutic strategies. Further, these deeply characterized cell lines will serve as an invaluable resource for future research in the field.

Epigenetic Repression of STING by MYC Promotes Immune Evasion and Resistance to Immune Checkpoint Inhibitors in Triple-Negative Breast Cancer

The MYC oncogene is frequently amplified in triple-negative breast cancer (TNBC). Here, we show that MYC suppression induces immune-related hallmark gene set expression and tumor-infiltrating T cells in MYC-hyperactivated TNBCs. Mechanistically, MYC repressed stimulator of interferon genes (STING) expression via direct binding to the STING1 enhancer region, resulting in downregulation of the T-cell chemokines CCL5, CXCL10, and CXCL11. In primary and metastatic TNBC cohorts, tumors with high MYC expression or activity exhibited low STING expression. Using a CRISPR-mediated enhancer perturbation approach, we demonstrated that MYC-driven immune evasion is mediated by STING repression. STING repression induced resistance to PD-L1 blockade in mouse models of TNBC. Finally, a small-molecule inhibitor of MYC combined with PD-L1 blockade elicited a durable response in immune-cold TNBC with high MYC expression, suggesting a strategy to restore PD-L1 inhibitor sensitivity in MYC-overexpressing TNBC.

Identification of an Endoplasmic Reticulum Stress-Related Gene Signature to Evaluate the Immune Status and Predict the Prognosis of Hepatocellular Carcinoma

Liver cancer is the sixth most frequently diagnosed primary malignancy and ranks as the third leading cause of cancer-related death worldwide in 2020. ER stress also plays a vital role in the pathogenesis of malignancies. In the current study, we aimed to construct an endoplasmic reticulum stress-related genes (ERGs) signature to predict the overall survival (OS) of patients with HCC. Differentially expressed ERGs (DE-ERGs) were analyzed using The Cancer Genome Atlas (TCGA-LIHC cohort) and International Cancer Genome Consortium (ICGC-LIRI-JP cohort) databases. The prognostic gene signature was identified by the univariate Cox regression and Least Absolute Shrinkage and Selection Operator (LASSO)-penalized Cox proportional hazards regression analysis. The predictive ability of the model was evaluated by utilizing Kaplan-Meier curves and time-dependent receiver operating characteristic (ROC) curves. Gene set variant analysis (GSVA) was performed to explore the underlying biological processes and signaling pathways. CIBERPORT and single-sample Gene Set Enrichment Analysis (ssGSEA) were implemented to estimate the immune status between the different risk groups. A total of 113 DE-ERGs were identified between 50 normal samples and 365 HCC samples in the TCGA-LIHC cohort, and 48 DE-ERGs were associated with OS through the univariate Cox regression. A six DE-ERGs (PPARGC1A, SQSTM1, SGK1, PON1, CDK1, and G6PD) signature was constructed and classified patients into high-risk and low-risk groups. The risk score was an independent prognostic indicator for OS (HR > 1, p < 0.001). The function enrichment analysis indicated that cell cycle, RNA degradation, protein localization, and cell division were the main biological processes. The high-risk group had higher immune cell infiltration levels than those of the low-risk group. We predicted the response to targeted therapy in high- and low-risk patients with HCC and found that the high-risk patients were more sensitive to pazopanib. At last, we verified the expression of the six gene patterns in HCC tissues by qRT-PCR and immunohistochemistry. This signature may be a potential tool to provide a choice for prognosis prediction and personal management of patients with HCC.

The Predictive Value of Tumor Mutation Burden on Clinical Efficacy of Immune Checkpoint Inhibitors in Melanoma: A Systematic Review and Meta-Analysis

Background: Tumor mutational burden (TMB) is a genomic biomarker that can predict favorable responses to immune checkpoint inhibitors (ICIs). Although we have better understanding of TMB in cancer immunity and cancer immunotherapy, the relationship between TMB and the clinical efficacy of ICIs remains unknown in the treatment of melanoma patients. Here, we conduct a systematic review and meta-analysis to evaluate the predictive value of TMB on the efficacy of ICIs in patients with melanoma.

Methods: We systematically collected data from PubMed, Embase, Cochrane Library, CNKI, China Biomedical Database (CBM), and Wanfang Database. The end date was set to 26 June 2021. We included retrospective studies or clinical trials of ICIs that reported hazard ratios (HRs) for overall survival and/or progression-free survival according to TMB. Data for 1,493 patients from 15 studies were included. In addition, pooled effect size, heterogeneity analysis, sensitivity analysis, publication bias detection, and subgroup analysis were performed based on the included data.

Results: Patients with high TMB showed significantly improved OS (HR = 0.49, 95% CI: 0.33, 0.73; p = 0.001) and PFS (HR = 0.47, 95% CI: 0.33, 0.68; p < 0.001) compared with patients with low TMB. This association was very good in patients treated with monotherapy, that is, anti-CTLA-4 or anti-PD-(L)-1 inhibitors, but not for the patients treated with a combination of the two drugs. The subgroup analysis results showed that heterogeneity was substantial in the targeted next-generation sequencing (NGS) group. Publication bias was detected, and the results were visualized using the funnel chart. And sensitivity analysis and trim-and-fill method analysis showed that our results were stable and reliable.

Conclusion: High TMB is associated with improved OS and PFS in melanoma patients treated with mono-drug ICIs. TMB determined by NGS should be standardized to eliminate heterogeneity. Therefore, the role of TMB in identifying melanoma patients who may benefit from ICI should be further determined in more randomized controlled trials in the future.

Multi-Level Analysis and Identification of Tumor Mutational Burden Genes across Cancer Types

Tumor mutational burden (TMB) is considered a potential biomarker for predicting the response and effect of immune checkpoint inhibitors (ICIs). However, there are still inconsistent standards of gene panels using next-generation sequencing and poor correlation between the TMB genes, immune cell infiltrating, and prognosis. We applied text-mining technology to construct specific TMB-associated gene panels cross various cancer types. As a case exploration, Pearson’s correlation between TMB genes and immune cell infiltrating was further analyzed in colorectal cancer. We then performed LASSO Cox regression to construct a prognosis predictive model and calculated the risk score of each sample for receiver operating characteristic (ROC) analysis. The results showed that the assessment of TMB gene panels performed well with fewer than 500 genes, highly mutated genes, and the inclusion of synonymous mutations and immune regulatory and drug-target genes. Moreover, the analysis of TMB differentially expressed genes (DEGs) suggested that JAKMIP1 was strongly correlated with the gene expression level of CD8⁺ T cell markers in colorectal cancer. Additionally, the prognosis predictive model based on 19 TMB DEGs reached AUCs of 0.836, 0.818, and 0.787 in 1-, 3-, and 5-year OS models, respectively (C-index: 0.810). In summary, the gene panel performed well and TMB DEGs showed great potential value in immune cell infiltration and in predicting survival.

Clinical and Molecular Characterization of POLE Mutations as Predictive Biomarkers of Response to Immune Checkpoint Inhibitors in Advanced Cancers

PURPOSE

DNA polymerase epsilon is critical to DNA proofreading and replication. Mutations in POLE have been associated with hypermutated tumors and antitumor response to immune checkpoint inhibitor (ICI) therapy. We present a clinicopathologic analysis of patients with advanced cancers harboring POLE mutations, the pattern of co-occurring mutations, and their response to ICI therapy within the context of mutation pathogenicity.

METHODS

We conducted a retrospective analysis of next-generation sequencing data at MD Anderson Cancer Center to identify patient tumors with POLE mutations and their co-occurring mutations. The pathogenicity of each mutation was annotated using InterVar and ClinVar. Differences in therapeutic response to ICI, survival, and co-occurring mutations were reported by POLE pathogenicity status.

