Current views on tumor mutational burden in patients with non-small cell lung cancer treated by immune checkpoint inhibitors

Revolutionary Cancer Therapy for Personalization and Improved Efficacy: Strategies to Overcome Resistance to Immune Checkpoint Inhibitor Therapy

Cancer remains a significant public health issue worldwide, standing as a primary contributor to global mortality, accounting for approximately 10 million fatalities in 2020 [...].

The genomic landscape of the immune system in lung cancer: present insights and continuing investigations

Lung cancer is one of the most prevalent malignancies worldwide, contributing to over a million cancer-related deaths annually. Despite extensive research investigating the genetic factors associated with lung cancer susceptibility and prognosis, few studies have explored genetic predispositions regarding the immune system. This review discusses the most recent genomic findings related to the susceptibility to or protection against lung cancer, patient survival, and therapeutic responses. The results demonstrated the effect of immunogenetic variations in immune system-related genes associated with innate and adaptive immune responses, cytokine, and chemokine secretions, and signaling pathways. These genetic diversities may affect the crosstalk between tumor and immune cells within the tumor microenvironment, influencing cancer progression, invasion, and prognosis. Given the considerable variability in the individual immunegenomics profiles, future studies should prioritize large-scale analyses to identify potential genetic variations associated with lung cancer using highthroughput technologies across different populations. This approach will provide further information for predicting response to targeted therapy and promotes the development of new measures for individualized cancer treatment.

Prognostic Significance of Tumor Mutation Burden among Patients with Non-small Cell Lung Cancer Who Received Platinum-based Adjuvant Chemotherapy: An Exploratory Study

This study aimed to investigate the prognostic significance of tumor mutation burden (TMB) among patients with non-small cell lung cancer (NSCLC) who received platinum-based adjuvant chemotherapy. Tumor tissue specimens after surgical resection were collected for DNA extraction. Somatic mutation detection and TMB analysis were conducted using next-generation sequencing (NGS). Recurrence status of the patients was assessed in the hospital during the adjuvant chemotherapy period, and long-term survival data of patients were obtained by telephone follow-up. Univariate analysis between TMB status and prognosis was carried out by survival analysis. A retrospective review of 78 patients with non-squamous NSCLC who received platinum-based adjuvant chemotherapy showed a median disease-free survival of 3.6 years and median overall survival (OS) of 5.3 years. NGS analysis exhibited that the most common mutated somatic genes among the 78 patients were tumor suppressor protein p53 (TP53), epidermal growth factor receptor, low-density lipoprotein receptor related protein 1B, DNA methyltransferase 3 alpha and FAT atypical cadherin 3, and their prevalence was 56.4%, 48.7%, 37.2%, 30.7%, and 25.6%, respectively. TMB status was divided into TMB-L (≤ 4.5/Mb) and TMB-H (> 4.5/Mb) based on the median TMB threshold. Relevance of TMB to prognosis suggested that the median OS of patients with TMB-L was significantly longer than that of patients with TMB-H (NR vs. 4.6, P = 0.014). Higher TMB status conferred a worse implication on OS among patients with non-squamous NSCLC who received platinum-based adjuvant chemotherapy.

Quantitative multiplexed imaging technologies for single-cell analysis to assess predictive markers for immunotherapy in thoracic immuno-oncology: promises and challenges

The past decade has witnessed a revolution in cancer treatment by the shift from conventional drugs (chemotherapies) towards targeted molecular therapies and immune-based therapies, in particular the immune-checkpoint inhibitors (ICIs). These immunotherapies selectively release the host immune system against the tumour and have shown unprecedented durable remission for patients with cancers that were thought incurable such as advanced non-small cell lung cancer (aNSCLC). The prediction of therapy response is based since the first anti-PD-1/PD-L1 molecules FDA and EMA approvals on the level of PD-L1 tumour cells expression evaluated by immunohistochemistry, and recently more or less on tumour mutation burden in the USA. However, not all aNSCLC patients benefit from immunotherapy equally, since only around 30% of them received ICIs and among them 30% have an initial response to these treatments. Conversely, a few aNSCLC patients could have an efficacy ICIs response despite low PD-L1 tumour cells expression. In this context, there is an urgent need to look for additional robust predictive markers for ICIs efficacy in thoracic oncology. Understanding of the mechanisms that enable cancer cells to adapt to and eventually overcome therapy and identifying such mechanisms can help circumvent resistance and improve treatment. However, more than a unique universal marker, the evaluation of several molecules in the tumour at the same time, particularly by using multiplex immunostaining is a promising open room to optimise the selection of patients who benefit from ICIs. Therefore, urgent further efforts are needed to optimise to individualise immunotherapy based on both patient-specific and tumour-specific characteristics. This review aims to rethink the role of multiplex immunostaining in immuno-thoracic oncology, with the current advantages and limitations in the near-daily practice use.

Nivolumab plus ipilimumab combination therapy in cancer: Current evidence to date

Immune checkpoint inhibitors (ICIs) have revolutionized cancer immunotherapy, yielding significant antitumor responses across multiple cancer types. Combination ICI therapy with anti-CTLA-4 and anti-PD-1 antibodies outperforms either antibody alone in terms of clinical efficacy. As a consequence, the U.S. Food and Drug Administration (FDA) approved ipilimumab (anti-CTLA-4) plus nivolumab (anti-PD-1) as the first-ever approved therapies for combined ICI in patients with metastatic melanoma. Despite the success of ICIs, treatment with checkpoint inhibitor combinations poses significant clinical challenges, such as increased rates of immune-related adverse events (irAEs) and drug resistance. Thus, identifying optimal prognostic biomarkers could help to monitor the safety and efficacy of ICIs and identify patients who may benefit the most from these treatments. In this review, we will first go over the fundamentals of the CTLA-4 and PD-1 pathways, as well as the mechanisms of ICI resistance. The results of clinical findings that evaluated the combination of ipilimumab and nivolumab are then summarized to support future research in the field of combination therapy. Finally, the irAEs associated with combined ICI therapy, as well as the underlying biomarkers involved in their management, are discussed.

Liquid biopsy on the horizon in immunotherapy of non-small cell lung cancer: current status, challenges, and perspectives

Non-small cell lung cancer (NSCLC) is one of the most threatening malignancies to human health and life. In most cases, patients with NSCLC are already at an advanced stage when they are diagnosed. In recent years, lung cancer has made great progress in precision therapy, but the efficacy of immunotherapy is unstable, and its response rate varies from patient to patient. Several biomarkers have been proposed to predict the outcomes of immunotherapy, such as programmed cell death-ligand 1 (PD-L1) expression and tumor mutational burden (TMB). Nevertheless, the detection assays are invasive and demanding on tumor tissue. To effectively predict the outcomes of immunotherapy, novel biomarkers are needed to improve the performance of conventional biomarkers. Liquid biopsy is to capture and detect circulating tumor cells (CTCs), circulating tumor DNA (ctDNA) and exosomes in body fluids, such as blood, saliva, urine, pleural fluid and cerebrospinal fluid as samples from patients, so as to make analysis and diagnosis of cancer and other diseases. The application of liquid biopsy provides a new possible solution, as it has several advantages such as non-invasive, real-time dynamic monitoring, and overcoming tumor heterogeneity. Liquid biopsy has shown predictive value in immunotherapy, significantly improving the precision treatment of lung cancer patients. Herein, we review the application of liquid biopsy in predicting the outcomes of immunotherapy in NSCLC patients, and discuss the challenges and future directions in this field.

Immunotherapy for hepatocellular carcinoma: Recent advances and future targets

Immunotherapy is a promising approach to treating various types of cancers, including hepatocellular carcinoma (HCC). While single immunotherapy drugs show limited effectiveness on a small subset of patients, the combination of the anti PD-L1 atezolizumab and anti-vascular endothelial growth factor bevacizumab has shown significant improvement in survival compared to sorafenib as a first-line treatment. However, the current treatment options still have a low success rate of about 30%. Thus, more effective treatments for HCC are urgently required. Several novel immunotherapeutic methods, including the use of novel immune checkpoint inhibitors, innovative immune cell therapies like chimeric antigen receptor T cells (CAR-T), TCR gene-modified T cells and stem cells, as well as combination strategies are being tested in clinical trials for the treatment of HCC. However, some crucial issues still exist such as the presence of heterogeneous antigens in solid tumors, the immune-suppressive environment within tumors, the risk of on-target/off-tumor, infiltrating CAR-T cells, immunosuppressive checkpoint molecules, and cytokines. Overall, immunotherapy is on the brink of major advancements in the fight against HCC.

