Harmonization of Tumor Mutational Burden Quantification and Association With Response to Immune Checkpoint Blockade in Non-Small-Cell Lung Cancer

Integrated Germline and Somatic Features Reveal Divergent Immune Pathways Driving Response to Immune Checkpoint Blockade

Immune checkpoint blockade (ICB) has revolutionized cancer treatment; however, the mechanisms determining patient response remain poorly understood. Here, we used machine learning to predict ICB response from germline and somatic biomarkers and interpreted the learned model to uncover putative mechanisms driving superior outcomes. Patients with higher infiltration of T-follicular helper cells had responses even in the presence of defects in the MHC class-I (MHC-I). Further investigation uncovered different ICB responses in tumors when responses were reliant on MHC-I versus MHC-II neoantigens. Despite similar response rates, MHC II-reliant responses were associated with significantly longer durable clinical benefits (discovery: median overall survival of 63.6 vs. 34.5 months; P = 0.0074; validation: median overall survival of 37.5 vs. 33.1 months; P = 0.040). Characteristics of the tumor immune microenvironment reflected MHC neoantigen reliance, and analysis of immune checkpoints revealed LAG3 as a potential target in MHC II-reliant but not MHC I-reliant responses. This study highlights the value of interpretable machine learning models in elucidating the biological basis of therapy responses.

CTLA4 blockade abrogates KEAP1/STK11-related resistance to PD-(L)1 inhibitors

For patients with advanced non-small-cell lung cancer (NSCLC), dual immune checkpoint blockade (ICB) with CTLA4 inhibitors and PD-1 or PD-L1 inhibitors (hereafter, PD-(L)1 inhibitors) is associated with higher rates of anti-tumour activity and immune-related toxicities, when compared with treatment with PD-(L)1 inhibitors alone. However, there are currently no validated biomarkers to identify which patients will benefit from dual ICB1,2. Here we show that patients with NSCLC who have mutations in the STK11 and/or KEAP1 tumour suppressor genes derived clinical benefit from dual ICB with the PD-L1 inhibitor durvalumab and the CTLA4 inhibitor tremelimumab, but not from durvalumab alone, when added to chemotherapy in the randomized phase III POSEIDON trial3. Unbiased genetic screens identified loss of both of these tumour suppressor genes as independent drivers of resistance to PD-(L)1 inhibition, and showed that loss of Keap1 was the strongest genomic predictor of dual ICB efficacy-a finding that was confirmed in several mouse models of Kras-driven NSCLC. In both mouse models and patients, KEAP1 and STK11 alterations were associated with an adverse tumour microenvironment, which was characterized by a preponderance of suppressive myeloid cells and the depletion of CD8+ cytotoxic T cells, but relative sparing of CD4+ effector subsets. Dual ICB potently engaged CD4+ effector cells and reprogrammed the tumour myeloid cell compartment towards inducible nitric oxide synthase (iNOS)-expressing tumoricidal phenotypes that-together with CD4+ and CD8+ T cells-contributed to anti-tumour efficacy. These data support the use of chemo-immunotherapy with dual ICB to mitigate resistance to PD-(L)1 inhibition in patients with NSCLC who have STK11 and/or KEAP1 alterations.

Immune-related adverse events of antibody-based biological medicines in cancer therapy

Recombinant antibodies (Abs) are an integral modality for the treatment of multiple tumour malignancies. Since the Food and Drug Administration (FDA) approval of rituximab as the first monoclonal antibody (mAb) for cancer treatment, several mAbs and antibody (Ab)-based therapies have been approved for the treatment of solid tumour malignancies and other cancers. These Abs function by either blocking oncogenic pathways or angiogenesis, modulating immune response, or by delivering a conjugated drug. The use of Ab-based therapy in cancer patients who could benefit from the treatment, however, is still limited by associated toxicity profiles which may stem from biological features and processes related to target binding, alongside biochemical and/or biophysical characteristics of the therapeutic Ab. A significant immune-related adverse event (irAE) associated with Ab-based therapies is cytokine release syndrome (CRS), characterized by the development of fever, rash and even marked, life-threatening hypotension, and acute inflammation with secondary to systemic uncontrolled increase in a range of pro-inflammatory cytokines. Here, we review irAEs associated with specific classes of approved, Ab-based novel cancer immunotherapeutics, namely immune checkpoint (IC)-targeting Abs, bispecific Abs (BsAbs) and Ab-drug-conjugates (ADCs), highlighting the significance of harmonization in preclinical assay development for safety assessment of Ab-based biotherapeutics as an approach to support and refine clinical translation.

Agnostic drug development revisited

The advent of molecular profiling and the generalization of next generation sequencing in oncology has enabled the identification of patients who could benefit from targeted agents. Since the tumor-agnostic approval of pembrolizumab for patients with MSI-High tumors in 2017, different molecularly-guided therapeutics have been awarded approvals and progressively incorporated in the treatment landscape across multiple tumor types. As the number of tumor-agnostic targets considered druggable expands in the clinic, novel challenges will reshape the drug development field involving all the stakeholders in oncology. In this review, we provide an overview of current tumor-agnostic approvals and discuss promising candidate therapeutics for tumor-agnostic designation and challenges for their broad implementation.