RESULTS

Four hundred fifty-eight patient tumors with POLE mutations were identified from 14,229 next-generation sequencing reports; 15.0% of POLE mutations were pathogenic, 15.9% benign, and 69.1% variant of unknown significance. Eighty-two patients received either programmed death 1 or programmed death ligand-1 inhibitors as monotherapy or in combination with cytotoxic T-cell lymphocyte-4 inhibitors. Patients with pathogenic POLE mutations had improved clinical benefit rate (82.4% v 30.0%; P = .013), median progression-free survival (15.1 v 2.2 months; P < .001), overall survival (29.5 v 6.8 months; P < .001), and longer treatment duration (median 15.5 v 2.5 months; P < .001) compared to those with benign variants. Progression-free survival and overall survival remained superior when adjusting for number of co-occurring mutations (≥ 10 v < 10) and/or microsatellite instability status (proficient mismatch repair v deficient mismatch repair). The number of comutations was not associated with response to ICI (clinical benefit v progressive disease: median 13 v 11 comutations; P = .18).

CONCLUSION

Pathogenic POLE mutations were associated with clinical benefit to ICI therapy. Further studies are warranted to validate POLE mutation as a predictive biomarker of ICI therapy.

Real-world survival analysis by tumor mutational burden in non-small cell lung cancer: a multisite U.S. study

BACKGROUND

Tumor mutational burden (TMB) is a potential biomarker to predict tumor response to immuno-oncology agents in patients with metastatic non-small cell lung cancer (NSCLC).

MATERIALS AND METHODS

A multi-site cohort study evaluated patients diagnosed with stage IV NSCLC between 2012 and 2019 who had received comprehensive genomic profiling (CGP) and any NSCLC-related treatment at 9 U.S. cancer centers. Baseline characteristics and clinical outcomes were compared between patients with TMB <10 and TMB ≥10.

RESULTS

Among the 667 patients with CGP results, most patients received CGP from Foundation Medicine (64%) or Caris (20%). Patients with TMB ≥10 (vs. TMB <10) were associated with a positive smoking history. TMB was associated with ALK (p = 0.01), EGFR (p < 0.01), and TP53 (p < 0.05) alterations. TMB >10 showed a significant association towards longer overall survival (OS) (HR: 0.43, 95% CI: 0.21-0.88, p = 0.02) and progression-free survival (PFS) (HR: 0.43, 95% CI: 0.21-0.85, p = 0.02) in patients treated with first-line immunotherapy and tested by Foundation Medicine or Caris at treatment initiation.

CONCLUSIONS

TMB levels greater than or equal to 10 mut/Mb, when tested by Foundation Medicine or Caris at treatment initiation, were significantly associated with improved OS and PFS among patients treated with first-line immunotherapy-containing regimens. Additional prospective research is warranted to validate this biomarker along with PD-L1 expression.

hDirect-MAP: projection-free single-cell modeling of response to checkpoint immunotherapy

There is a lack of robust generalizable predictive biomarkers of response to immune checkpoint blockade in multiple types of cancer. We develop hDirect-MAP, an algorithm that maps T cells into a shared high-dimensional (HD) expression space of diverse T cell functional signatures in which cells group by the common T cell phenotypes rather than dimensional reduced features or a distorted view of these features. Using projection-free single-cell modeling, hDirect-MAP first removed a large group of cells that did not contribute to response and then clearly distinguished T cells into response-specific subpopulations that were defined by critical T cell functional markers of strong differential expression patterns. We found that these grouped cells cannot be distinguished by dimensional-reduction algorithms but are blended by diluted expression patterns. Moreover, these identified response-specific T cell subpopulations enabled a generalizable prediction by their HD metrics. Tested using five single-cell RNA-seq or mass cytometry datasets from basal cell carcinoma, squamous cell carcinoma and melanoma, hDirect-MAP demonstrated common response-specific T cell phenotypes that defined a generalizable and accurate predictive biomarker.

Predictive molecular markers for the treatment with immune checkpoint inhibitors in colorectal cancer

Colorectal cancer is one of the most common malignant tumors and, hence, has become one of the most important public health issues in the world. Treatment with immune checkpoint inhibitors (ICIs) successfully improves the survival rate of patients with melanoma, non-small-cell lung cancer, and other malignancies, and its application in metastatic colorectal cancer is being actively explored. However, a few patients develop drug resistance. Predictive molecular markers are important tools to precisely screen patient groups that can benefit from treatment with ICIs. The current article focused on certain important predictive molecular markers for ICI treatment in colorectal cancer, including not only some of the mature molecular markers, such as deficient mismatch repair (d-MMR), microsatellite instability-high (MSI-H), tumor mutational burden (TMB), programmed death-ligand-1 (PD-L1), tumor immune microenvironment (TiME), and tumor-infiltrating lymphocytes (TILs), but also some of the novel molecular markers, such as DNA polymerase epsilon (POLE), polymerase delta 1 (POLD1), circulating tumor DNA (ctDNA), and consensus molecular subtypes (CMS). We have reviewed these markers in-depth and presented the results from certain important studies, which suggest their applicability in CRC and indicate their advantages and disadvantages. We hope this article is helpful for clinicians and researchers to systematically understand these markers and can guide the treatment of colorectal cancer.

Inhibition of CMTM4 Sensitizes Cholangiocarcinoma and Hepatocellular Carcinoma to T Cell-Mediated Antitumor Immunity Through PD-L1

Liver cancers consist primarily of hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC). Immune checkpoint inhibitors have emerged as promising therapeutic agents against liver cancers. Programmed cell death protein 1 (PD-1) is an immunoinhibitory receptor present on T cells that interacts with its ligand programmed death-ligand 1 (PD-L1) found on cancer cells. Blocking PD-1/PD-L1 binding improves T-cell survival, proliferation and cytotoxicity, which enhances their antitumor activity. Better understanding of the molecular mechanisms governing PD-1/PD-L1 response is essential to the development of predictive markers and therapeutic combinations that could improve the efficiency of anti-PD-1/PD-L1 treatment. Chemokine-like factor (CKLF)-like MARVEL transmembrane domain-containing 6 (CMTM6) has been recently identified as a major regulator of PD-L1. Another member in the CMTM family, CKLF-like MARVEL transmembrane domain-containing 4 (CMTM4), has been shown to compensate for the effects of CMTM6 when CMTM6 is lost. Interestingly, we found that CMTM4 is the major regulator of PD-L1 in the context of liver cancer. Up-regulated CMTM4 in patients with HCC and ICC is associated with poor patient survival, potentially due to its function in stabilizing PD-L1 expression, hence facilitating escape from T cell-mediated cytotoxicity. We confirmed the role of CMTM4 as a positive regulator of PD-L1 in multiple HCC and ICC cell lines and demonstrated that CMTM4 stabilizes PD-L1 through posttranslational mechanisms. In vivo, suppression of Cmtm4 inhibited HCC growth and increased CD8+ T-cell infiltration in immunocompetent mice. Furthermore, we found that depletion of CMTM4 sensitized HCC tumor to anti-PD-L1 treatment compared with control. This suggests that CMTM4 expression level could be a predictive marker for patient response to anti-PD-L1 treatment, and CMTM4 depletion can potentially be used to enhance the clinical benefits of anti-PD-L1 immunotherapy in patients with liver cancer.

Comparative Analysis of Predictive Biomarkers for PD-1/PD-L1 Inhibitors in Cancers: Developments and Challenges

Simple Summary

The development of immune checkpoint inhibitors (ICIs) has greatly changed the treatment landscape of multiple malignancies. However, the wide administration of ICIs is mainly obstructed by the low response rate and several life-threatening adverse events. Thus, there is an urgent need to identify sets of biomarkers to predict which patients will respond to ICIs. In this review, we discuss the recently investigated molecular and clinical determinants of ICI response, from the aspects of tumor features, clinical features, as well as tumor microenvironment.

Abstract

Immune checkpoint inhibitors (ICIs) targeting programmed cell death protein 1 (PD-1)/programmed death-ligand 1 (PD-L1) have dramatically changed the landscape of cancer therapy. Both remarkable and durable responses have been observed in patients with melanoma, non-small-cell lung cancer (NSCLC), and other malignancies. However, the PD-1/PD-L1 blockade has demonstrated meaningful clinical responses and benefits in only a subset of patients. In addition, several severe and life-threatening adverse events were observed in these patients. Therefore, the identification of predictive biomarkers is urgently needed to select patients who are more likely to benefit from ICI therapy. PD-L1 expression level is the most commonly used biomarker in clinical practice for PD-1/PD-L1 inhibitors. However, negative PD-L1 expression cannot reliably exclude a response to a PD-1/PD-L1 blockade. Other factors, such as tumor microenvironment and other tumor genomic signatures, appear to impact the response to ICIs. In this review, we examine emerging data for novel biomarkers that may have a predictive value for optimizing the benefit from anti-PD-1/PD-L1 immunotherapy.