Extensive molecular profiling of squamous cell anal carcinoma in a phase 2 trial population: Translational analyses of the "CARACAS" study

BACKGROUND

Molecular characteristics of squamous cell anal carcinoma (SCAC) are poorly explored. Immune checkpoint inhibitors showed limited activity in phase I/II trials, but predictive and prognostic biomarkers are lacking.

PATIENTS AND METHODS

In the phase II randomised trial CARACAS (NCT03944252), avelumab alone (Arm A) or with cetuximab (Arm B) was tested in pre-treated advanced SCAC , with overall response rate being the primary end-point. On pre-treatment tumour tissue samples, we assessed Human papillomavirus status, programmed-death ligand 1 (PD-L1) expression, mismatch repair proteins expression, tumour mutational burden (TMB) and comprehensive genomic profiling by FoundationOne CDx. Tumour-infiltrating lymphocytes were characterised on haematoxylin-eosine-stained samples. Primary objective was to describe response to immunotherapy in the CARACAS trial population according to molecular and histological characteristics. Secondary objectives were to assess progression-free survival (PFS) and overall survival (OS) according to molecular biomarkers.

RESULTS

High PD-L1 (>40 with combined positive score) was significantly more frequent in patients with disease control (p = 0.0109). High TMB (>10 mutations per megabase) was related to better OS (hazard ratio (HR) = 0.09; 95%confidence interval (CI) 0.01-0.68; p = 0.019) and PFS (HR = 0.44; 95%CI = 0.15-1.27; p = 0.129). High expression of PD-L1 conferred longer OS (HR = 0.46; 95%CI = 0.19-1.08; p = 0.075) and PFS (HR = 0.42; 95%CI = 0.20-0.92; p = 0.03). Neither OS (HR = 1.30; 95%CI = 0.72-2.36; p = 0.39) or PFS (HR = 1.31; 95%CI = 0.74-2.31; p = 0.357) was affected by high (>1.2) Tumour-infiltrating lymphocytes count. High TMB and PD-L1identified patients were with significantly better OS (HR = 0.33; 95%CI = 0.13-0.81; p = 0.015) and PFS (HR = 0.48; 95%CI = 0.23-1.00; p = 0.015).

CONCLUSIONS

To our knowledge, TranslaCARACAS is the first study to document prognostic role of TMB and PD-L1 in advanced SCAC patients treated with immune checkpoint inhibitors.

Associations of Tissue Tumor Mutational Burden and Mutational Status With Clinical Outcomes With Pembrolizumab Plus Chemotherapy Versus Chemotherapy For Metastatic NSCLC

Introduction

We evaluated tissue tumor mutational burden (tTMB) and mutations in STK11, KEAP1, and KRAS as biomarkers for outcomes with pembrolizumab plus platinum-based chemotherapy (pembrolizumab-combination) for NSCLC among patients in the phase 3 KEYNOTE-189 (ClinicalTrials.gov, NCT02578680; nonsquamous) and KEYNOTE-407 (ClinicalTrials.gov, NCT02775435; squamous) trials.

Methods

This retrospective exploratory analysis evaluated prevalence of high tTMB and STK11, KEAP1, and KRAS mutations in patients enrolled in KEYNOTE-189 and KEYNOTE-407 and the relationship between these potential biomarkers and clinical outcomes. tTMB and STK11, KEAP1, and KRAS mutation status was assessed using whole-exome sequencing in patients with available tumor and matched normal DNA. The clinical utility of tTMB was assessed using a prespecified cutpoint of 175 mutations/exome.

Results

Among patients with evaluable data from whole-exome sequencing for evaluation of tTMB (KEYNOTE-189, n = 293; KEYNOTE-407, n = 312) and matched normal DNA, no association was found between continuous tTMB score and overall survival (OS) or progression-free survival for pembrolizumab-combination (Wald test, one-sided p > 0.05) or placebo-combination (Wald test, two-sided p > 0.05) in patients with squamous or nonsquamous histology. Pembrolizumab-combination improved outcomes for patients with tTMB greater than or equal to 175 compared with tTMB less than 175 mutations/exome in KEYNOTE-189 (OS, hazard ratio = 0.64 [95% confidence interval (CI): 0.38‒1.07] and 0.64 [95% CI: 0.42‒0.97], respectively) and KEYNOTE-407 (OS, hazard ratio = 0.74 [95% CI: 0.50‒1.08 and 0.86 [95% CI: 0.57‒1.28], respectively) versus placebo-combination. Treatment outcomes were similar regardless of KEAP1, STK11, or KRAS mutation status.

Conclusions

These findings support pembrolizumab-combination as first-line treatment in patients with metastatic NSCLC and do not suggest the utility of tTMB, STK11, KEAP1, or KRAS mutation status as a biomarker for this regimen.

Transforming Diagnosis and Therapeutics Using Cancer Genomics

In past quarter of the century, much has been understood about the genetic variation and abnormal genes that activate cancer in humans. All the cancers somehow possess alterations in the DNA sequence of cancer cell's genome. In present, we are heading toward the era where it is possible to obtain complete genome of the cancer cells for their better diagnosis, categorization and to explore treatment options.

Cell adhesion molecules and immunotherapy in advanced non-small cell lung cancer: Current process and potential application

Advanced non-small cell lung cancer (NSCLC) is a severe disease and still has high mortality rate after conventional treatment (e.g., surgical resection, chemotherapy, radiotherapy and targeted therapy). In NSCLC patients, cancer cells can induce immunosuppression, growth and metastasis by modulating cell adhesion molecules of both cancer cells and immune cells. Therefore, immunotherapy is increasingly concerned due to its promising anti-tumor effect and broader indication, which targets cell adhesion molecules to reverse the process. Among these therapies, immune checkpoint inhibitors (mainly anti-PD-(L)1 and anti-CTLA-4) are most successful and have been adapted as first or second line therapy in advanced NSCLC. However, drug resistance and immune-related adverse reactions restrict its further application. Further understanding of mechanism, adequate biomarkers and novel therapies are necessary to improve therapeutic effect and alleviate adverse effect.

Recent progress in cancer immunotherapy: Overview of current status and challenges

Cancer treatment is presently one of the most important challenges in medical science. Surgery, chemotherapy, radiotherapy, or combining these methods is used to eliminate the tumor. Hormone therapy, bone marrow transplantation, stem cell therapy as well as immunotherapy are other well-known therapeutic modalities. Immunotherapy, as the most important complementary method, uses the immune system for treating cancer followed by surgery, chemotherapy, and radiotherapy. This method is systematically used to prevent malignancies development mainly via potentiating antitumor immune cells activation and conversely compromising their exhaustion with the lowest negative effects on healthy cells. Active immunotherapy can be employed for cancer immunotherapy by directly using the ingredients of the immune system and activating immune responses. On the other hand, inactive immunotherapy is utilized by indirect induction and using immune cell-based products consisting of monoclonal antibodies. It has strongly been proved that combination therapy with immunotherapies and other therapeutic means, such as anti-angiogenic agents, could be a rational plan to treat cancer. Herein, we have focused on recent findings concerning the therapeutic merits of cancer therapy using immune checkpoint inhibitors (ICIs), adoptive cell transfer (ACT) and cancer vaccine alone or in combination with other approaches. Also, we offer a glimpse into the current challenges in this context.

Oncogenic alterations reveal key strategies for precision oncology in melanoma treatment

Background

Molecular profiling with next-generation sequencing (NGS) has been applied in multiple solid tumors, including melanomas, to identify potential drug targets. However, the association between clinical outcomes and the molecular alterations has not yet been fully clarified.

Methods

A total of 108 patients with melanoma were included in this study, 95 of whom had both sequencing data and clinical outcomes were collected. We analyzed the genetic alterations of 108 malignant melanoma patients using the OncoCare panel, which covers 559 genes.