Integrated germline and somatic features reveal divergent immune pathways driving ICB response

Immune Checkpoint Blockade (ICB) has revolutionized cancer treatment, however mechanisms determining patient response remain poorly understood. Here we used machine learning to predict ICB response from germline and somatic biomarkers and interpreted the learned model to uncover putative mechanisms driving superior outcomes. Patients with higher T follicular helper infiltrates were robust to defects in the class-I Major Histocompatibility Complex (MHC-I). Further investigation uncovered different ICB responses in MHC-I versus MHC-II neoantigen reliant tumors across patients. Despite similar response rates, MHC-II reliant responses were associated with significantly longer durable clinical benefit (Discovery: Median OS=63.6 vs. 34.5 months P=0.0074; Validation: Median OS=37.5 vs. 33.1 months, P=0.040). Characteristics of the tumor immune microenvironment reflected MHC neoantigen reliance, and analysis of immune checkpoints revealed LAG3 as a potential target in MHC-II but not MHC-I reliant responses. This study highlights the value of interpretable machine learning models in elucidating the biological basis of therapy responses.

A Dramatic Response to Second-Line Nivolumab and Ipilimumab in BRAF-V600-Mutated Metastatic Melanoma

Introduction

Current treatment options for BRAF V600-mutated unresectable stage III/IV melanoma include anti-PD-1 monotherapy or combination with anti-CTLA-4 or anti-LAG-3 agents, BRAF/MEK inhibitors, and clinical trials. The strategy of combination immunotherapy with nivolumab and ipilimumab has shown promising results, achieving higher response rates, longer duration of response, improved progression-free survival, and enhanced overall survival. The optimal sequence of treatments remains a topic of interest, with preliminary data suggesting a greater effectiveness of immunotherapy as the first-line approach. Preclinical trials have indicated that the efficacy of this sequence may be due to the modification of the immune environment by BRAF kinase inhibitors, leading to immune escape by tumor cells and resistance to immune checkpoint inhibitors.

Case Presentation

We present a case of a 72-year-old woman with high-burden metastatic melanoma who failed to respond to prior targeted therapy with BRAF/MEK inhibitors and exhibited a successful response to the second-line treatment with ipilimumab and nivolumab. We discuss the potential reasons for this positive outcome contributing to the current debate concerning treatment sequences, resistance mechanisms, and biomarkers predictive of response to immune checkpoint inhibitors in metastatic melanoma.

Conclusion

We believe that in few years the therapeutic algorithms in BRAF V600-mutated unresectable stage III/IV melanoma will be more complex since they will define clearly the correct therapeutic sequences with the inclusion of new immune checkpoint inhibitor drugs and multiple predictive biomarkers of response to better select patients eligible to immunotherapy.

Challenges and Future Directions in the Management of Tumor Mutational Burden-High (TMB-H) Advanced Solid Malignancies

A standardized assessment of Tumor Mutational Burden (TMB) poses challenges across diverse tumor histologies, treatment modalities, and testing platforms, requiring careful consideration to ensure consistency and reproducibility. Despite clinical trials demonstrating favorable responses to immune checkpoint inhibitors (ICIs), not all patients with elevated TMB exhibit benefits, and certain tumors with a normal TMB may respond to ICIs. Therefore, a comprehensive understanding of the intricate interplay between TMB and the tumor microenvironment, as well as genomic features, is crucial to refine its predictive value. Bioinformatics advancements hold potential to improve the precision and cost-effectiveness of TMB assessments, addressing existing challenges. Similarly, integrating TMB with other biomarkers and employing comprehensive, multiomics approaches could further enhance its predictive value. Ongoing collaborative endeavors in research, standardization, and clinical validation are pivotal in harnessing the full potential of TMB as a biomarker in the clinic settings.

Atezolizumab plus stereotactic ablative radiotherapy for medically inoperable patients with early-stage non-small cell lung cancer: a multi-institutional phase I trial

Stereotactic ablative radiotherapy (SABR) is a standard-of-care for medically-inoperable-early-stage non-small cell lung cancer (NSCLC). One third of patients progress and chemotherapy is rarely used in this population. We questioned if addition of the immune-checkpoint-inhibitor (ICI) atezolizumab to standard-of-care SABR can improve outcomes. We initiated a multi-institutional single-arm phase I study (NCT02599454) enrolling twenty patients with the primary endpoint of maximum tolerated dose (MTD); secondary endpoints of safety and efficacy; and exploratory mechanistic correlatives. Treatment is well tolerated and full dose atezolizumab (1200 mg) is the MTD. Efficacy signals include early responses (after 2 cycles of ICI, before initiation of SABR) in 17% of patients. Biomarkers of functional adaptive immunity, including T cell activation in the tumor and response to ex-vivo stimulation by circulating T cells, are highly predictive of benefit. These results require validation and are being tested in a phase III randomized trial.

Impact of TMB/PD-L1 expression and pneumonitis on chemoradiation and durvalumab response in stage III NSCLC

Although concurrent chemoradiation (CRT) and durvalumab consolidation has become a standard treatment for stage III non-small cell lung cancer (NSCLC), clinicopathologic and genomic factors associated with its efficacy remain poorly characterized. Here, in a multi-institutional retrospective cohort study of 328 patients treated with CRT and durvalumab, we identify that very high PD-L1 tumor proportion score (TPS) expression ( ≥ 90%) and increased tumor mutational burden (TMB) are independently associated with prolonged disease control. Additionally, we identify the impact of pneumonitis and its timing on disease outcomes among patients who discontinue durvalumab: compared to patients who experienced early-onset pneumonitis ( < 3 months) leading to durvalumab discontinuation, patients with late-onset pneumonitis had a significantly longer PFS (12.7 months vs not reached; HR 0.24 [95% CI, 0.10 to 0.58]; P = 0.001) and overall survival (37.2 months vs not reached; HR 0.26 [95% CI, 0.09 to 0.79]; P = 0.017). These findings suggest that opportunities exist to improve outcomes in patients with lower PD-L1 and TMB levels, and those at highest risk for pneumonitis.