Dietary fiber and probiotics influence the gut microbiome and melanoma immunotherapy response

Gut bacteria modulate the response to immune checkpoint blockade (ICB) treatment in cancer, but the effect of diet and supplements on this interaction is not well studied. We assessed fecal microbiota profiles, dietary habits, and commercially available probiotic supplement use in melanoma patients and performed parallel preclinical studies. Higher dietary fiber was associated with significantly improved progression-free survival in 128 patients on ICB, with the most pronounced benefit observed in patients with sufficient dietary fiber intake and no probiotic use. Findings were recapitulated in preclinical models, which demonstrated impaired treatment response to anti–programmed cell death 1 (anti–PD-1)–based therapy in mice receiving a low-fiber diet or probiotics, with a lower frequency of interferon-γ–positive cytotoxic T cells in the tumor microenvironment. Together, these data have clinical implications for patients receiving ICB for cancer.

Tilsotolimod with Ipilimumab Drives Tumor Responses in Anti-PD-1 Refractory Melanoma

Many patients with advanced melanoma are resistant to immune checkpoint inhibition. In the ILLUMINATE-204 phase I/II trial, we assessed intratumoral tilsotolimod, an investigational Toll-like receptor 9 agonist, with systemic ipilimumab in patients with anti-PD-1- resistant advanced melanoma. In all patients, 48.4% experienced grade 3/4 treatment-emergent adverse events. The overall response rate at the recommended phase II dose of 8 mg was 22.4%, and an additional 49% of patients had stable disease. Responses in noninjected lesions and in patients expected to be resistant to ipilimumab monotherapy were observed. Rapid induction of a local IFNα gene signature, dendritic cell maturation and enhanced markers of antigen presentation, and T-cell clonal expansion correlated with clinical response. A phase III clinical trial with this combination (NCT03445533) is ongoing. SIGNIFICANCE: Despite recent developments in advanced melanoma therapies, most patients do not experience durable responses. Intratumoral tilsotolimod injection elicits a rapid, local type 1 IFN response and, in combination with ipilimumab, activates T cells to promote clinical activity, including in distant lesions and patients not expected to respond to ipilimumab alone.This article is highlighted in the In This Issue feature, p. 1861.

Tumor Mutational Burden as a Potential Biomarker for Immunotherapy in Pancreatic Cancer: Systematic Review and Still-Open Questions

Simple Summary

Tumor mutational burden (TMB) represents the number of mutations per megabase (muts/Mb) harbored by tumor cells in a given neoplasm, and can be determined with next-generation sequencing. High values are an indicator of potential response to immunotherapy. With this systematic review, we assessed its role in pancreatic ductal adenocarcinoma (PDAC). Our main findings can be summarized as: (i) high-TMB can be found in about 1% of PDAC; (ii) it is associated with mucinous/colloid and medullary histology; (iii) high-TMB PDAC frequently harbor other actionable alterations, with microsatellite instability as the most common; (iv) immunotherapy has shown promising results in high-TMB PDAC.

Abstract

Tumor mutational burden (TMB) is a numeric index that expresses the number of mutations per megabase (muts/Mb) harbored by tumor cells in a neoplasm. TMB can be determined using different approaches based on next-generation sequencing. In the case of high values, it indicates a potential response to immunotherapy. In this systematic review, we assessed the potential predictive role of high-TMB in pancreatic ductal adenocarcinoma (PDAC), as well as the histo-molecular features of high-TMB PDAC. High-TMB appeared as a rare but not-negligible molecular feature in PDAC, being present in about 1.1% of cases. This genetic condition was closely associated with mucinous/colloid and medullary histology (p < 0.01). PDAC with high-TMB frequently harbored other actionable alterations, with microsatellite instability/defective mismatch repair as the most common. Immunotherapy has shown promising results in high-TMB PDAC, but the sample size of high-TMB PDAC treated so far is quite small. This study highlights interesting peculiarities of PDAC harboring high-TMB and may represent a reliable starting point for the assessment of TMB in the clinical management of patients affected by pancreatic cancer.

Challenges in bioinformatics approaches to tumor mutation burden analysis

Several immune checkpoint inhibitors (ICIs) have already been introduced into clinical practice or are in advanced phases of clinical experimentation. Extensive efforts are being made to identify robust biomarkers to select patients who may benefit from treatment with ICIs. Tumor mutation burden (TMB) may be a relevant biomarker of response to ICIs in different tumor types; however, its clinical use is challenged by the analytical methods required for its evaluation. The possibility of using targeted next-generation sequencing panels has been investigated as an alternative to the standard whole exome sequencing approach. However, no standardization exists in terms of genes covered, types of mutations included in the estimation of TMB, bioinformatics pipelines for data analysis, and cut-offs used to discriminate samples with high, intermediate or low TMB. Bioinformatics serve a relevant role in the analysis of targeted sequencing data and its standardization is essential to deliver a reliable test in clinical practice. In the present study, cultured and formalin-fixed, paraffin-embedded cell lines were analyzed using a commercial panel for TMB testing; the results were compared with data from the literature and public databases, demonstrating a good correlation. Additionally, the correlation between high tumor mutation burden and microsatellite instability was confirmed. The bioinformatics analyses were conducted using two different pipelines to highlight the challenges associated with the development of an appropriate analytical workflow.

The genetic and epigenetic basis of distinct melanoma types

Melanoma represents the deadliest skin cancer. Recent therapeutic developments, including targeted and immune therapies have revolutionized clinical management and improved patient outcome. This progress was achieved by rigorous molecular and functional studies followed by robust clinical trials. The identification of key genomic alterations and gene expression profiles have propelled the understanding of distinct characteristics within melanoma subtypes. The aim of this review is to summarize and highlight the main genetic and epigenetic findings of melanomas and highlight their pathological and therapeutic importance.

PD-1/PD-L1 in Cancer: Pathophysiological, Diagnostic and Therapeutic Aspects

Immune evasion is a key strategy adopted by tumor cells to escape the immune system while promoting their survival and metastatic spreading. Indeed, several mechanisms have been developed by tumors to inhibit immune responses. PD-1 is a cell surface inhibitory receptor, which plays a major physiological role in the maintenance of peripheral tolerance. In pathological conditions, activation of the PD-1/PD-Ls signaling pathway may block immune cell activation, a mechanism exploited by tumor cells to evade the antitumor immune control. Targeting the PD-1/PD-L1 axis has represented a major breakthrough in cancer treatment. Indeed, the success of PD-1 blockade immunotherapies represents an unprecedented success in the treatment of different cancer types. To improve the therapeutic efficacy, a deeper understanding of the mechanisms regulating PD-1 expression and signaling in the tumor context is required. We provide an overview of the current knowledge of PD-1 expression on both tumor-infiltrating T and NK cells, summarizing the recent evidence on the stimuli regulating its expression. We also highlight perspectives and limitations of the role of PD-L1 expression as a predictive marker, discuss well-established and novel potential approaches to improve patient selection and clinical outcome and summarize current indications for anti-PD1/PD-L1 immunotherapy.

Find the Flame: Predictive Biomarkers for Immunotherapy in Melanoma

Immunotherapy has revolutionized the therapeutic landscape of melanoma. In particular, checkpoint inhibition has shown to increase long-term outcome, and, in some cases, it can be virtually curative. However, the absence of clinically validated predictive biomarkers is one of the major causes of unpredictable efficacy of immunotherapy. Indeed, the availability of predictive biomarkers could allow a better stratification of patients, suggesting which type of drugs should be used in a certain clinical context and guiding clinicians in escalating or de-escalating therapy. However, the difficulty in obtaining clinically useful predictive biomarkers reflects the deep complexity of tumor biology. Biomarkers can be classified as tumor-intrinsic biomarkers, microenvironment biomarkers, and systemic biomarkers. Herein we review the available literature to classify and describe predictive biomarkers for checkpoint inhibition in melanoma with the aim of helping clinicians in the decision-making process. We also performed a meta-analysis on the predictive value of PDL-1.