Results

A model was also established to predict side effects through a combination analysis of clinical data and somatic variants, yielding an area under the receiver operating characteristic curve (AUROC) score of 0.8. We also identified epidermal growth factor receptor (EGFR) mutation was excellent predictor for progression-free survival (PFS) for patient who received immunotherapy (log-rank P=0.01), while tumor mutation burden (TMB) was found to not be significantly associated with PFS (log-rank P=0.87). Combining clinical features with genetic analysis, we found that patients carrying both DNA POLD1/ALOX12B or POLD1/PTPRT mutations had a significantly lower survival rate.

Conclusions

Overall, these results demonstrate the benefits of applying NGS clinical panels and shed light on future directions of personalized therapeutics for the treatment of melanoma.

Nanomedicine-Based Gene Delivery for a Truncated Tumor Suppressor RB94 Promotes Lung Cancer Immunity

Because lung cancer remains the most common and lethal of cancers, novel therapeutic approaches are urgently needed. RB94 is a truncated form of retinoblastoma tumor suppressor protein with elevated anti-tumor efficacy. Our investigational nanomedicine (termed scL-RB94) is a tumor-targeted liposomal formulation of a plasmid containing the gene encoding RB94. In this research, we studied anti-tumor and immune modulation activities of scL-RB94 nanocomplex in preclinical models of human non-small cell lung cancer (NSCLC). Systemic treatment with scL-RB94 of mice bearing human NSCLC tumors significantly inhibited tumor growth by lowering proliferation and increasing apoptosis of tumor cells in vivo. scL-RB94 treatment also boosted anti-tumor immune responses by upregulating immune recognition molecules and recruiting innate immune cells such as natural killer (NK) cells. Antibody-mediated depletion of NK cells blunted the anti-tumor activity of scL-RB94, suggesting that NK cells were crucial for the observed anti-tumor activity in these xenograft models. Treatment with scL-RB94 also altered the polarization of tumor-associated macrophages by reducing immune-suppressive M2 macrophages to lower immune suppression in the tumor microenvironment. Collectively, our data suggest that the efficacy of scL-RB94 against NSCLC is due to an induction of tumor cell death as well as enhancement of innate anti-tumor immunity.

Tumor mutational burden in non-immunotherapy patients with heavily pretreated metastatic breast cancer: long-term outcomes from a single institution

Patients with heavily pretreated (≥3^rd-line treatment) metastatic breast cancer (MBC) had poor outcomes and lack prognostic biomarkers. Tumor mutational burden (TMB) was a prognostic biomarker for immunotherapy, but is not well defined in non-immunotherapy. Forty-nine heavily pretreated MBC not received immunotherapy were enrolled between March 2016 and September 2018. TMB of metastatic tumor tissue was evaluated by targeted next-generation sequencing of a 247-genes panel. CBRs (clinical benefit rates) were 47.7% (9 months), 36.2% (12 months) in high TMB patients, higher than 16.1% (9 months), 8.1% (12 months) in low TMB patients, respectively. After a median follow-up of 38 months, patients with high TMB had a longer mPFS (median progress-free survival) compared to low TMB patients in 3^rd-line treatment group (13.5 versus 7 months, HR 0.32, p = 0.019) but not in >3^rd-line treatment group. Cox regression showed TMB and line of treatment were the two independent prognostic factors for prolonged mPFS in heavily pretreated MBC, with a HR of 0.34 (p = 0.009) for high TMB and 0.37 (p = 0.013) for 3^rd-line treatment. In luminal subtype, mPFS was longer with endocrine therapy (ET) alone than with endocrine therapy + chemotherapy (ET + CT) in high TMB cohort (p = 0.037) but shorter mPFS with ET alone than with ET + CT in low TMB cohort (p = 0.047). High TMB and line of treatment are two independent prognostic factors for prolonged mPFS in heavily pretreated MBC patients. TMB may be a predictive biomarker of efficacy with ET alone or ET + CT in luminal subtype.

Matched Paired Primary and Recurrent Meningiomas Points to Cell-Death Program Contributions to Genomic and Epigenomic Instability along Tumor Progression

Meningioma (MN) is an important cause of disability, and predictive tools for estimating the risk of recurrence are still scarce. The need for objective and cost-effective techniques addressed to this purpose is well known. In this study, we present methylation-specific multiplex ligation-dependent probe amplification (MS-MLPA) as a friendly method for deepening the understanding of the mechanisms underlying meningioma progression. A large follow-up allowed us to obtain 50 samples, which included the primary tumor of 20 patients in which half of them are suffering one recurrence and the other half are suffering more than one. We histologically characterized the samples and performed MS-MLPA assays validated by FISH to assess their copy number alterations (CNA) and epigenetic status. Interestingly, we determined the increase in tumor instability with higher values of CNA during the progression accompanied by an increase in epigenetic damage. We also found a loss of HIC1 and the hypermethylation of CDKN2B and PTEN as independent prognostic markers. Comparison between grade 1 and higher primary MN's self-evolution pointed to a central role of GSTP1 in the first stages of the disease. Finally, a high rate of alterations in genes that are related to apoptosis and autophagy, such as DAPK1, PARK2, BCL2, FHIT, or VHL, underlines an important influence on cell-death programs through different pathways.

Deep phenotyping for precision medicine in Parkinson's disease

A major challenge in medical genomics is to understand why individuals with the same disorder have different clinical symptoms and why those who carry the same mutation may be affected by different disorders. In every complex disorder, identifying the contribution of different genetic and non-genetic risk factors is a key obstacle to understanding disease mechanisms. Genetic studies rely on precise phenotypes and are unable to uncover the genetic contributions to a disorder when phenotypes are imprecise. To address this challenge, deeply phenotyped cohorts have been developed for which detailed, fine-grained data have been collected. These cohorts help us to investigate the underlying biological pathways and risk factors to identify treatment targets, and thus to advance precision medicine. The neurodegenerative disorder Parkinson's disease has a diverse phenotypical presentation and modest heritability, and its underlying disease mechanisms are still being debated. As such, considerable efforts have been made to develop deeply phenotyped cohorts for this disorder. Here, we focus on Parkinson's disease and explore how deep phenotyping can help address the challenges raised by genetic and phenotypic heterogeneity. We also discuss recent methods for data collection and computation, as well as methodological challenges that have to be overcome.

Immune Checkpoint Inhibitors in Cancer Therapy

The discovery of immune checkpoint proteins such as PD-1/PDL-1 and CTLA-4 represents a significant breakthrough in the field of cancer immunotherapy. Therefore, humanized monoclonal antibodies, targeting these immune checkpoint proteins have been utilized successfully in patients with metastatic melanoma, renal cell carcinoma, head and neck cancers and non-small lung cancer. The US FDA has successfully approved three different categories of immune checkpoint inhibitors (ICIs) such as PD-1 inhibitors (Nivolumab, Pembrolizumab, and Cemiplimab), PDL-1 inhibitors (Atezolimumab, Durvalumab and Avelumab), and CTLA-4 inhibitor (Ipilimumab). Unfortunately, not all patients respond favourably to these drugs, highlighting the role of biomarkers such as Tumour mutation burden (TMB), PDL-1 expression, microbiome, hypoxia, interferon-γ, and ECM in predicting responses to ICIs-based immunotherapy. The current study aims to review the literature and updates on ICIs in cancer therapy.