Efficacy of PD-(L)1 blockade monotherapy compared with PD-(L)1 blockade plus chemotherapy in first-line PD-L1-positive advanced lung adenocarcinomas: a cohort study

BACKGROUND

Single-agent PD-(L)1 blockade (IO) alone or in combination with chemotherapy (Chemotherapy-IO) is approved first-line therapies in patients with advanced lung adenocarcinomas (LUADs) with PD-L1 expression ≥1%. These regimens have not been compared prospectively. The primary objective was to compare first-line efficacies of single-agent IO to Chemotherapy-IO in patients with advanced LUADs. Secondary objectives were to explore if clinical, pathological, and genomic features were associated with differential response to Chemotherapy-IO versus IO.

METHODS

This was a multicenter retrospective cohort study. Inclusion criteria were patients with advanced LUADs with tumor PD-L1 ≥1% treated with first-line Chemotherapy-IO or IO. To compare the first-line efficacies of single-agent IO to Chemotherapy-IO, we conducted inverse probability weighted Cox proportional hazards models using estimated propensity scores.

RESULTS

The cohort analyzed included 866 patients. Relative to IO, Chemotherapy-IO was associated with improved objective response rate (ORR) (44% vs 35%, p=0.007) and progression-free survival (PFS) in patients with tumor PD-L1≥1% (HR 0.84, 95% CI 0.72 to 0.97, p=0.021) or PD-L1≥50% (ORR 55% vs 38%, p<0.001; PFS HR 0.68, 95% CI 0.53 to 0.87, p=0.002). Using propensity-adjusted analyses, only never-smokers in the PD-L1≥50% subgroup derived a differential survival benefit from Chemotherapy-IO vs IO (p=0.013). Among patients with very high tumor PD-L1 expression (≥90%), there were no differences in outcome between treatment groups. No genomic factors conferred differential survival benefit to Chemotherapy-IO versus IO.

CONCLUSIONS

While the addition of chemotherapy to PD-(L)1 blockade increases the probability of initial response, never-smokers with tumor PD-L1≥50% comprise the only population identified that derived an apparent survival benefit with treatment intensification.

Narrative review: blood and tumor biomarker testing in non-small cell lung cancer without an oncogenic driver

Background and Objective

For patients with metastatic non-small cell lung cancer (NSCLC) without an oncogenic driver, systemic therapy with immune checkpoint inhibitors (ICIs) alone or in combination with chemotherapy have significantly improved the outcomes. However, the majority of patients do not have a durable response, and there is a need for additional predictive biomarkers. The objective of this narrative review is to describe potential biomarkers for immunotherapy.

Methods

Narrative overview of the literature synthesizing the findings of literature reporting retrospective, prospective, and subset analyses of studies investigating potential predictive biomarkers for ICI.

Key Content and Findings

Tumor expression of programmed death ligand-1 (PD-L1) is the only clinically available biomarker for patients receiving ICI-based therapy. However, PD-L1 has significant limitations and studies have investigated the predictive value of higher PD-L1 expression levels. There has been interest in tumor mutation burden (TMB) based on the premise that a higher TMB would be associated with a more neoantigens, which would increase the likelihood of an immune response. The studies to date have not revealed a consistent association with TMB level and survival benefit. Kelch-like ECH Associated Protein 1 (KEAP1) and serine/threonine kinase 11 (STK11) mutations have been associated with worse outcomes with ICI but these mutations appear to be associated with a worse prognosis, and not predictive for ICI. Tumor infiltrating lymphocytes (TIL's) are the mechanism of immune response, and there is interest in further investigating the presence, type and distribution of TIL's to predict immune benefit. Circulating tumor deoxyribonucleic acid (ctDNA) levels, at baseline and on treatment samples, are being investigated to assess response to therapy and long-term benefit of ICI.

Conclusions

None of the current biomarkers in development are validated for use in routine clinical care. Given the complexity of NSCLC biology and immune response to ICI most likely a composite biomarker using multiple biomarkers will need to be develop.

Multiparametric immune profiling of advanced cervical cancer to predict response to programmed death-1 inhibitor combination therapy: an exploratory study of the CLAP trial

PURPOSE

Checkpoint immunotherapy is a promising treatment option for advanced cervical cancer. To aid in selecting patients for this treatment, we identified potential predictors of the response to anti-PD-1 combination therapy.

METHODS

We simultaneously characterized CD8⁺, FoxP3⁺, PD-L1⁺, CD68⁺, CD31⁺, PANCK⁺, and PANCK^-PD-L1⁺ cells at the invasive margin (IM) of tumor by multispectral imaging of tissue sections from 37 patients with advanced cervical cancer in our previous trial cohort. The densities of each cell and cell-to-cell topography were compared between the responder and non-responder groups and evaluated for their predictive value in clinical response and survival.

RESULTS

CD8⁺ T cells, PD-L1⁺ cells, and PANCK^-PD-L1⁺ immune cells showed higher densities at the IM in the responders than in the non-responders (P = 0.022, 0.0094, and 0.049, respectively). A higher density of CD8⁺ T cells at the IM was related to prolonged progression-free survival (PFS; P = 0.031). A higher ratio of CD68⁺/CD8⁺ cells was found in the non-responder group (P = 0.003) and related to poor PFS (P = 0.016). A higher density of PANCK^-PD-L1⁺ immune cells within 20, 30, and 45 µm of PANCK⁺ tumor cells was correlated with better clinical response (P = 0.017, 0.017, and 0.02, respectively).