Analysis of tumor mutation burden combined with immune infiltrates in endometrial cancer

BACKGROUND

Tumor mutational burden (TMB) is widely regarded as a predictor of response to immunotherapy. Few researchers have focused on the activity and prognosis of TMB in endometrial cancer (EC) and immune cells. Our study aimed to identify the prognostic role of TMB in EC.

METHODS

We downloaded transcriptome data from The Cancer Genome Atlas (TCGA) database. Kaplan-Meier analysis with log-rank test was conducted to assess the difference in overall survival (OS) between the high and low TMB groups. The "CIBERSORT" scripts were performed to evaluate the immune compositions of EC patients. Cox regression analysis and survival analysis were used to verify the prognostic value prognosis of TMB.

RESULTS

We obtained the single nucleotide mutation data for 529 EC patients. A missense mutation was the most common mutation type. TMB was associated with survival outcome, tumor grades, and pathological types. We identified 10 hub TMB-related signature and found that elevated T-cell subsets infiltrating density in the high TMB group revealed improved survival outcomes. According to Kaplan-Meier analysis, T cells gamma delta and T cells regulatory were prognostic immune cells in EC samples. Moreover, many top gene set enrichment analysis (GSEA) results, including amino sugar and nucleotide sugar metabolism, nucleotide excision repair, or p53 signaling pathway, were enriched significantly with TMB level as phenotype.

CONCLUSIONS

TMB is an important prognostic factor for EC, and TMB-related genes may be potential therapeutic targets for EC.

Immunotherapy in non-small cell lung cancer: Update and new insights

BACKGROUND

The treatment of non-small-cell lung carcinoma (NSCLC) has changed markedly in recent years as a result of two major treatment milestones: Targeted therapy and immunotherapy. Since 2015, immunotherapy has been changing the paradigm of NSCLC treatment in different settings and has contributed to improve the quality of life of these patients. The most widely used immunotherapy strategy in clinical practice is currently PD-1 and CTLA-4 immune checkpoint inhibition-based immunotherapy. Initial successful results came from an improvement in overall survival for pretreated patients, and immunotherapy subsequently moved to a first-line palliative setting as monotherapy, in combination with chemotherapy or as double-checkpoint inhibition. With regard to earlier stages, consolidation immunotherapy after chemoradiation has also changed the paradigm of unresectable NSCLC, with marked benefits in terms of disease-free and overall survival. During the last few years, efforts have focused on the introduction of immunotherapy in earlier stages as neoadjuvant treatment for potentially resectable tumors and in an adjuvant setting, with some very promising results.

AIM

In this manuscript, we provide both an agile and thorough review of the role of immunotherapy in non-small cell lung cancer, a critical analysis of the most important studies, current indications, the role of biomarkers, new insights, and future challenges.

RELEVANCE FOR PATIENTS

Immunotherapy has revolutionized the treatment of non-small cell lung cancer patients reaching better survival outcomes in first and second palliative setting and in unresectable stage III tumors. Next year's immunotherapy will also introduce in earlier stages. Through an extensive knowledge of the mechanisms of action and of immunotherapy-based studies, the best treatment alternative can be offered to patients, helping to improve their survival and cure rates.

The Challenges of Tumor Mutational Burden as an Immunotherapy Biomarker

Tumor mutational burden (TMB) reflects cancer mutation quantity. Mutations are processed to neo-antigens and presented by major histocompatibility complex (MHC) proteins to T cells. To evade immune eradication, cancers exploit checkpoints that dampen T cell reactivity. Immune checkpoint inhibitors (ICIs) have transformed cancer treatment by enabling T cell reactivation; however, response biomarkers are required, as most patients do not benefit. Higher TMB results in more neo-antigens, increasing chances for T cell recognition, and clinically correlates with better ICI outcomes. Nevertheless, TMB is an imperfect response biomarker. A composite predictor that also includes critical variables, such as MHC and T cell receptor repertoire, is needed.

Recent advances and future perspectives in adjuvant and neoadjuvant immunotherapies for lung cancer

The superior efficacy of immune checkpoint inhibitors for the treatment of advanced non-small cell lung cancer has inspired many clinical trials to use immune checkpoint inhibitors in earlier stages of lung cancer worldwide. Based on the theoretical feasibility that neoantigens derived from a tumor tissue are present in vivo, some clinical trials have recently evaluated the neoadjuvant, rather than the adjuvant, use of immune checkpoint inhibitors. Some of these trials have already produced evidence on the safety and efficacy of immune checkpoint inhibitors in a neoadjuvant setting, with a favorable major pathologic response and few adverse events. In the most impactful report from Johns Hopkins University and the Memorial Sloan Kettering Cancer Center, the programed death-1 inhibitor nivolumab was administered to 21 patients in a neoadjuvant setting. The authors reported a major pathologic response rate of 45%, with no unexpected delay of surgery related to the adverse effects of nivolumab. The adjuvant as well as the neoadjuvant administration of immune checkpoint inhibitors has also been considered in various clinical trials, with or without the combined use of chemotherapy or radiotherapy. The development of appropriate biomarkers to predict the efficacy of immune checkpoint inhibitors is also underway. The expression of programed death ligand-1 and the tumor mutation burden are promising biomarkers that have been evaluated in many settings. To establish an appropriate method for using immune checkpoint inhibitors in combination with surgery, the Lung Cancer Surgical Study Group of the Japan Clinical Oncology Group will manage clinical trials using a multimodality treatment, including immune checkpoint inhibitors and surgery.

Predictive value of tumor mutation burden (TMB) with targeted next-generation sequencing in immunocheckpoint inhibitors for non-small cell lung cancer (NSCLC)

Background: To evaluate the clinical predictive value of tumor mutation burden (TMB) for immune checkpoint inhibitor (ICI) therapy in patients with non-small cell lung cancer (NSCLC).

Method: As of 15 February 2020, PubMed, PMC and EMBASE databases as well as the American society of clinical oncology (ASCO) and European society of medical oncology (ESMO) databases were searched. The Mantel-Haenszel or inverse variance weighted fixed-effects model (I² ≤ 50%) or random-effects model (I² > 50%) were used to evaluate OR and its 95% CI of objective response rate (ORR) and disease control rate (DCR) , as well as HR and its 95% CI of progression-free survival (PFS) and overall survival (OS). In addition, we did publication bias, heterogeneity analysis, sensitivity analysis and subgroup analysis. And quality of the studies included and the level of evidence for outcome measures were evaluated.

Results: 14 studies involving 2872 patients were included. The ORR (OR 3.52, 95%CI 2.32-5.35, p < 0.00001), DCR (OR 3.26, 95%CI 1.91-5.55, p < 0.0001), PFS (HR 0.81, 95%CI 0.74-0.89, p < 0.00001) and OS (HR 0.83, 95%CI 0.74-0.94, p = 0.002) of ICI therapy in the high TMB group were all superior to those in the low TMB group.

Conclusions: TMB is a promising biomarker, which can predict the efficacy of ICI therapy in advanced NSCLC patients, included ORR, DCR, PFS and OS.

Association of tumor mutation burden and epidermal growth factor receptor inhibitor history with survival in patients with metastatic stage III/IV non-small-cell lung cancer: A retrospective study

OBJECTIVES

Lung cancer is the leading cause of cancer-related deaths worldwide. However, factors associated with the survival of patients with advanced non-small-cell lung cancer (NSCLC) who received only hospice care are largely unclear. In this study, we aimed to determine the prognostic factors correlated with survival in patients with advanced NSCLC who had undergone hospice care only.

METHODS

A total of 102 patients with recurrent stage III/IV NSCLC after traditional treatment failure were investigated. Survival was measured from the date of enrollment to December 2019 or the time of death. Tumor tissues were collected, and DNA sequencing was performed to identify somatic mutations. Data on clinical factors of patients were collected and analyzed by univariate and multivariate analyses. Overall survival analysis was conducted using the Kaplan-Meier method.