Genomic characteristics of invasive mucinous adenocarcinoma of the lung with multiple pulmonary sites of involvement

Invasive mucinous adenocarcinoma (IMA) of the lung frequently presents with diffuse pneumonic-type features or multifocal lesions, which are regarded as a pattern of intrapulmonary metastases. However, the genomics of multifocal IMAs have not been well studied. We performed whole exome sequencing on samples taken from 2 to 5 regions in seven patients with synchronous multifocal IMAs of the lung (24 regions total). Early initiating driver events, such as KRAS, NKX2-1, TP53, or ARID1A mutations, are clonal mutations and were present in all multifocal IMAs in each patient. The tumor mutational burden of multifocal IMAs was low (mean: 1.13/mega base), but further analyses suggested intra-tumor heterogeneity. The mutational signature analysis found that IMAs were predominantly associated with endogenous mutational process (signature 1), APOBEC activity (signatures 2 and 13), and defective DNA mismatch repair (signature 6), but not related to smoking signature. IMAs synchronously located in the bilateral lower lobes of two patients with background usual interstitial pneumonia had different mutation types, suggesting that they were double primaries. In conclusion, genomic evidence found in this study indicated the clonal intrapulmonary spread of diffuse pneumonic-type or multifocal IMAs, although they can occur in multicentric origins in the background of usual interstitial pneumonia. IMAs exhibited a heterogeneous genomic landscape despite the low somatic mutation burden. Further studies are warranted to determine the clinical significance of the genomic characteristics of IMAs in expanded cohorts.

EMSY inhibits homologous recombination repair and the interferon response, promoting lung cancer immune evasion

Non-small cell lung cancers (NSCLCs) harboring KEAP1 mutations are often resistant to immunotherapy. Here, we show that KEAP1 targets EMSY for ubiquitin-mediated degradation to regulate homologous recombination repair (HRR) and anti-tumor immunity. Loss of KEAP1 in NSCLC induces stabilization of EMSY, producing a BRCAness phenotype, i.e., HRR defects and sensitivity to PARP inhibitors. Defective HRR contributes to a high tumor mutational burden that, in turn, is expected to prompt an innate immune response. Notably, EMSY accumulation suppresses the type I interferon response and impairs innate immune signaling, fostering cancer immune evasion. Activation of the type I interferon response in the tumor microenvironment using a STING agonist results in the engagement of innate and adaptive immune signaling and impairs the growth of KEAP1-mutant tumors. Our results suggest that targeting PARP and STING pathways, individually or in combination, represents a therapeutic strategy in NSCLC patients harboring alterations in KEAP1.

Prediction performance of twelve tumor mutation burden panels in melanoma and non-small cell lung cancer

As a potential biomarker to predict the response to immunotherapy, tumor mutation burden (TMB) which can be estimated by the cancer gene panel (CGP) has received considerable attention. However, it is not clear which CGP is better in predicting the efficacy of immunotherapy. To evaluate the twelve CGPs, we compared them on 13 datasets of melanoma and non-small cell lung cancer (NSCLC) from the perspective of gene composition, reliability of measuring TMB and prediction performance of patient treatment benefits. The larger CGPs generally performed better, but their proportions of driver genes and function densities were smaller. The CGPs performed differently on melanoma and NSCLC patients treated with two blockades. Moreover, their ability to classify and predict patients with or without long-term clinical benefits was similar but not good enough, so it is necessary to explore a higher-performance biomarker.

Assessment of the albumin-bilirubin grade as a prognostic factor in patients with non-small-cell lung cancer receiving anti-PD-1-based therapy

Introduction

The albumin-bilirubin (ALBI) grade is a novel indicator of the liver function. Some studies showed that the ALBI grade was a prognostic and predictive biomarker for the efficacy of chemotherapy in cancer patients. The association between the ALBI grade and outcomes in patients with non-small-cell lung cancer (NSCLC) treated with cancer immunotherapy, however, is poorly understood.

Methods

We retrospectively enrolled 452 patients with advanced or recurrent NSCLC who received anti-programmed cell death protein 1 (PD-1)-based therapy between 2016 and 2019 at three medical centers in Japan. The ALBI score was calculated from albumin and bilirubin measured at the time of treatment initiation and was stratified into three categories, ALBI grade 1-3, with reference to previous reports. We examined the clinical impact of the ALBI grade on the outcomes of NSCLC patients receiving anti-PD-1-based therapy using Kaplan–Meier survival curve analysis with log-rank test and Cox proportional hazards regression analysis.

Results

The classifications of the 452 patients were as follows: grade 1, n = 158 (35.0%); grade 2, n = 271 (60.0%); and grade 3, n = 23 (5.0%). Kaplan–Meier survival curve analysis showed that the ALBI grade was significantly associated with progression-free survival and overall survival. Moreover, Cox regression analysis revealed that the ALBI grade was an independent prognostic factor for progression-free survival and overall survival.

Conclusion

The ALBI grade was an independent prognostic factor for survival in patients with advanced or recurrent NSCLC who receive anti-PD-1-based therapy. These findings should be validated in a prospective study with a larger sample size.

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ALBI grade is calculated from albumin and bilirubin.

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We evaluated the impact of ALBI grade on survival in NSCLC patients receiving immune checkpoint inhibitors.

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ALBI grade was an independent prognostic factor for progression-free survival (PFS) and overall survival (OS).

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ALBI grade effectively stratified PFS and OS in patients with performance status 1-3.

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ALBI grade was significantly associated with PFS and OS, regardless of programmed death ligand-1.

Machine Learning for Prediction of Immunotherapy Efficacy in Non-Small Cell Lung Cancer from Simple Clinical and Biological Data

BACKGROUND

Immune checkpoint inhibitors (ICIs) are now a therapeutic standard in advanced non-small cell lung cancer (NSCLC), but strong predictive markers for ICIs efficacy are still lacking. We evaluated machine learning models built on simple clinical and biological data to individually predict response to ICIs.

METHODS

Patients with metastatic NSCLC who received ICI in second line or later were included. We collected clinical and hematological data and studied the association of this data with disease control rate (DCR), progression free survival (PFS) and overall survival (OS). Multiple machine learning (ML) algorithms were assessed for their ability to predict response.

RESULTS

Overall, 298 patients were enrolled. The overall response rate and DCR were 15.3% and 53%, respectively. Median PFS and OS were 3.3 and 11.4 months, respectively. In multivariable analysis, DCR was significantly associated with performance status (PS) and hemoglobin level (OR 0.58, p < 0.0001; OR 1.8, p < 0.001). These variables were also associated with PFS and OS and ranked top in random forest-based feature importance. Neutrophil-to-lymphocyte ratio was also associated with DCR, PFS and OS. The best ML algorithm was a random forest. It could predict DCR with satisfactory efficacy based on these three variables. Ten-fold cross-validated performances were: accuracy 0.68 ± 0.04, sensitivity 0.58 ± 0.08; specificity 0.78 ± 0.06; positive predictive value 0.70 ± 0.08; negative predictive value 0.68 ± 0.06; AUC 0.74 ± 0.03.

CONCLUSION

Combination of simple clinical and biological data could accurately predict disease control rate at the individual level.

Smoking History as a Potential Predictor of Immune Checkpoint Inhibitor Efficacy in Metastatic Non-Small Cell Lung Cancer

BACKGROUND

Despite the therapeutic efficacy of immune checkpoint inhibitors (ICIs) in a subset of patients, consistent and easily obtainable predictors of efficacy remain elusive.

METHODS

This study was conducted on 644 advanced non-small cell lung cancer (NSCLC) patients treated with ICI monotherapy between April 2013 and September 2020 at the Dana-Farber Cancer Institute and Brigham and Women's Hospital. Patient smoking history, clinicopathological characteristics, tumor mutation burden (TMB) by clinical targeted next-generation sequencing, and programmed death ligand-1 (PD-L1) tumor proportion score (TPS) by immunohistochemistry were prospectively collected. The association of smoking history with clinical outcomes of ICI monotherapy in metastatic NSCLC patients was evaluated after adjusting for other potential predictors. All statistical tests were 2-sided.

RESULTS

Of 644 advanced NSCLC patients, 105 (16.3%) were never smokers, 375 (58.2%) were former smokers (median pack-years = 28), and 164 (25.4%) were current smokers (median pack-years = 40). Multivariable logistic and Cox proportional hazards regression analyses suggested that doubling of smoking pack-years is statistically significantly associated with improved clinical outcomes of patients treated with ICI monotherapy (objective response rate odds ratio = 1.21, 95% confidence interval [CI] = 1.09 to 1.36, P < .001; progression-free survival hazard ratio = 0.92, 95% CI = 0.88 to 0.95, P < .001; overall survival hazard ratio = 0.94, 95% CI = 0.90 to 0.99, P = .01). Predictive models incorporating pack-years and PD-L1 TPS yielded additional information and achieved similar model performance compared with using TMB and PD-L1 TPS.