CONCLUSIONS

Multiparametric immune profiling of CD8⁺ T cells, PD-L1⁺ cells, CD68⁺ macrophages and PANCK^-PD-L1⁺ immune cells at the invasive margin may help identify patients with cervical cancer who may benefit from anti-PD-1 combination therapy.

CLINICAL TRIAL REGISTRATION

ClinicalTrials. gov identifier: NCT03816553, January 25, 2019.

Malignant neoplasm of the bronchi and lung: Russian clinical guidelines

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Association of High Tumor Mutation Burden in Non-Small Cell Lung Cancers With Increased Immune Infiltration and Improved Clinical Outcomes of PD-L1 Blockade Across PD-L1 Expression Levels

Importance

Although tumor mutation burden (TMB) has been explored as a potential biomarker of immunotherapy efficacy in solid tumors, there still is a lack of consensus about the optimal TMB threshold that best discriminates improved outcomes of immune checkpoint inhibitor therapy among patients with non-small cell lung cancer (NSCLC).

Objectives

To determine the association between increasing TMB levels and immunotherapy efficacy across clinically relevant programmed death ligand-1 (PD-L1) levels in patients with NSCLC.

Design, Setting, and Participants

This multicenter cohort study included patients with advanced NSCLC treated with immunotherapy who received programmed cell death-1 (PD-1) or PD-L1 inhibition in the Dana-Farber Cancer Institute (DFCI), Memorial Sloan Kettering Cancer Center (MSKCC), and in the Stand Up To Cancer (SU2C)/Mark Foundation data sets. Clinicopathological and genomic data were collected from patients between September 2013 and September 2020. Data analysis was performed from November 2021 to February 2022.

Exposures

Treatment with PD-1/PD-L1 inhibition without chemotherapy.

Main Outcomes and Measures

Association of TMB levels with objective response rate (ORR), progression-free survival (PFS), and overall survival (OS).

Results

In the entire cohort of 1552 patients with advanced NSCLC who received PD-1/PD-L1 blockade, the median (range) age was 66 (22-92) years, 830 (53.5%) were women, and 1347 (86.8%) had cancer with nonsquamous histologic profile. A regression tree modeling ORR as a function of TMB identified 2 TMB groupings in the discovery cohort (MSKCC), defined as low TMB (≤19.0 mutations per megabase) and high TMB (>19.0 mutations per megabase), which were associated with increasing improvements in ORR, PFS, and OS in the discovery cohort and in 2 independent cohorts (DFCI and SU2C/Mark Foundation). These TMB levels also were associated with significant improvements in outcomes of immunotherapy in each PD-L1 tumor proportion score subgroup of less than 1%, 1% to 49%, and 50% or higher. The ORR to PD-1/PD-L1 inhibition was as high as 57% in patients with high TMB and PD-L1 expression 50% or higher and as low as 8.7% in patients with low TMB and PD-L1 expression less than 1%. Multiplexed immunofluorescence and transcriptomic profiling revealed that high TMB levels were associated with increased CD8-positive, PD-L1-positive T-cell infiltration, increased PD-L1 expression on tumor and immune cells, and upregulation of innate and adaptive immune response signatures.

Conclusions and Relevance

These findings suggest that increasing TMB levels are associated with immune cell infiltration and an inflammatory T-cell-mediated response, resulting in increased sensitivity to PD-1/PD-L1 blockade in NSCLC across PD-L1 expression subgroups.

[Immunotherapy for non-small cell lung cancer (NSCLC)]

Within a few years the introduction of immune checkpoint inhibitors (ICI) fundamentally changed the treatment landscape of patients with metastatic non-small cell lung cancer (NSCLC) and improved survival for a relevant proportion of patients. Immune monotherapies are highly efficient in cancers showing a PD-L1 overexpression ≥ 50% of tumor cells, all others with a lower level and independent from the PD-L1 expression can be treated with various treatment combinations. In a curative setting all PD-L1 positive patients (≥ 1%) who underwent chemoradiotherapy to reduce disease relapse and subsequently to improve survival should undergo an ICI maintenance treatment. Furthermore, positive results from phase III studies are also available for adjuvant treatment of patients with resectable NSCLC, whereby an EMA approval is currently pending. The treatment with ICIs has given rise to a new class of immune-mediated adverse side effects, which occur in approximately one third of the patients and range from easily substituted endocrinopathies to life-threatening organ toxicity. An anticipatory monitoring as well as interdisciplinary treatment are therefore the keys to avoiding progression of higher grade potentially fatal toxicities.

Potential prognosis index for m6A-related mRNA in cholangiocarcinoma

Background

Cholangiocarcinoma (CHOL) is a malignant tumor that originates in the extrahepatic bile duct and can extend from the hilar region to the lower end of the common bile duct. The prognosis of CHOL patients is particularly poor; therefore, in this study, we screened mRNAs correlated with N6-methyladenosine (m⁶A) to construct a risk model for prognosis in CHOL.

Methods

The TCGA-CHOL dataset was applied to obtain and analyze the coexpression of 1281 m⁶A-related mRNAs, from which 14 were selected for further analysis through univariate proportional hazards (cox) regression analysis. Aryl hydrocarbon receptor interacting protein (AIP), CCAAT/enhancer binding protein beta (CEBPB), syndecan1 (SDC1), vacuolar protein sorting 25 homolog (VPS25) and syntaxin binding protein 2 (STXBP2) were then screened out through the least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analysis to develop a precise m⁶A-related mRNA prognosis risk model (MRMRPM) with an area under curve (AUC) of 0.908 and 0.923 after 1 and 2 years, respectively. We divided the samples into high-risk and low-risk groups using the m⁶A-related mRNA prognosis risk model.