RESULTS

The 6-month, 1-year, and 2-year overall survival rates of the 102 patients with metastatic NSCLC were 17.65%, 3.92%, and 0.98%, respectively. The median overall survival of the 102 patients was 3.15 months. Tumor location in the peripheral lung, epidermal growth factor receptor (EGFR) inhibitor history, low tumor mutation load, adenocarcinoma, and poor performance status score were associated with prolonged survival compared with tumor location in the central lung, no EGFR inhibitor history, high tumor mutation load, squamous cell carcinoma, and good performance status score (p=0.045, p=0.003, p=0.045, p=0.021, and p=0.0003, respectively).

CONCLUSIONS

EGFR inhibitor treatment history and tumor mutation load are risk factors for the overall survival of patients with stage III/IV NSCLC who have undergone only hospice care. These results provide a critical clinical basis for further study of nontraditional anti-tumor responses induced by EGFR inhibitors.

Immune Profiling of Advanced Thyroid Cancers Using Fluorescent Multiplex Immunohistochemistry

Background: Advanced thyroid cancers, including differentiated thyroid carcinoma (DTC) with distant metastasis, and anaplastic thyroid carcinoma (ATC), are associated with poor clinical outcomes and limited treatment options. This study aimed to determine the immune profiles of advanced thyroid cancers using fluorescent multiplex immunohistochemistry (F-MIHC) and multispectral imaging (MSI). Methods: Twenty-eight tissue samples were collected from 12 patients who had DTC with distant metastasis and from 16 with ATC. The samples were assessed using F-MIHC and MSI with antibodies against the cell surface molecules, cluster of differentiation (CD)4, CD8, programmed cell death-1 (PD-1), PD ligand 1 (PD-L1), forkhead box protein 3, and cytokeratin (CK). The expression of PD-L1 was evaluated using tumor proportion score (TPS) and combined positive score (CPS). Results: Significantly, more PD-L1-positive tumor cells (CK⁺PD-L1⁺) per mm² were found in ATC samples than in DTC samples (183.5 vs. 0.03, p < 0.001). Lymphocyte infiltration was significantly increased in ATC compared with DTC, with significantly more PD-L1- or PD-1-positive lymphocytes in ATC samples than in DTC samples. The TPS and CPS for PD-L1 expression were negative in all DTC samples but positive in 81% and 94% of ATC samples, respectively. Conclusions: Immune profiling revealed significant differences between advanced DTC and ATC, particularly in terms of PD-L1 expression and lymphocyte infiltration. Therefore, immune profiling using F-MIHC and MSI can provide invaluable information regarding tumor microenvironments, which could help select candidates for immunotherapy.

A genomic signature for accurate classification and prediction of clinical outcomes in cancer patients treated with immune checkpoint blockade immunotherapy

Tumor mutational burden (TMB) is associated with clinical response to immunotherapy, but application has been limited to a subset of cancer patients. We hypothesized that advanced machine-learning and proper modeling could identify mutations that classify patients most likely to derive clinical benefits. Training data: Two sets of public whole-exome sequencing (WES) data for metastatic melanoma. Validation data: One set of public non-small cell lung cancer (NSCLC) data. Least Absolute Shrinkage and Selection Operator (LASSO) machine-learning and proper modeling were used to identify a set of mutations (biomarker) with maximum predictive accuracy (measured by AUROC). Kaplan-Meier and log-rank methods were used to test prediction of overall survival. The initial model considered 2139 mutations. After pruning, 161 mutations (11%) were retained. An optimal threshold of 0.41 divided patients into high-weight (HW) or low-weight (LW) TMB groups. Classification for HW-TMB was 100% (AUROC = 1.0) on melanoma learning/testing data; HW-TMB was a prognostic marker for longer overall survival. In validation data, HW-TMB was associated with survival (p = 0.0057) and predicted 6-month clinical benefit (AUROC = 0.83) in NSCLC. In conclusion, we developed and validated a 161-mutation genomic signature with "outstanding" 100% accuracy to classify melanoma patients by likelihood of response to immunotherapy. This biomarker can be adapted for clinical practice to improve cancer treatment and care.

Pathogenic germline variants are associated with poor survival in stage III/IV melanoma patients

Patients with late stage resected cutaneous melanoma have poor overall survival (OS) and experience irreversible adverse events from systemic therapy. There is a clinical need to identify biomarkers to predict outcome. Performing germline/tumour whole-exome sequencing of 44 stage III/IV melanoma patients we identified pathogenic germline mutations in CDKN2A, CDK4, ATM, POLH, MRE11A, RECQL4 and XPC, affecting 7/44 patients. These mutations were associated with poor OS (p = 0.0082). We confirmed our findings in The Cancer Genome Atlas (TCGA) human skin cutaneous melanoma cohort where we identified pathogenic variants in 40/455 patients (p = 0.0203). Combining these cohorts (n = 499) further strengthened these findings showing germline carriers had worse OS (p = 0.0009). Additionally, we determined whether tumour mutation burden (TMB) or BRAF status were prognostic markers of survival. Low TMB rate (< 20 Mut/Mb; p = 0.0034) and BRAF p.V600 mutation (p = 0.0355) were associated with worse progression-free survival. Combining these biomarkers indicated that V600 mutant patients had significantly lower TMB (p = 0.0155). This was confirmed in the TCGA (n = 443, p = 0.0007). Integrative analysis showed germline mutation status conferred the highest risk (HR 5.2, 95% CI 1.72–15.7). Stage IV (HR 2.5, 0.74–8.6) and low TMB (HR 2.3, 0.57–9.4) were similar, whereas BRAF V600 status was the weakest prognostic biomarker (HR 1.5, 95% CI 0.44–5.2).

Morphological, immune and genetic features in biopsy sample associated with the efficacy of pembrolizumab in patients with non-squamous non-small cell lung cancer

INTRODUCTION

The usefulness of the histopathology of biopsy samples for predicting the efficacy of immunotherapy in non-squamous, non-small cell lung cancer (NSq NSCLC) patients remains unclear.

METHODS

We retrospectively investigated the associations between the histopathological features in biopsy samples and survival outcomes in advanced NSq NSCLC patients receiving pembrolizumab. NSq NSCLC was classified histopathologically as morphological adenocarcinoma or non-small cell carcinoma (NSCC: absence of definitive features of either adenocarcinoma or a squamous morphology). We investigated the association between the tumor morphological features and immune/genetic features by examining the tumor PD-L1 expression and tumor mutation burden (TMB).

RESULTS

Among 33 advanced NSq NSCLC patients with tumor PD-L1 scores ≥ 50% receiving pembrolizumab as first-line therapy, a biopsy diagnosis of NSCC was associated with a significantly longer progression-free survival [median 16.8 vs. 2.3 months; hazard ratio (HR) 0.26; 95% CI 0.10-0.62, P = 0.01] and overall survival (median NR vs. 10.1 months; HR 0.35; 0.12-0.97, P = 0.04) as compared to that of morphological adenocarcinoma. In an analysis of 367 biopsy samples, the NSCC group showed a higher percentage of samples with PD-L1 scores ≥ 50% than the morphological adenocarcinoma group (35% vs. 10%). The NSCC group (n = 8) also showed a significantly higher TMB than the morphological adenocarcinoma group (n = 7) (median 236 vs. 25 mutations/whole exome, P = 0.01).

CONCLUSION

Absence of definitive morphological features in a biopsy sample could be a useful predictor of the efficacy of pembrolizumab in NSq NSCLC patients with tumor PD-L1 scores ≥ 50%, as these tumors are likely to show high tumor PD-L1 expression and high TMB.

Integrated genomic analysis identifies a genetic mutation model predicting response to immune checkpoint inhibitors in melanoma

Several biomarkers such as tumor mutation burden (TMB), neoantigen load (NAL), programmed cell‐death receptor 1 ligand (PD‐L1) expression, and lactate dehydrogenase (LDH) have been developed for predicting response to immune checkpoint inhibitors (ICIs) in melanoma. However, some limitations including the undefined cut‐off value, poor uniformity of test platform, and weak reliability of prediction have restricted the broad application in clinical practice. In order to identify a clinically actionable biomarker and explore an effective strategy for prediction, we developed a genetic mutation model named as immunotherapy score (ITS) for predicting response to ICIs therapy in melanoma, based on whole‐exome sequencing data from previous studies. We observed that patients with high ITS had better durable clinical benefit and survival outcomes than patients with low ITS in three independent cohorts, as well as in the meta‐cohort. Notably, the prediction capability of ITS was more robust than that of TMB. Remarkably, ITS was not only an independent predictor of ICIs therapy, but also combined with TMB or LDH to better predict response to ICIs than any single biomarker. Moreover, patients with high ITS harbored the immunotherapy‐sensitive characteristics including high TMB and NAL, ultraviolet light damage, impaired DNA damage repair pathway, arrested cell cycle signaling, and frequent mutations in NF1 and SERPINB3/4. Overall, these findings deserve prospective investigation in the future and may help guide clinical decisions on ICIs therapy for patients with melanoma.