CONCLUSIONS

Increased smoking exposure had a statistically significant association with improved clinical outcomes in metastatic NSCLC treated with ICI monotherapy independent of PD-L1 TPS. Pack-years may serve as a consistent and readily obtainable surrogate of ICI efficacy when TMB is not available to inform prompt clinical decisions and allow more patients to benefit from ICIs.

The relationship between blood-based tumor mutation burden level and efficacy of PD-1/PD-L1 inhibitors in advanced non-small cell lung cancer: a systematic review and meta-analysis

Background

The predictive role of blood-based tumor mutation burden (bTMB) for selecting advanced nonsmall cell lung cancer (NSCLC) patients who might benefit from immune checkpoint inhibitors (ICIs) is still under debate. Therefore, the purpose of this meta-analysis was to evaluate the efficacy of programmed cell death 1 (PD-1) /programmed cell death ligand 1 (PD-L1) inhibitors versus that of standard-of-care therapy in patients with NSCLC who were bTMB high and bTMB low.

Methods

PubMed, Embase, Cochrane, the Web of Science, and ClinicalTrials.gov were searched systematically from inception to February 2021 for studies of PD-1/PD-L1 inhibitors (durvalumab OR atezolizumab OR avelumab OR pembrolizumab OR Nivolumab) that provided hazard ratios (HRs) for overall survival (OS) or progression-free survival (PFS), or odds ratios (ORs) for objective response rate (ORR) in both bTMB high and bTMB low groups.

Results

A total of 2338 patients with advanced or metastatic NSCLC from six randomized controlled trials, which all used chemotherapy (CT) as a control, were included in this study. Compared with CT, PD-1/PD-L1 inhibitor therapy improved OS (HR 0.62, 95% CI 0.52–0.75, P < 0.01), PFS (HR 0.57, 95% CI 0.48–0.67, P < 0.01), and ORR (OR 2.69, 95% CI 1.84–3.93, P < 0.01) in bTMB-high NSCLC patients but not in bTMB-low patients (OS HR 0.86, 95% CI 0.69–1.07, P = 0.17; PFS HR 1.00, 95% CI 0.78–1.27, P = 0.98; ORR OR 0.63, 95% CI 0.49–0.80, P = 0.03). Subgroup analyses showed that these results were consistent across all subgroups (line of therapy, therapy regimen, type of NGS panel, PD-L1 expression, and cutoff value). Meta-regression analysis showed that the proportion of patients with squamous cell histology had no statistical effect on clinical outcomes. Sensitivity analyses illustrated that all results were stable.

Conclusions

The efficacy of PD-1/PD-L1 inhibitor therapy in advanced NSCLC patients may be dependent on bTMB level. Patients with high bTMB tend to obtain significantly better OS, PFS, and ORR from PD-1/PD-L1 inhibitor therapy than from CT. However, because of multiple limitations, including those related to reproducibility, the results are exploratory and should be interpreted with caution.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08924-z.

Molecular predictors of response to pembrolizumab in thymic carcinoma

Thymic carcinoma is rare and has a poorer prognosis than thymomas. The treatment options are limited after failure of platinum-based chemotherapy. We previously performed a single-center phase II study of pembrolizumab in patients with advanced thymic carcinoma, showing a 22.5% response rate. Here, we characterize the genomic and transcriptomic profile of thymic carcinoma samples from 10 patients (5 non-responders versus 5 responders) in this cohort, with the main aim of identifying potential predictors of response to immunotherapy. We find that expression of PDL1 and alterations in genes or pathways that correlated with PD-L1 expression (CYLD and BAP1) could be potential predictors for response or resistance to immunotherapy in patients with advanced thymic carcinoma. Our study provides insights into potential predictive markers/pathways to select patients with thymic carcinoma for anti-PD-1 immunotherapy.

Allele frequency deviation (AFD) as a new prognostic model to predict overall survival in lung adenocarcinoma (LUAD)

Background

Lung adenocarcinoma (LUAD) remains one of the world’s most known aggressive malignancies with a high mortality rate. Molecular biological analysis and bioinformatics are of great importance as they have recently occupied a large area in the studies related to the identification of various biomarkers to predict survival for LUAD patients. In our study, we attempted to identify a new prognostic model by developing a new algorithm to calculate the allele frequency deviation (AFD), which in turn may assist in the early diagnosis and prediction of clinical outcomes in LUAD.

Method

First, a new algorithm was developed to calculate AFD using the whole-exome sequencing (WES) dataset. Then, AFD was measured for 102 patients, and the predictive power of AFD was assessed using Kaplan–Meier analysis, receiver operating characteristic (ROC) curves, and area under the curve (AUC). Finally, multivariable cox regression analyses were conducted to evaluate the independence of AFD as an independent prognostic tool.

Result

The Kaplan–Meier analysis showed that AFD effectively segregated patients with LUAD into high-AFD-value and low-AFD-value risk groups (hazard ratio HR = 1.125, 95% confidence interval CI 1.001–1.26, p = 0.04) in the training group. Moreover, the overall survival (OS) of patients who belong to the high-AFD-value group was significantly shorter than that of patients who belong to the low-AFD-value group with 42.8% higher risk and 10% lower risk of death for both groups respectively (HR for death = 1.10; 95% CI 1.01–1.2, p = 0.03) in the training group. Similar results were obtained in the validation group (HR = 4.62, 95% CI 1.22–17.4, p = 0.02) with 41.6%, and 5.5% risk of death for patients who belong to the high and low-AFD-value groups respectively. Univariate and multivariable cox regression analyses demonstrated that AFD is an independent prognostic model for patients with LUAD. The AUC for 5-year survival were 0.712 and 0.86 in the training and validation groups, respectively.

Conclusion

AFD was identified as a new independent prognostic model that could provide a prognostic tool for physicians and contribute to treatment decisions.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-02127-z.

What Is New in Biomarker Testing at Diagnosis of Advanced Non-Squamous Non-Small Cell Lung Carcinoma? Implications for Cytology and Liquid Biopsy

The discovery and clinical validation of biomarkers predictive of the response of non-squamous non-small-cell lung carcinomas (NS-NSCLC) to therapeutic strategies continue to provide new data. The evaluation of novel treatments is based on molecular analyses aimed at determining their efficacy. These tests are increasing in number, but the tissue specimens are smaller and smaller and/or can have few tumor cells. Indeed, in addition to tissue samples, complementary cytological and/or blood samples can also give access to these biomarkers. To date, it is recommended and necessary to look for the status of five genomic molecular biomarkers (EGFR, ALK, ROS1, BRAFV600, NTRK) and of a protein biomarker (PD-L1). However, the short- and more or less long-term emergence of new targeted treatments of genomic alterations on RET and MET, but also on others’ genomic alteration, notably on KRAS, HER2, NRG1, SMARCA4, and NUT, have made cellular and blood samples essential for molecular testing. The aim of this review is to present the interest in using cytological and/or liquid biopsies as complementary biological material, or as an alternative to tissue specimens, for detection at diagnosis of new predictive biomarkers of NS-NSCLC.

The prognostic impact of tumor mutational burden (TMB) in the first-line management of advanced non-oncogene addicted non-small-cell lung cancer (NSCLC): a systematic review and meta-analysis of randomized controlled trials

BACKGROUND

The role of tumor mutational burden (TMB) is still debated for selecting advanced non-oncogene addicted non-small-cell lung cancer (NSCLC) patients who might benefit from immune checkpoint inhibitors (ICIs). Of note, TMB failed to predict a benefit in overall survival (OS) among such patients.

MATERIALS AND METHODS

The purpose of this meta-analysis was to compare efficacy outcomes among first-line immune-oncology (IO) agents versus standard platinum-based chemotherapy (CT) within two subgroups (TMB-low and TMB-high on either tissue or blood). We collected hazard ratios (HRs) to evaluate the association for progression-free survival (PFS) and OS, with the relative 95% confidence intervals (CIs). Risk ratios (RRs) were used as an association measure for objective response rate (ORR).