Results

Kaplan–Meier analysis indicated poor overall survival (OS) for the high-risk group. Two Gene Expression Omnibus (GEO) datasets (GSE89748 and GSE107943) were used to validate the risk model. The results of drug sensitivity and immune cell infiltration analysis showed that the risk model could serve as a prognosis index of potential immunotherapeutic characteristics and drug sensitivity. Furthermore, the proportion of resting dendritic cells and regulatory T cells was positively associated with an increased expression of four m⁶A-related mRNAs — AIP, CEBPB, SDC1, and VPS25 — in the high-risk CHOL group.

Conclusions

Our findings suggest that this model can be a prognostic indicator for CHOL patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09665-3.

Pathological Response and Immune Biomarker Assessment in Non-Small-Cell Lung Carcinoma Receiving Neoadjuvant Immune Checkpoint Inhibitors

Simple Summary

Recently, the U.S. Food and Drug Administration (FDA) approved neoadjuvant immunotherapy plus chemotherapy for the treatment of resectable non-small-cell lung carcinoma (NSCLC) due to the clinical benefits reported in several clinical trials. In these settings, the pathological assessment of the tumor bed to quantify a pathological response has been used as a surrogate method of clinical benefit to neoadjuvant therapy. In addition, several clinical trials are including the assessment of tissue-, blood-, or host-based biomarkers to predict therapy response and to monitor the response to neoadjuvant treatment. In this manuscript, we provide an overview of current recommendations for the evaluation of pathological response and describe potential biomarkers used in clinical trials of neoadjuvant immunotherapy in resectable NSCLC.

Abstract

Lung cancer is the leading cause of cancer incidence and mortality worldwide. Adjuvant and neoadjuvant chemotherapy have been used in the perioperative setting of non-small-cell carcinoma (NSCLC); however, the five-year survival rate only improves by about 5%. Neoadjuvant treatment with immune checkpoint inhibitors (ICIs) has become significant due to improved survival in advanced NSCLC patients treated with immunotherapy agents. The assessment of pathology response has been proposed as a surrogate indicator of the benefits of neaodjuvant therapy. An outline of recommendations has been published by the International Association for the Study of Lung Cancer (IASLC) for the evaluation of pathologic response (PR). However, recent studies indicate that evaluations of immune-related changes are distinct in surgical resected samples from patients treated with immunotherapy. Several clinical trials of neoadjuvant immunotherapy in resectable NSCLC have included the study of biomarkers that can predict the response of therapy and monitor the response to treatment. In this review, we provide relevant information on the current recommendations of the assessment of pathological responses in surgical resected NSCLC tumors treated with neoadjuvant immunotherapy, and we describe current and potential biomarkers to predict the benefits of neoadjuvant immunotherapy in patients with resectable NSCLC.

Computational methods and translational applications for targeted next-generation sequencing platforms

During the past decade, next-generation sequencing (NGS) technologies have become widely adopted in cancer research and clinical care. Common applications within the clinical setting include patient stratification into relevant molecular subtypes, identification of biomarkers of response and resistance to targeted and systemic therapies, assessment of heritable cancer risk based on known pathogenic variants, and longitudinal monitoring of treatment response. The need for efficient downstream processing and reliable interpretation of sequencing data has led to the development of novel algorithms and computational pipelines, as well as structured knowledge bases that link genomic alterations to currently available drugs and ongoing clinical trials. Cancer centers around the world use different types of targeted solid-tissue and blood based NGS assays to analyze the genomic and transcriptomic profile of patients as part of their routine clinical care. Recently, cross-institutional collaborations have led to the creation of large pooled datasets that can offer valuable insights into the genomics of rare cancers.

Immune biomarkers and response to checkpoint inhibition of BRAFV600 and BRAF non-V600 altered lung cancers

BACKGROUND

While 2-4% of lung cancers possess alterations in BRAF, little is known about the immune responsiveness of these tumours.

METHODS

Clinical and genomic data were collected from 5945 patients with lung cancers whose tumours underwent next-generation sequencing between 2015 and 2018. Patients were followed through 2020.

RESULTS

In total, 127 patients with metastatic BRAF-altered lung cancers were identified: 29 tumours had Class I mutations, 59 had Class II/III alterations, and 39 had variants of unknown significance (VUS). Tumour mutation burden was higher in Class II/III than Class I-altered tumours (8.8 mutations/Mb versus 4.9, P < 0.001), but this difference was diminished when stratified by smoking status. The overall response rate to immune checkpoint inhibitors (ICI) was 9% in Class I-altered tumours and 26% in Class II/III (P = 0.25), with median time on treatment of 1.9 months in both groups. Among patients with Class I-III-altered tumours, 36-month HR for death in those who ever versus never received ICI was 1.82 (1.17-6.11). Nine patients were on ICI for >2 years (two with Class I mutations, two with Class II/III alterations, and five with VUS).

CONCLUSIONS

A subset of patients with BRAF-altered lung cancers achieved durable disease control on ICI. However, collectively no significant clinical benefit was seen.