Understanding Response to Immunotherapy Using Standard of Care and Experimental Imaging Approaches

Immunotherapy has emerged as a standard of care in the treatment of a wide variety of malignancies, and it may be used in combination with other treatments including surgery, radiation, and chemotherapy. However, a patient's imaging response to immunotherapy can be confounded by a variety of factors, including the appearance of pseudoprogression or the development of immune-related adverse events. In these situations, the immune response itself can mimic disease progression, potentially causing confusion in assessment and determination of further treatment. To address these challenges, a variety of approaches have been proposed to improve response assessment. First, revised definitions of response criteria, accounting for the appearance of pseudoprogression, can improve specificity of assessment. Second, advanced image processing including radiomics and machine learning analysis can be used to further analyze standard of care imaging data. In addition, new molecular imaging techniques can be used to directly interrogate immune cell activity or study aspects of the tumor microenvironment. These approaches have promise for improving the understanding of the response to immunotherapy and improving patient care.

Tumor mutation burden in Chinese cancer patients and the underlying driving pathways of high tumor mutation burden across different cancer types

Background

Tumor mutation burden (TMB) has an important association with immunotherapy responses. TMB in the Chinese population has not been well established. Finding differences between the Chinese and Caucasian populations and elucidating the underlying biological mechanisms of high TMB might help develop more precise and effective means for TMB and immunotherapy response prediction.

Methods

Chinese cancer patients fresh tissue (n=2,177), formalin-fixed, paraffin-embed (FFPE) specimens (n=3,294), and pleural fluid (n=189) were profiled using a 295- or 520-gene next-generation sequencing (NGS) panel. The association of the TMB status with a series of molecular features and biological pathways was determined using bootstrapping.

Results

TMB, measured by 295- or 520-cancer-related gene panels, was correlated with whole-exome sequencing (WES) TMB based on the in silico simulation in The Cancer Genome Atlas cohort. The median TMB of our data was slightly higher than that from the Foundation Medicine Inc. (FMI) dataset. TMB was also slightly different within the same cancer type between the Chinese and Caucasian population. We discovered that the underlying pathways of TMB status varied greatly and sometimes had an opposite association with TMB across different cancer types. Moreover, we developed a 23-gene and a 16-gene signature to predict TMB prediction for lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC), respectively, indicating a histology-specific mechanism for driving high-TMB in lung cancer.

Conclusions

TMB varies among different ethnic populations. Our findings extend the knowledge of the underlying biological mechanisms for high TMB and might be helpful for developing more precise and accessible TMB assessment panels and algorithms in more cancer types.

Identification of relapse-associated gene mutations by next-generation sequencing in low-risk acute myeloid leukaemia patients

Recommended genetic categorization of acute myeloid leukaemias (AML) includes a favourable-risk category, but not all these patients have good prognosis. Here, we used next-generation sequencing to evaluate the mutational profile of 166 low-risk AML patients: 30 core-binding factor (CBF)-AMLs, 33 nucleophosmin (NPM1)-AMLs, 4 biCEBPα-AMLs and 101 acute promyelocytic leukaemias (APLs). Functional categories of mutated genes differed among subgroups. NPM1-AMLs showed frequent variations in DNA-methylation genes (DNMT3A, TET2, IDH1/2) (79%), although without prognostic impact. Within this group, splicing-gene mutations were an independent factor for relapse-free (RFS) and overall survival (OS). In CBF-AML, poor independent factors for RFS and OS were mutations in RAS pathway and cohesin genes, respectively. In APL, the mutational profile differed according to the risk groups. High-risk APLs showed a high mutation rate in cell-signalling genes (P = 0·002), highlighting an increased incidence of FLT3 internal tandem duplication (ITD) (65%, P < 0·0001). Remarkably, in low-risk APLs (n = 28), NRAS mutations were strongly correlated with a shorter five-year RFS (25% vs. 100%, P < 0·0001). Overall, a high number of mutations (≥3) was the worst prognostic factor RFS (HR = 2·6, P = 0·003). These results suggest that gene mutations may identify conventional low-risk AML patients with poor prognosis and might be useful for better risk stratification and treatment decisions.

PD-1/PD-L1 Blockade Therapy in Advanced Non-Small-Cell Lung Cancer: Current Status and Future Directions

This article summarizes the latest clinical applications of PD‐1/PD‐L1 blockade therapy in advanced non‐small cell lung cancer (NSCLC) worldwide and in China, reporting the bottlenecks related to the use of this therapy in clinic. An exploration of the underlying mechanism of PD‐1/PD‐L1 blockade therapy and biomarker identification will maximize the application of immune checkpoint inhibitors in advanced NSCLC and facilitate bedside‐to‐bench studies in cancer immunotherapy.

The use of immune checkpoint inhibitors (ICIs) has become one of the most promising approaches in the field of cancer therapy. Unlike the current therapies that target tumor cells, such as chemotherapy, radiotherapy, or targeted therapy, ICIs directly restore the exhausted host antitumor immune responses mediated by the tumors. Among multiple immune modulators identified, the programmed cell death protein 1 (PD‐1)/programmed cell death protein ligand 1 (PD‐L1) axis leading to the exhaustion of T‐cell immunity in chronic infections and tumors has been widely investigated. Therefore, blocking antibodies targeting PD‐1 or PD‐L1 have been developed and approved for the treatment of various advanced cancers, including non‐small‐cell lung cancer (NSCLC), making them the most successful ICIs. Compared with chemotherapy or radiotherapy, PD‐1/PD‐L1 blockade therapy significantly improves the durable response rate and prolongs long‐term survival with limited adverse effects in both monotherapy and combination therapy for advanced NSCLC. However, extensive challenges exist for further clinical applications, such as a small fraction of benefit population, primary and acquired resistance, the lack of predictive and prognostic biomarkers, and treatment‐related adverse effects. In this article, we summarize the latest clinical applications of PD‐1/PD‐L1 blockade therapy in advanced NSCLC worldwide, as well as in China, and discuss the bottlenecks related to the use of this therapy in clinical practice. An exploration of the underlying mechanism of PD‐1/PD‐L1 blockade therapy and biomarker identification will maximize the application of ICIs in advanced NSCLC and facilitate bedside‐to‐bench studies in cancer immunotherapy as well.

Implications for Practice.

Immune checkpoint inhibitors (ICIs) targeting programmed cell death protein 1 (PD‐1) and programmed cell death protein ligand 1 (PD‐L1) display apparent benefits for the treatment of advanced non‐small‐cell lung cancer (NSCLC). However, the clinical applications of these therapies are challenged by the limited benefit population with additional high economic burden and adverse events. This review discusses the bottlenecks of ICI therapy in clinical practice and provides appropriate guidance in the development of predictive biomarkers, the establishment of the criteria for combining PD‐1/PD‐L1 blockade therapy with the existing therapies, and the management of adverse events observed both in monotherapy and combination therapy, which will help maximize the applications of ICIs in advanced NSCLC.

Tumor Mutational Burden From Tumor-Only Sequencing Compared With Germline Subtraction From Paired Tumor and Normal Specimens

IMPORTANCE

Tumor mutation burden (TMB) is an emerging factor associated with survival with immunotherapy. When tumor-normal pairs are available, TMB is determined by calculating the difference between somatic and germline sequences. In the case of commonly used tumor-only sequencing, additional steps are needed to estimate the somatic alterations. Computational tools have been developed to determine germline contribution based on sample copy state, purity estimates, and occurrence of the variant in population databases; however, there is potential for sampling bias in population data sets.