RESULTS

Eight different cohorts of five randomized controlled phase III studies (3848 patients) were analyzed. In TMB-high patients, IO agents were associated with improved ORR (RRs 1.37, 95% CI 1.13-1.66), PFS (HR 0.69, 95% CI 0.61-0.79) and OS (HR 0.67, 95% CI 0.59-0.77) when compared with CT, thus suggesting a possible predictive role of high TMB for IO regimens. In TMB-low patients, the IO strategy did not lead to any significant benefit in survival and activity, whereas the pooled results of both ORR and PFS were intriguingly associated with a statistical significance in favor of CT.

CONCLUSIONS

This meta-analysis resulted in a proven benefit in OS in favor of IO agents in the TMB-high population. Although more prospective data are warranted, we postulated the hypothesis that monitoring TMB, in addition to the existing programmed death-ligand 1 (PD-L1) expression level, could represent the preferable option for future clinical research in the first-line management of advanced non-oncogene addicted NSCLC patients.

Thermal ablation in non-small cell lung cancer: a review of treatment modalities and the evidence for combination with immune checkpoint inhibitors

Lung cancer is the leading cause of cancer death worldwide, with approximately 1.6 million cancer related deaths each year. Prognosis is best in patients with early stage disease, though even then five-year survival is only 55% in some groups. Median survival for advanced non-small cell lung cancer (NSCLC) is 8–12 months with conventional treatment. Immune checkpoint inhibitor (ICI) therapy has revolutionised the treatment of NSCLC with significant long-term improvements in survival demonstrated in some patients with advanced NSCLC. However, only a small proportion of patients respond to ICI, suggesting the need for further techniques to harness the potential of ICI therapy. Thermal ablation utilizes the extremes of temperature to cause tumour destruction. Commonly used modalities are radiofrequency ablation (RFA), cryoablation and microwave ablation (MWA). At present thermal ablation is reserved for curative-intent therapy in patients with localized NSCLC who are unable to undergo surgical resection or stereotactic ablative body radiotherapy (SABR). Limited evidence suggests that thermal ablative modalities can upregulate an anticancer immune response in NSCLC. It is postulated that thermal ablation can increase tumour antigen release, which would initiate and upregulated steps in the cancer immunity cycle required to elicit an anticancer immune response. This article will review the current thermal ablative techniques and their ability to modulate an anti-cancer immune response with a view of using thermal ablation in conjunction with ICI therapy.

Circulating tumor DNA in lung cancer: real-time monitoring of disease evolution and treatment response

Lung cancer is one of the leading causes of all cancer-related deaths. Circulating tumor DNA (ctDNA) is released from apoptotic and necrotic tumor cells. Several sensitive techniques have been invented and adapted to quantify ctDNA genomic alterations. Applications of ctDNA in lung cancer include early diagnosis and detection, prognosis prediction, detecting mutations and structural alterations, minimal residual disease, tumor mutational burden, and tumor evolution tracking. Compared to surgical biopsy and radiographic imaging, the advantages of ctDNA are that it is a non-invasive procedure, allows real-time monitoring, and has relatively high sensitivity and specificity. Given the massive research on non-small cell lung cancer, attention should be paid to small cell lung cancer.

Perioperative clinical trials for glioma: Raising the bar

Gliomas are a heterogeneous group of primary brain cancers with poor survival despite multimodality therapy that includes surgery, radiation and chemotherapy. Numerous clinical trials have investigated systemic therapies in glioma, but have largely been negative. Multiple factors have contributed to the lack of progress including tumour heterogeneity, the tumour micro-environment and presence of the blood-brain barrier, as well as extrinsic factors relating to trial design, such as the lack of a contemporaneous biopsy at the time of treatment. A number of strategies have been proposed to progress new agents into the clinic. Here, we review the progress of perioperative, including phase 0 and 'window of opportunity', studies and provide recommendations for trial design in the development of new agents for glioma. The incorporation of pre- and post-treatment biopsies in glioma early phase trials will provide valuable pharmacokinetic and pharmacodynamic data and also determine the target or biomarker effect, which will guide further development of new agents. Perioperative 'window of opportunity' studies must use drugs with a recommended-phase-2-dose, known safety profile and adequate blood-brain barrier penetration. Drugs shown to have on-target effects in perioperative trials can then be evaluated further in a larger cohort of patients in an adaptive trial to increase the efficiency of drug development.

Association between Smoking History and Tumor Mutation Burden in Advanced Non-Small Cell Lung Cancer

Lung carcinogenesis is a complex and stepwise process involving accumulation of genetic mutations in signaling and oncogenic pathways via interactions with environmental factors and host susceptibility. Tobacco exposure is the leading cause of lung cancer, but its relationship to clinically relevant mutations and the composite tumor mutation burden (TMB) has not been fully elucidated. In this study, we investigated the dose-response relationship in a retrospective observational study of 931 patients treated for advanced-stage non-small cell lung cancer (NSCLC) between April 2013 and February 2020 at the Dana Farber Cancer Institute and Brigham and Women's Hospital. Doubling smoking pack-years was associated with increased KRASG12C and less frequent EGFRdel19 and EGFRL858R mutations, whereas doubling smoking-free months was associated with more frequent EGFRL858R . In advanced lung adenocarcinoma, doubling smoking pack-years was associated with an increase in TMB, whereas doubling smoking-free months was associated with a decrease in TMB, after controlling for age, gender, and stage. There is a significant dose-response association of smoking history with genetic alterations in cancer-related pathways and TMB in advanced lung adenocarcinoma. SIGNIFICANCE: This study clarifies the relationship between smoking history and clinically relevant mutations in non-small cell lung cancer, revealing the potential of smoking history as a surrogate for tumor mutation burden.

Next-Generation Sequencing with Liquid Biopsies from Treatment-Naïve Non-Small Cell Lung Carcinoma Patients

Recently, the liquid biopsy (LB), a non-invasive and easy to repeat approach, has started to compete with the tissue biopsy (TB) for detection of targets for administration of therapeutic strategies for patients with advanced stages of lung cancer at tumor progression. A LB at diagnosis of late stage non-small cell lung carcinoma (NSCLC) is also being performed. It may be asked if a LB can be complementary (according to the clinical presentation or systematics) or even an alternative to a TB for treatment-naïve advanced NSCLC patients. Nucleic acid analysis with a TB by next-generation sequencing (NGS) is gradually replacing targeted sequencing methods for assessment of genomic alterations in lung cancer patients with tumor progression, but also at baseline. However, LB is still not often used in daily practice for NGS. This review addresses different aspects relating to the use of LB for NGS at diagnosis in advanced NSCLC, including its advantages and limitations.

Robust Prediction of Immune Checkpoint Inhibition Therapy for Non-Small Cell Lung Cancer

Background

The development of immune checkpoint inhibitors (ICIs) is a revolutionary milestone in the field of immune-oncology. However, the low response rate is the major problem of ICI treatment. The recent studies showed that response rate to single-agent programmed cell death protein 1 (PD-1)/programmed cell death-ligand 1 (PD-L1) inhibition in unselected non-small cell lung cancer (NSCLC) patients is 25% so that researchers defined several biomarkers to predict the response of immunotherapy in ICIs treatment. Common biomarkers like tumor mutational burden (TMB) and PD-L1 expression have several limitations, such as low accuracy and inadequately validated cutoff value.

Methods

Two published and an unpublished ICIs treatment NSCLC cohorts with 129 patients were collected and divided into a training cohort (n = 53), a validation cohort (n = 22), and two independent test cohorts (n = 34 and n = 20). We identified six immune-related pathways whose mutational status was significantly associated with overall survival after ICIs treatment. Then these pathways mutational status combined with TMB, PD-L1 expression and intratumor heterogeneity were incorporated to build a Bayesian-regularization neural networks (BRNN) model to predict the ICIs treatment response.

Results

We firstly proved that TMB, PD-L1, and mutant-allele tumor heterogeneity (MATH) were independent biomarkers. The survival analysis of six immune-related pathways revealed the mutational status could distinguish overall survival after ICIs treatment. When predicting immunotherapy efficacy, the overall accuracy of area under curve (AUC) in validation cohort reaches 0.85, outperforming previous predictors in either sensitivity or specificity. And the AUC in two independent test cohorts reach 0.74 and 0.80.