Biomarkers of response to checkpoint inhibitors beyond PD-L1 in lung cancer

Immunotherapy, including use of checkpoint inhibitors against PD-1, PD-L1, and CTLA-4, forms the backbone of oncologic management for the majority of non-small cell lung carcinoma patients. However, response to these therapies varies widely, from patients who have complete resolution of metastatic disease and long-term remission, to those who rapidly progress and succumb to their cancer despite use of the newest checkpoint inhibitors. While PD-L1 protein expression by immunohistochemistry serves as the principle predictive biomarker for immunotherapy response, neither the sensitivity nor the specificity of this approach is optimal, and clinical PD-L1 testing is plagued by concerns around result reproducibility and confusion born from the proliferation of different companion diagnostic assays. At the same time, insights into tumor and host immune-specific factors that inform both prognosis and response prediction are beginning to define better immunotherapy biomarkers. Beyond immune checkpoint expression status, common themes in analyses of immunotherapy response prediction include cancer neoantigen production, the state of the antigen presentation pathway in both tumor and antigen presenting cells, the admixture of effector and suppressor immune cells in the tumor microenvironment, and the genomic drivers and comutations that can influence the all of these variables. This review will address the state of PD-L1 testing in lung cancer, the role for tumor mutation burden as a predictive biomarker, the evolving status of human leukocyte antigen/major histocompatibility complex expression as a marker of antigen presentation, approaches to tumor immune cell quantitation including by multiplex immunofluorescence, and the importance of tumor genomic profiling to ascertain oncogenic driver (EGFR, ALK, KRAS, MET, etc.) and co-mutation (STK11, KEAP1, SMARCA4) status.

Insertion-deletion rate is a qualitative aspect of the tumor mutation burden associated with the clinical outcomes of gastric cancer patients treated with nivolumab

BACKGROUND

We aimed to investigate the clinical implications of the tumor mutation burden (TMB) and insertion-deletion (indel) rate in gastric cancer patients treated with nivolumab.

METHODS

A total of 105 patients with advanced gastric cancer who were treated with nivolumab as third or later line of therapy were included as the study population. The indel rate was defined as the proportion of indels making up the TMB.

RESULTS

The median age was 58 (32-78 years), and 65 (61.9%) were men. Patients with TMB > 18.03/Mb showed superior progression-free survival (PFS) and overall survival (OS) compared to those with TMB ≤ 18.03/Mb. Patients with a high indel rate (> 40%) had a favorable PFS and OS compared to those with a lower indel rate (≤ 40%) (P = 0.009 and P = 0.007, respectively). The association between a high indel rate and favorable PFS and OS was prominent in a subgroup with TMB > 18.03/Mb (P < 0.001 and P = 0.007 for PFS and OS, respectively), but not in that with TMB ≤ 18.03/Mb. All five patients with deficient-MMR fell into the category of 'TMB > 18.03/Mb with an indel rate of > 40%. TMB ≥ 18.03/Mb with an indel rate of > 40% was independently associated with a favorable PFS (hazard ratio [HR] 0.07, P = 0.012) and OS (HR 0.09, P = 0.023).

CONCLUSION

TMB and indel rate should be jointly considered to better predict survival outcomes of gastric cancer patients treated with nivolumab. Our findings deserve further investigation and validation in future studies.

Artificial intelligence-aided clinical annotation of a large multi-cancer genomic dataset

To accelerate cancer research that correlates biomarkers with clinical endpoints, methods are needed to ascertain outcomes from electronic health records at scale. Here, we train deep natural language processing (NLP) models to extract outcomes for participants with any of 7 solid tumors in a precision oncology study. Outcomes are extracted from 305,151 imaging reports for 13,130 patients and 233,517 oncologist notes for 13,511 patients, including patients with 6 additional cancer types. NLP models recapitulate outcome annotation from these documents, including the presence of cancer, progression/worsening, response/improvement, and metastases, with excellent discrimination (AUROC > 0.90). Models generalize to cancers excluded from training and yield outcomes correlated with survival. Among patients receiving checkpoint inhibitors, we confirm that high tumor mutation burden is associated with superior progression-free survival ascertained using NLP. Here, we show that deep NLP can accelerate annotation of molecular cancer datasets with clinically meaningful endpoints to facilitate discovery.

Clinicopathologic Features and Response to Therapy of NRG1 Fusion-Driven Lung Cancers: The eNRGy1 Global Multicenter Registry

PURPOSE

Although NRG1 fusions are oncogenic drivers across multiple tumor types including lung cancers, these are difficult to study because of their rarity. The global eNRGy1 registry was thus established to characterize NRG1 fusion-positive lung cancers in the largest and most diverse series to date.

METHODS

From June 2018 to February 2020, a consortium of 22 centers from nine countries in Europe, Asia, and the United States contributed data from patients with pathologically confirmed NRG1 fusion-positive lung cancers. Profiling included DNA-based and/or RNA-based next-generation sequencing and fluorescence in situ hybridization. Anonymized clinical, pathologic, molecular, and response (RECIST v1.1) data were centrally curated and analyzed.

RESULTS

Although the typified never smoking (57%), mucinous adenocarcinoma (57%), and nonmetastatic (71%) phenotype predominated in 110 patients with NRG1 fusion-positive lung cancer, further diversity, including in smoking history (43%) and histology (43% nonmucinous and 6% nonadenocarcinoma), was elucidated. RNA-based testing identified most fusions (74%). Molecularly, six (of 18) novel 5' partners, 20 unique epidermal growth factor domain-inclusive chimeric events, and heterogeneous 5'/3' breakpoints were found. Platinum-doublet and taxane-based (post-platinum-doublet) chemotherapy achieved low objective response rates (ORRs 13% and 14%, respectively) and modest progression-free survival medians (PFS 5.8 and 4.0 months, respectively). Consistent with a low programmed death ligand-1 expressing (28%) and low tumor mutational burden (median: 0.9 mutations/megabase) immunophenotype, the activity of chemoimmunotherapy and single-agent immunotherapy was poor (ORR 0%/PFS 3.3 months and ORR 20%/PFS 3.6 months, respectively). Afatinib achieved an ORR of 25%, not contingent on fusion type, and a 2.8-month median PFS.