OBJECTIVE

To investigate whether tumor-only filtering approaches overestimate TMB.

DESIGN, SETTING, AND PARTICIPANTS

This was a retrospective cohort study of 50 tumor samples from 10 different tumor types. A 595-gene panel test was used to assess TMB by adding all missense, indels, and frameshift variants with an allelic fraction of at least 5% and coverage of at least 100× within each tumor. Tumor-only TMB was evaluated against the criterion standard of matched germline-subtracted TMB at 3 levels. Level 1 removed all the tumor-only variants with allelic fraction of at least 1% in the Exome Aggregation Consortium database (with the Cancer Genome Atlas cohort removed). Level 2 removed all variants observed in population databases, simulating a naive approach of removing germline variation. Level 3 used an internal tumor-only pipeline for calculating TMB. These specimens were processed with a commercially available panel, and results were analyzed at the Mayo Clinic. Data were analyzed between December 1, 2018, and May 28, 2019.

MAIN OUTCOMES AND MEASURES

Tumor mutation burden per megabase (Mb) as determined by 3 levels of filtering and germline subtraction.

RESULTS

There were significantly higher estimates of TMB with level 1 (median [range] mutations per Mb, 28.8 [17.5-67.1]), level 2 (median [range] mutations per Mb, 20.8 [10.4-30.8]), and level 3 (median [range] mutations per Mb, 3.8 [0.8-12.1]) tumor-only filtering approaches than those determined by germline subtraction (median [range] mutations per Mb, 1.7 [0.4-9.2]). There were no strong associations between TMB estimates and tumor-germline TMB for level 1 filtering (r = 0.008; 95% CI, -0.004 to 0.020), level 2 filtering (r = 0.018; 95% CI, 0.003 to 0.033), or level 3 filtering (r = 0.54; 95% CI, 0.36 to 0.68).

CONCLUSIONS AND RELEVANCE

The findings of this study indicate that tumor-only approaches that filter variants in population databases can overestimate TMB compared with germline subtraction methods. Despite improved association with more stringent filtering approaches, these falsely elevated estimates may result in the inappropriate categorization of tumor specimens and negatively affect clinical trial results and patient outcomes.

Genetic Profiling of Advanced Melanoma: Candidate Mutations for Predicting Sensitivity and Resistance to Targeted Therapy

BACKGROUND

Molecularly targeted therapy has revolutionized the treatment of advanced melanoma. However, despite its high efficiency, a majority of patients experience relapse within 1 year of treatment because of acquired resistance, and approximately 10-25% patients gain no benefit from these agents owing to intrinsic resistance. This is mainly caused by the genetic heterogeneity of melanoma cells.

OBJECTIVE

We aimed to validate the predictive significance of selected genes in advanced melanoma patients before treatment with BRAF/MEK inhibitors.

PATIENTS AND METHODS

Archival DNA derived from 37 formalin-fixed paraffin-embedded pre-treatment advanced melanoma samples of patients treated with targeted therapy was used for next-generation sequencing analysis using the Ion Torrent platform. The AmpliSeq Custom Panel comprised coding sequences or hot spots of 23 melanoma genes: ATM, BRAF, CDK4, CDKN2A, CTNNB1, EGFR, HOXD8, HRAS, IDH1, KIT, KRAS, MAP3K8, MAP2K1, MAP2K2, MITF, MYC, NF1, NRAS, PAX5, PIK3R1, PTEN, RAC1, and RB1. The sequences were evaluated for genomic alterations and further validated using Sanger sequencing.

RESULTS

Our analysis revealed non-BRAF genetic alterations in 28 out of 37 samples (75.7%). Genetic changes were identified in PTEN, CDK4, CDKN2A, CTNNB1, EGFR, HOXD8, HRAS, KIT, MAP2K1, MAP2K2, MITF, MYC, NF1, PAX5, RAC1, and RB1. Fifteen known pathogenic mutations (single nucleotide variants or indels) and 11 variants of unknown significance were detected. Statistical analysis revealed an association between the presence of pathogenic mutations and time to progression during treatment with combination therapy.

CONCLUSIONS

Pathogenic mutations identified by gene panel sequencing have potential predictive value for targeted therapy of melanoma and are worth further validation in a larger series of cases. The role of some known mutations (e.g. CDK4R24, PTEN c.801 + 1G > A, CTNNB1S45F) as well as variants of unknown significance identified in this study (e.g. MITFR316K, KITG498S) in the generation of resistance to BRAF/MEK inhibitors should be further investigated.

Targeted literature review on use of tumor mutational burden status and programmed cell death ligand 1 expression to predict outcomes of checkpoint inhibitor treatment

Background

To achieve optimal outcomes, an individual approach is needed in the treatment and care of patients. The potential value of tumor mutational burden (TMB) status and/or programmed cell death ligand 1 (PD-L1) expression as biomarkers to predict which patients are most likely to respond to checkpoint inhibitors has been explored in many studies. The goal of this targeted literature review is to identify data available for TMB status and/or PD-L1 expression that predict response to checkpoint inhibitors and/or anti–cytotoxic T-lymphocyte–associated protein 4 (CTLA-4) antibodies.

Methods

Targeted literature searches were performed using electronic medical databases (MEDLINE, Embase, and BIOSIS) and internet searches of specified sites. Bibliographies of key systematic literature reviews and meta-analyses also were reviewed for studies of interest.

Results

The review identified 27 studies of non-small cell lung cancer (NSCLC), 40 studies of melanoma, 10 studies of urothelial cancer, and 5 studies of renal cell cancer indications. Studies also were identified in other cancer types, e.g., colorectal, breast, gastric, and Merkel cell cancer and squamous-cell carcinoma of the head and neck.

Twelve trials, including six in NSCLC and four in melanoma, evaluated TMB as a predictor of outcomes. A TMB of ≥10 mutations per megabase was shown to be an effective biomarker in the CheckMate 227 study. PD-L1 expression was included in the majority of identified studies and was found to predict response in in melanoma and in all types of NSCLC. Prediction of response was not a prespecified analysis in some studies; others had small sample sizes and wide confidence intervals. A clear predictive trend for PD-L1 expression was not identified in renal, breast, gastric, or Merkel cell cancer.

Conclusion

Based on data contained in this review, assessment of TMB status and PD-L1 expression may help enhance the prediction of response to checkpoint inhibition in some tumors, such as NSCLC and melanoma. In this rapidly growing area of research, further exploratory biomarkers are being investigated including tumor-infiltrating lymphocytes, immune profiling (e.g., effector T cells or regulatory T cells), epigenetic signatures, T-cell receptor repertoire, proteomics, microbiome, and metabolomics.

Tumor Mutational Burden and Efficacy of Immune Checkpoint Inhibitors: A Systematic Review and Meta-Analysis

Tumor mutational burden (TMB) is a genomic biomarker that predicts favorable responses to immune checkpoint inhibitors (ICIs). Here, we set out to assess the predictive value of TMB on long-term survival outcomes in patients undergoing ICIs. We systematically searched PubMed, Embase, CENTRAL and clinicaltrials.gov from inception to 6 August 2019. We included retrospective studies or clinical trials of ICIs that reported hazard ratios (HRs) for overall survival (OS) and/or progression-free survival (PFS) according to TMB. Data on 5712 patients from 26 studies were included. Among patients who received ICIs, high TMB groups showed better OS (HR 0.53, 95% CI 0.42 to 0.67) and PFS (HR 0.52, 95% CI 0.40 to 0.67) compared to low TMB groups. In patients with high TMB, those who received ICIs had a better OS (HR 0.69, 95% CI 0.50 to 0.95) and PFS (HR = 0.66, 95% CI = 0.47 to 0.92) compared to those who received chemotherapy alone, while in patients with low TMB, such ICI benefits of OS or PFS were not statistically significant. In conclusion, TMB may be an effective biomarker to predict survival in patients undergoing ICI treatment. The role of TMB in identifying patient groups who may benefit from ICIs should be determined in future randomized controlled trials.