Conclusion

We developed a pathway-model that could predict the efficacy of ICIs in NSCLC patients. Our study made a significant contribution to solving the low prediction accuracy of immunotherapy of single biomarker. With the accumulation of larger data sets, further studies are warranted to refine the predictive performance of the approach.

Prognostic and Predictive Biomarkers in Non-Small Cell Lung Cancer Patients on Immunotherapy-The Role of Liquid Biopsy in Unraveling the Puzzle

In the last decade, immunotherapy has been one of the most important advances in the non-small cell lung cancer (NSCLC) treatment landscape. Nevertheless, only a subset of NSCLC patients benefits from it. Currently, the only Food and Drug Administration (FDA) approved diagnostic test for first-line immunotherapy in metastatic NSCLC patients uses tissue biopsies to determine the programmed death ligand 1 (PD-L1) status. However, obtaining tumor tissue is not always feasible and puts the patient at risk. Liquid biopsy, which refers to the tumor-derived material present in body fluids, offers an alternative approach. This less invasive technique gives real-time information on the tumor characteristics. This review addresses different promising liquid biopsy based biomarkers in NSCLC patients that enable the selection of patients who benefit from immunotherapy and the monitoring of patients during this therapy. The challenges and the opportunities of blood-based biomarkers such as cell-free DNA (cfDNA), circulating tumor cells (CTCs), exosomes, epigenetic signatures, microRNAs (miRNAs) and the T cell repertoire will be addressed. This review also focuses on the less-studied feces-based and breath-based biomarkers.

Combination of HGF/MET-targeting agents and other therapeutic strategies in cancer

MET receptor has emerged as a druggable target across several human cancers. Agents targeting MET and its ligand hepatocyte growth factor (HGF) including small molecules such as crizotinib, tivantinib and cabozantinib or antibodies including rilotumumab and onartuzumab have proven their values in different tumors. Recently, capmatinib was approved for treatment of metastatic lung cancer with MET exon 14 skipping. In this review, we critically examine the current evidence on how HGF/MET combination therapies may take advantage of synergistic effects, overcome primary or acquired drug resistance, target tumor microenvironment, modulate drug metabolism or tackle pharmacokinetic issues. Preclinical and clinical studies on the combination of HGF/MET-targeted agents with conventional chemotherapeutics or molecularly targeted treatments (including EGFR, VEGFR, HER2, RAF/MEK, and PI3K/Akt targeting agents) and also the value of biomarkers are examined. Our deeper understanding of molecular mechanisms underlying successful pharmacological combinations is crucial to find the best personalized treatment regimens for cancer patients.

Efficacy of Checkpoint Inhibitors in Neuroendocrine Neoplasms: Mayo Clinic Experience

OBJECTIVES

Checkpoint inhibitors (CPIs) for low- and intermediate-grade neuroendocrine tumors (NETs) have been associated with limited efficacy; recent studies suggest CPIs may represent promising treatment for high-grade neuroendocrine neoplasms (NENs).

METHODS

We examined 57 patients with NENs who were treated with CPIs to determine if NETs and neuroendocrine carcinomas (NECs) respond to immunotherapy.

RESULTS

Patients with poorly differentiated NECs on CPI monotherapy had an objective response rate (ORR) of 0% and median progression-free survival (PFS) of 2.1 months (95% confidence interval [CI], 0.5-4.6). Patients with poorly differentiated NECs on dual CPI therapy had an ORR of 13% and PFS of 3.5 months (95% CI, 1.4-not reached [NR]). Patients with poorly differentiated NECs on CPI and cytotoxic therapy had an ORR of 36% with PFS of 4.2 months (95% CI, 1.6-NR). Well-differentiated grade 1 and 2 NETs on CPI monotherapy had an ORR of 25% with PFS NR. Well-differentiated grade 3 NETs had 0% ORR with a PFS of 2.9 months (95% CI, 1.4-4.2) on CPI monotherapy.

CONCLUSIONS

Checkpoint inhibitor therapy shows limited activity in patients with NENs. Future studies should identify biomarkers that can help identify patients who are likely responders to immunotherapy.

Genetic Ancestry Contributes to Somatic Mutations in Lung Cancers from Admixed Latin American Populations

Inherited lung cancer risk, particularly in nonsmokers, is poorly understood. Genomic and ancestry analysis of 1,153 lung cancers from Latin America revealed striking associations between Native American ancestry and their somatic landscape, including tumor mutational burden, and specific driver mutations in EGFR, KRAS, and STK11. A local Native American ancestry risk score was more strongly correlated with EGFR mutation frequency compared with global ancestry correlation, suggesting that germline genetics (rather than environmental exposure) underlie these disparities. SIGNIFICANCE: The frequency of somatic EGFR and KRAS mutations in lung cancer varies by ethnicity, but we do not understand why. Our study suggests that the variation in EGFR and KRAS mutation frequency is associated with genetic ancestry and suggests further studies to identify germline alleles that underpin this association.See related commentary by Gomez et al., p. 534.This article is highlighted in the In This Issue feature, p. 521.

The Importance of STK11/LKB1 Assessment in Non-Small Cell Lung Carcinomas

Despite the recent implementation of immunotherapy as a single treatment or in combination with chemotherapy for first-line treatment of advanced non-small cell lung cancer (NSCLC), many patients do not benefit from this regimen due to primary treatment resistance or toxicity. Consequently, there is an urgent need to develop efficient biomarkers that can select patients who will benefit from immunotherapy thereby providing the appropriate treatment and avoiding toxicity. One of the biomarkers recently described for the stratification of NSCLC patients undergoing immunotherapy are mutations in STK11/LKB1, which are often associated with a lack of response to immunotherapy in some patients. Therefore, the purpose of this review is to describe the different cellular mechanisms associated with STK11/LKB1 mutations, which may explain the lack of response to immunotherapy. Moreover the review addresses the co-occurrence of additional mutations that may influence the response to immunotherapy and the current clinical studies that have further explored STK11/LKB1 as a predictive biomarker. Additionally this work includes the opportunities and limitations to look for the STK11/LKB1 status in the therapeutic strategy for NSCLC patients.

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.

Next Generation Sequencing-Based Profiling of Cell Free DNA in Patients with Advanced Non-Small Cell Lung Cancer: Advantages and Pitfalls

Lung cancer (LC) is the main cause of death for cancer worldwide and non-small cell lung cancer (NSCLC) represents the most common histology. The discovery of genomic alterations in driver genes that offer the possibility of therapeutic intervention has completely changed the approach to the diagnosis and therapy of advanced NSCLC patients, and tumor molecular profiling has become mandatory for the choice of the most appropriate therapeutic strategy. However, in approximately 30% of NSCLC patients tumor tissue is inadequate for biomarker analysis. The development of highly sensitive next generation sequencing (NGS) technologies for the analysis of circulating cell-free DNA (cfDNA) is emerging as a valuable alternative to assess tumor molecular landscape in case of tissue unavailability. Additionally, cfDNA NGS testing can better recapitulate NSCLC heterogeneity as compared with tissue testing. In this review we describe the main advantages and limits of using NGS-based cfDNA analysis to guide the therapeutic decision-making process in advanced NSCLC patients, to monitor the response to therapy and to identify mechanisms of resistance early. Therefore, we provide evidence that the implementation of cfDNA NGS testing in clinical research and in the clinical practice can significantly improve precision medicine approaches in patients with advanced NSCLC.

The Role of Intratumor Heterogeneity in the Response of Metastatic Non-Small Cell Lung Cancer to Immune Checkpoint Inhibitors

Immune checkpoint inhibitors (ICIs) represent one of the most promising therapeutic approaches in metastatic non-small cell lung cancer (M-NSCLC). Unfortunately, approximately 50–75% of patients do not respond to this treatment modality. Intratumor heterogeneity (ITH) at the genetic and phenotypic level is considered as a major cause of anticancer therapy failure, including resistance to ICIs. Recent observations suggest that spatial heterogeneity in the composition and spatial organization of the tumor microenvironment plays a major role in the response of M-NSCLC patients to ICIs. In this mini review, we first present a brief overview of the use of ICIs in M-NSCLC. We then discuss the role of genetic and non-genetic ITH on the efficacy of ICIs in patients with M-NSCLC.