CONCLUSION

NRG1 fusion-positive lung cancers were molecularly, pathologically, and clinically more heterogeneous than previously recognized. The activity of cytotoxic, immune, and targeted therapies was disappointing. Further research examining NRG1-rearranged tumor biology is needed to develop new therapeutic strategies.

Nivolumab in combination with cabozantinib for metastatic triple-negative breast cancer: a phase II and biomarker study

This single-arm phase II study investigated the efficacy and safety of cabozantinib combined with nivolumab in metastatic triple-negative breast cancer (mTNBC). The primary endpoint was objective response rate (ORR) by RECIST 1.1. Biopsies at baseline and after cycle 1 were analyzed for tumor-infiltrating lymphocytes (TILs), PD-L1, and whole-exome and transcriptome sequencing. Only 1/18 patients achieved a partial response (ORR 6%), and the trial was stopped early. Toxicity led to cabozantinib dose reduction in 50% of patients. One patient had a PD-L1-positive tumor, and three patients had TILs > 10%. The responding patient had a PD-L1-negative tumor with low tumor mutational burden but high TILs and enriched immune gene expression. High pretreatment levels of plasma immunosuppressive cytokines, chemokines, and immune checkpoint molecules were associated with rapid progression. Although this study did not meet its primary endpoint, immunostaining, genomic, and proteomic studies indicated a high degree of tumor immunosuppression in this mTNBC cohort.

Comprehensive assessment of PD-L1 expression, tumor mutational burden and oncogenic driver alterations in non-small cell lung cancer patients treated with immune checkpoint inhibitors

OBJECTIVES

Immune checkpoint inhibitors (ICIs) have proven to be effective treatment for lung cancer. However, a precise predictive immuno-oncology biomarker is still under development. We investigated the associations among PD-L1 expression, tumor mutational burden (TMB), and oncogenic driver alterations in advanced non-small cell lung cancer (NSCLC) patients treated with ICIs.

MATERIALS AND METHODS

This multicenter cohort study included 1017 lung cancer patients. PD-L1 expression using four IHC assays (22C3, 28-8, SP263, SP142), TMB by whole-exome sequencing and oncogenic driver alterations were analyzed comprehensively. Clinical characteristics, treatment and survival data were collected.

RESULTS

The results of 22C3 and 28-8 for PD-L1 expression showed acceptable concordance (k = 0.89; 95% confidence interval [CI], 0.87-0.92), and the clinical outcomes of ICIs classified according to PD-L1 expression by both assays were also approximately the same. There was slight concordance (k = 0.16; 95% CI, 0.11-0.22) between 22C3 and SP142, and high PD-L1 expression by SP142 was correspond to very high PD-L1 expressions by other assays. Patients with both high PD-L1 expression and high TMB showed a good response to ICIs with the response rate of 64% and median progression-free survival of 9.0 months despite of small population. Common EGFR or STK11 mutations showed a lower rate of high PD-L1 expression and a worse efficacy of ICIs and KRAS mutations had no negative impact on response to ICIs.

CONCLUSION

Comprehensive assessment of PD-L1 expression, TMB, and oncogenic driver alterations would help to better predict the clinical outcomes of ICIs in NSCLC patients.

Enhanced Antitumor Response to Immune Checkpoint Blockade Exerted by Cisplatin-Induced Mutagenesis in a Murine Melanoma Model

Sequencing data from different types of cancers including melanomas demonstrate that tumors with high mutational loads are more likely to respond to immune checkpoint blockade (ICB) therapies. We have previously shown that low-dose intratumoral injection of the chemotherapeutic DNA damaging drug cisplatin activates intrinsic mutagenic DNA damage tolerance pathway, and when combined with ICB regimen leads to tumor regression in the mouse YUMM1.7 melanoma model. We now report that tumors generated with an in vitro cisplatin-mutagenized YUMM1.7 clone (YUMM1.7-CM) regress in response to ICB, while an identical ICB regimen alone fails to suppress growth of tumors generated with the parental YUMM1.7 cells. Regressing YUMM1.7-CM tumors show greater infiltration of CD8 T lymphocytes, higher granzyme B expression, and higher tumoral cell death. Similarly, ex-vivo, immune cells isolated from YUMM1.7-CM tumors-draining lymph nodes (TDLNs) co-incubated with cultured YUMM1.7-CM cells, eliminate the tumor cells more efficiently than immune cells isolated from TDLNs of YUMM1.7 tumor-bearing mice. Collectively, our findings show that in vitro induced cisplatin mutations potentiate the antitumor immune response and ICB efficacy, akin to tumor regression achieved in the parental YUMM1.7 model by ICB administered in conjunction with intratumoral cisplatin injection. Hence, our data uphold the role of tumoral mutation burden in improving immune surveillance and response to ICB, suggesting a path for expanding the range of patients benefiting from ICB therapy.