Tumor mutational burden in lung cancer: a systematic literature review

Purpose: To assess the association of tumor mutational burden (TMB) with clinical outcomes, other biomarkers and patient/disease characteristics in patients receiving therapy for lung cancer. Results: In total, 4,303 publications were identified; 81 publications were included. The majority of publications assessing clinical efficacy of immunotherapy reported an association with high TMB, particularly when assessing progression-free survival and objective response rate. High TMB was consistently associated with TP53 alterations, and negatively associated with EGFR mutations. High TMB was also associated with smoking, squamous cell non-small cell lung carcinoma, and being male. Methods: A systematic literature review based upon an a priori protocol was conducted following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and Cochrane methodologies. Searches were conducted in EMBASE, SCOPUS, Ovid MEDLINE®, and Emcare (from January 2012 until April 2018) and in two clinical trial registries. Conference abstracts were identified in EMBASE, and in targeted searches of recent major conference proceedings (from January 2016 until April 2018). Publications reporting data in patients receiving therapy for lung cancer that reported TMB and its association with clinical efficacy, or with other biomarkers or patient/disease characteristics, were included. Results are presented descriptively. Conclusion: This systematic literature review identified several clinical outcomes, biomarkers, and patient/disease characteristics associated with high TMB, and highlights the need for standardized definitions and testing practices. Further studies using standardized methodology are required to inform treatment decisions.

The Predictive Value of Tumor Mutation Burden on Efficacy of Immune Checkpoint Inhibitors in Cancers: A Systematic Review and Meta-Analysis

Background: Despite an increasing understanding about tumor mutation burden (TMB) in cancer immunity and cancer immunotherapy, the comprehensive cognition between TMB and efficiency of immune checkpoint inhibitors (ICIs) is still lacking. A systematic review and meta-analysis was conducted to evaluate the predictive value of TMB on efficacy of ICIs. Methods: Systematic literature search was conducted on PubMed, EMBASE, Web of Science and Cochrane Library up to June 16, 2019. Pooled odds ratio (OR) of objective response rate (ORR), hazard ratio (HR) of progression-free survival (PFS) and overall survival (OS) were estimated by inverse variance weighted fixed-effects model (I ² ≤ 50%) or DerSimonian-Laird random-effects model (I ² > 50%). In addition, heterogeneity analysis, sensitivity analysis, publication bias and subgroup analysis were conducted. Moreover, fractional polynomial regression was conducted to investigate the dose-response relationship between TMB cutoffs and efficacy of ICIs. Furthermore, we assessed ORR by TMB and programmed cell death ligand 1 (PD-L1) expression after layering each other in studies which the two could be both acquired. Results: Three thousand six hundred fifty-seven records were retrieved through database searching, and 29 studies with 4,431 patients were finally included in the meta-analysis. TMB high group had significantly improved ORR (pooled OR 3.31, 95% CI 2.61, 4.19, P < 0.001), PFS (pooled HR 0.59, 95% CI 0.49, 0.71, P < 0.001) and OS (pooled HR 0.68, 95% CI 0.53, 0.89, P = 0.004). Sensitivity analyses illustrated the results were stable, and publication bias was identified in ORR. Subgroup analyses showed the predictive value of TMB was significant in non-small-cell lung cancer (except for the OS) and melanoma. In addition, heterogeneity was substantial in targeted next generation sequencing group but tiny in whole exome sequencing group. Furthermore, TMB and PD-L1 expression were capable to predict improved ORR of ICIs after stratification of each other, with tiny heterogeneity. Conclusions: High tumor mutation burden predicted improved efficacy of immune checkpoint inhibitors in cancers, and targeted next generation sequencing for estimating tumor mutation burden in clinic should be standardized to eliminate heterogeneity in the future. Moreover, tumor mutation burden and programmed cell death ligand 1 expression were independent factors on predicting efficacy of immune checkpoint inhibitors.

Circulating biomarkers predictive of tumor response to cancer immunotherapy

Introduction: The advent of checkpoint blockade immunotherapy has revolutionized cancer treatment, but clinical response to immunotherapies is highly heterogeneous among individual patients and between cancer types. This represents a challenge to oncologists when choosing specific immunotherapies for personalized medicine. Thus, biomarkers that can predict tumor responsiveness to immunotherapies before and during treatment are invaluable. Areas covered: We review the latest advances in 'liquid biopsy' biomarkers for noninvasive prediction and in-treatment monitoring of tumor response to immunotherapy, focusing primarily on melanoma and non-small cell lung cancer. We concentrate on high-quality studies published within the last five years on checkpoint blockade immunotherapies, and highlight significant breakthroughs, identify key areas for improvement, and provide recommendations for how these diagnostic tools can be translated into clinical practice. Expert opinion: The first biomarkers proposed to predict tumor response to immunotherapy were based on PD1/PDL1 expression, but their predictive value is limited to specific cancers or patient populations. Recent advances in single-cell molecular profiling of circulating tumor cells and host cells using next-generation sequencing has dramatically expanded the pool of potentially useful predictive biomarkers. As immunotherapy moves toward personalized medicine, a composite panel of both genomic and proteomic biomarkers will have enormous utility in therapeutic decision-making.

Review and perspective on adjuvant and neoadjuvant immunotherapies in NSCLC

Postoperative patients have risk recurring, even for completed resected early stage non-small-cell lung cancer (NSCLC). To control the recurrence rate, neoadjuvant and adjuvant therapies have been applied widely in clinical practice; however, neoadjuvant and adjuvant immunotherapy clinical trials on NSCLC are still being explored. In this review, we summarized the research progress and outline the issues need to be solved on adjuvant and neoadjuvant immunotherapies in NSCLC.

Predictive Biomarkers for Checkpoint Immunotherapy: Current Status and Challenges for Clinical Application

Immune-checkpoint blockade (ICB), in particular PD-1 inhibition, has rapidly changed the treatment landscape and altered therapeutic paradigms across many tumor types, with unprecedented rates of durable clinical responses in a number of cancers. Despite this success, only a subset of patients responds to ICB and, as a result, predictive biomarkers would be useful to guide the selection of patients for these therapies. This article highlights currently used biomarkers, as well as several promising novel candidates, and also discusses the challenges involved in establishing their analytic validity and clinical utility. Progress is being evaluated in melanoma and non-small cell lung cancer, for which PD-1 ± CTLA-4 inhibitors have become standard therapy, to other malignancies for which PD-L1 inhibitors remain investigational. Although single biomarkers have substantial limitations, a combination of biomarkers that reflect the interaction of host and tumor will likely be needed to provide a reproducible surrogate for the benefit of checkpoint modulation. Cancer Immunol Res; 6(10); 1122-8. ©2018 AACR.

Developing a score system to predict therapeutic outcomes to anti-PD-1 immunotherapy in metastatic melanoma

BACKGROUND

Prognosis of patients with metastatic melanoma has improved due to the advent of antibodies targeting the programmed cell death protein-1 (PD-1). However, therapeutic outcomes from anti-PD-1 therapy widely differ among patients. Biomarkers for outcome are needed as these may influence patient selection and treatment decision.

METHODS

Data of patients with metastatic melanoma treated with anti-PD-1 were retrospectively reviewed. Baseline biochemical (serum lactate dehydrogenase [LDH] levels, complete blood count) and clinical characteristics were evaluated to identify predictors of progression-free survival (PFS) and overall survival (OS). PFS and OS were assessed using Kaplan-Meier and Cox models. The comparison of predictive power of independent predictors for response to anti-PD-1 was evaluated by receiver operating characteristic (ROC) curves.

RESULTS

Overall, 173 patients were included. Low metastases burden, normal baseline LDH levels, and high relative lymphocyte count (RLC) were associated with favorable outcomes (p < 0.01). According to ROC curves, RLC >17.5% improved survival outcomes. PFS was 3.7 and 15.8 months for patients with RLC <17.5% and >17.5%, respectively (p = 0.004); OS was 5.0 and 33.6 months for patients with RLC <17.5% and >17.5%, respectively (p < 0.001). Stratification of patients according to these variables showed that survival outcomes strongly differ in patients with 3 of 3 compared to those with 2, 1, and none of these 3 factors present (p < 0.001).

CONCLUSIONS

Metastases burden, LDH levels, and RLC are independent baseline characteristics associated with outcome in patients with melanoma receiving anti-PD-1. Further investigations are needed to clarify if evaluation of these parameters can translate into clinical strategy and apply to patient selection.