Computational identification of biomarker genes for lung cancer considering treatment and non-treatment studies

BACKGROUND

Lung cancer is the number one cancer killer in the world with more than 142,670 deaths estimated in the United States alone in the year 2019. Consequently, there is an overreaching need to identify the key biomarkers for lung cancer. The aim of this study is to computationally identify biomarker genes for lung cancer that can aid in its diagnosis and treatment. The gene expression profiles of two different types of studies, namely non-treatment and treatment, are considered for discovering biomarker genes. In non-treatment studies healthy samples are control and cancer samples are cases. Whereas, in treatment studies, controls are cancer cell lines without treatment and cases are cancer cell lines with treatment.

RESULTS

The Differentially Expressed Genes (DEGs) for lung cancer were isolated from Gene Expression Omnibus (GEO) database using R software tool GEO2R. A total of 407 DEGs (254 upregulated and 153 downregulated) from non-treatment studies and 547 DEGs (133 upregulated and 414 downregulated) from treatment studies were isolated. Two Cytoscape apps, namely, CytoHubba and MCODE, were used for identifying biomarker genes from functional networks developed using DEG genes. This study discovered two distinct sets of biomarker genes - one from non-treatment studies and the other from treatment studies, each set containing 16 genes. Survival analysis results show that most non-treatment biomarker genes have prognostic capability by indicating low-expression groups have higher chance of survival compare to high-expression groups. Whereas, most treatment biomarkers have prognostic capability by indicating high-expression groups have higher chance of survival compare to low-expression groups.

CONCLUSION

A computational framework is developed to identify biomarker genes for lung cancer using gene expression profiles. Two different types of studies - non-treatment and treatment - are considered for experiment. Most of the biomarker genes from non-treatment studies are part of mitosis and play vital role in DNA repair and cell-cycle regulation. Whereas, most of the biomarker genes from treatment studies are associated to ubiquitination and cellular response to stress. This study discovered a list of biomarkers, which would help experimental scientists to design a lab experiment for further exploration of detail dynamics of lung cancer development.

Genetic Biomarkers: Implications of Increased Understanding and Identification in Lung Cancer Management

BACKGROUND

In the management of lung cancer, molecular profiling of the tumor is pivotal to defining a personalized treatment plan and is recommended for each patient.

OBJECTIVES

The purpose of this article is to provide an update on genomic testing in lung cancer and the associated targeted treatment options. In addition, emerging biomarkers and mechanisms of resistance are discussed.

METHODS

A comprehensive review of the CINAHL®, MEDLINE®, and PubMed® databases was performed.

FINDINGS

Molecular tumor profiling has advanced treatment options for patients diagnosed with lung cancer. Knowledge about pathologic variants and inhibitory pathways have led to the development of targeted treatments for lung cancer. Based on a solid understanding of molecular biomarkers, testing protocols, testing results, and how biomarkers affect treatment decisions, nurses can best educate and support patients and family members as clinical care incorporates molecular profiling.

What is the Burden of Proof for Tumor Mutational Burden in gliomas?

The treatment of patients with a variety of solid tumors has benefitted from immune checkpoint inhibition targeting the anti-programmed cell death-1 (PD-1)/programmed cell death ligand-1 (PD-L1) axis. The US Food and Drug Administration (FDA) granted accelerated approval of PD-1 inhibitor pembrolizumab for the treatment of adult and pediatric patients with TMB-high (TMB-H), solid tumors that have progressed following prior treatment and who have no other treatment options, including the extension to tumors of the Central Nervous System (CNS). In general, pan-cancer approvals are viewed positively to empower patients and clinicians. There are subsets (eg, BRAF, NTRK) for which this pathway for approval is appropriate. However, the pan-cancer FDA approval of pembrolizumab raises several concerns regarding the generalizability of the evidence to other tumor types, including managing patients with gliomas and other CNS tumors. The cut off for TMB-H is not well defined. There are intrinsic immunological differences between gliomas and other cancers types, including the immunosuppressive glioma microenvironment, the tumor's effects on systemic immune function, and the transformation of the T cell populations to an exhausted phenotype in glioma. Here we address the caveats with pan-cancer approvals concerning gliomas, complexities of the unique CNS immune environment, and discuss potential predictive biomarkers, including TMB, and explain why the recent approval should be applied with caution in CNS tumors.

ACAA1 Is a Predictive Factor of Survival and Is Correlated With T Cell Infiltration in Non-Small Cell Lung Cancer

Non-small cell lung cancer (NSCLC) is the predominant subtype of lung cancers. KRAS mutation is the second most prevalent mutation in NSCLC. KRAS mutant cancer cells suppress the anti-tumor T cell response. However, the underlying mechanism is still unknown. Here, we analyzed the differential expression of acetyl-CoA acyltransferase 1 (ACAA1) in various types of cancers using the TIMER database and validated the results in the NSCLC cell line H1944. We silenced oncogenic KRAS by siRNA targeting KRASG13D, and employed an MAPK signaling pathway inhibitor to clarify the possible regulatory pathway. Moreover, we analyzed the correlation of ACAA1 expression level with B cells, CD4+ T cells, CD8+ T cells, neutrophils, macrophages, and dendritic cells. Correlations between expression of ACAA1 and several biomarkers of mutation burden were also tested. Finally, we evaluated the prognostic value of ACAA1 in a wide range of cancers using the Kaplan-Meier Plotter Database. We found lower expression of ACAA1 in tumor tissue than in adjacent normal tissue in various cancers. This result was confirmed using a GEO dataset. Knock-down of mutant KRAS resulted in increased ACAA1 mRNA level in H1944 cells. ACAA1 mRNA level was significantly upregulated in H1944 after treatment with MAPK pathway inhibitor sorafenib, indicating that oncogenic KRAS may downregulate ACAA1 through MAPK signaling. ACAA1 was negatively correlated with biomarkers of tumor mutation burden, including BRCA1, ATM, ATR, CDK1, PMS2, MSH2, and MDH6. Conversely, ACAA1 expression was positively correlated with infiltrating CD4+ cells and with Th1, Th2, Treg cells in the lung tumor microenvironment. Finally, we showed that ACAA1 is a predictive factor for survival in several cancer types. In summary, decreased ACAA1 expression is correlated with poor prognosis and decreases immune infiltration of CD4+ T cells in LUAD and LUSC. ACAA1 also predicts T cell exhaustion in LUSC. The mechanism underlying KRAS/ACAA1 axis-mediated regulation of immune cell infiltration requires further investigation.

From Tumor Mutational Burden to Blood T Cell Receptor: Looking for the Best Predictive Biomarker in Lung Cancer Treated with Immunotherapy

Despite therapeutic advances, lung cancer (LC) is one of the leading causes of cancer morbidity and mortality worldwide. Recently, the treatment of advanced LC has experienced important changes in survival benefit due to immune checkpoint inhibitors (ICIs). However, overall response rates (ORR) remain low in unselected patients and a large proportion of patients undergo disease progression in the first weeks of treatment. Therefore, there is a need of biomarkers to identify patients who will benefit from ICIs. The programmed cell death ligand 1 (PD-L1) expression has been the first biomarker developed. However, its use as a robust predictive biomarker has been limited due to the variability of techniques used, with different antibodies and thresholds. In this context, tumor mutational burden (TMB) has emerged as an additional powerful biomarker based on the observation of successful response to ICIs in solid tumors with high TMB. TMB can be defined as the total number of nonsynonymous mutations per DNA megabases being a mechanism generating neoantigens conditioning the tumor immunogenicity and response to ICIs. However, the latest data provide conflicting results regarding its role as a biomarker. Moreover, considering the results of the recent data, the use of peripheral blood T cell receptor (TCR) repertoire could be a new predictive biomarker. This review summarises recent findings describing the clinical utility of TMB and TCRβ (TCRB) and concludes that immune, neontigen, and checkpoint targeted variables are required in combination for accurately identifying patients who most likely will benefit of ICIs.