Integrating endobronchial ultrasound bronchoscopy with molecular testing of immunotherapy biomarkers in non-small cell lung cancer

Immunotherapy has transformed treatment of advanced non-small-cell lung cancer (NSCLC) patients leading to remarkable long-term survival benefit. However, only about 20% of advanced NSCLC patients typically respond to immune checkpoint inhibitors (ICIs) that target the PD-1/PD-L1 pathway. The only validated biomarker for ICI therapy is the PD-L1 immunohistochemistry (IHC) test, which is considered an imperfect assay due to several variables including availability and integrity of tumour tissue, variability in staining/scoring techniques and heterogeneity in PD-L1 protein expression within and across tumour biopsies. Herein, we discuss integrating minimally invasive EBUS bronchoscopy procedures with novel molecular approaches to improve accuracy and sensitivity of PD-L1 testing. EBUS guided bronchoscopy facilitates repeated sampling of tumour tissue to increase the probability of detecting PD-L1 positive tumours. Since intra-tumoural PD-L1 (CD274) copy number is reported to be less heterogeneous than PD-L1 protein detection, quantifying PD-L1 transcript levels may increase detection of PD-L1 positive tumours. PD-L1 transcript levels show excellent concordance with PD-L1 IHC scoring and multiplex digital droplet PCR (ddPCR) assays that quantify absolute PD-L1 transcript copy number have been developed. ddPCR can also be automated for high throughput detection of low abundant variants with excellent sensitivity and accuracy to improve the broader application of diagnostic cut-off values. Optimizing diagnostic workflows that integrate optimal EBUS bronchoscopy procedures with emerging molecular ICI biomarker assays may improve the selection criteria for ICI therapy benefit.

Genomic profiling of advanced cervical cancer to predict response to programmed death-1 inhibitor combination therapy: a secondary analysis of the CLAP trial

BACKGROUND

The Camrelizumab Plus Apatinib in Patients with Advanced Cervical Cancer trial was a single-arm, phase II study that showed promising activity of the programmed death-1 (PD-1) inhibitor camrelizumab plus the vascular endothelial growth factor receptor-2 inhibitor apatinib in patients with advanced cervical cancer. However, the predictive biomarkers for treatment outcomes are unknown. In this study, we aimed to identify potential predictors of treatment response in PD-1 inhibitor combination therapy.

METHODS

Genomic profiling was performed on patients with available biopsy or surgical samples by targeted next-generation sequencing of 425 cancer-related genes in this preplanned, secondary analysis. Somatic alterations, including all non-synonymous mutations, and tumor mutational burden (TMB) were assessed for their predictive values in objective response rate, progression-free survival (PFS), and overall survival (OS).

RESULTS

A subset of 32 patients was included in this analysis. Top altered genes included PIK3CA (43.8%), STK11 (25%), FBXW7 (15.6%), and PTEN (15.6%). The PI3K/AKT pathway was among the most frequently dysregulated pathways, and its genetic alterations were identified in 68.8% of patients. PIK3CA (PFS HR 0.33, p=0.05; OS HR 0.23, p=0.04) and PTEN (PFS HR 3.71^e-09, p=0.05; OS HR 3.64^e-09, p=0.08) alterations were associated with improved outcomes. PI3K/AKT pathway genetic alterations showed improved predictive power compared with either PIK3CA or PTEN alterations alone (PFS HR 0.33, p=0.03; OS HR 0.25, p=0.02), while ERBB3 mutations (PFS HR 34.9, p<0.001; OS HR 19.8, p<0.001) correlated with poor survival. TMB-high (≥5 mut/Mb) was associated with prolonged PFS (HR 0.26, p<0.01) and OS (HR 0.31, p=0.05). Multivariate analysis showed ERBB3 mutations (PFS p=0.01, OS p<0.001), PD-L1 positive (PFS p=0.01, OS p=0.05), and high TMB (PFS p=0.01, OS p=0.05) remained significantly associated with survival.

CONCLUSIONS

We uncovered that genetic alterations in PIK3CA, PTEN, ERBB3, and PI3K/AKT pathway, as well as TMB, could be novel predictive biomarkers in patients with cervical cancer treated with PD-1 inhibitor combination therapy.

TRIAL REGISTRATION NUMBER

NCT03816553.

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.

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

BACKGROUND

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

PATIENTS AND METHODS

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

RESULTS

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

CONCLUSIONS

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

Prospective development and validation of a liquid immune profile-based signature (LIPS) to predict response of patients with recurrent/metastatic cancer to immune checkpoint inhibitors

Background

The predictive power of novel biological markers for treatment response to immune checkpoint inhibitors (ICI) is still not satisfactory for the majority of patients with cancer. One should identify valid predictive markers in the peripheral blood, as this is easily available before and during treatment. The current interim analysis of patients of the ST-ICI cohort therefore focuses on the development and validation of a liquid immune profile-based signature (LIPS) to predict response of patients with metastatic cancer to ICI targeting the programmed cell death protein 1 (PD-1)/programmed cell death-ligand 1 (PD-L1) axis.

Methods

A total of 104 patients were prospectively enrolled. 54 immune cell subsets were prospectively analyzed in patients’ peripheral blood by multicolor flow cytometry before treatment with ICI (pre-ICI; n=89), and after the first application of ICI (n=65). Pre-ICI, patients were randomly allocated to a training (n=56) and a validation cohort (n=33). Univariate Cox proportional hazards regression analysis and least absolute shrinkage and selection operator Cox model were used to create a predictive immune signature, which was also checked after the first ICI, to consider the dynamics of changes in the immune status.

Results

Whole blood samples were provided by 89 patients pre-ICI and by 65 patients after the first ICI. We identified a LIPS which is based on five immune cell subtypes: CD14^high monocytes, CD8+/PD-1⁺ T cells, plasmacytoid dendritic cells, neutrophils, and CD3⁺/CD56⁺/CD16⁺ natural killer (NK)T cells. The signature achieved a high accuracy (C-index 0.74 vs 0.71) for predicting overall survival (OS) benefit in both the training and the validation cohort. In both cohorts, the low-risk group had significantly longer OS than the high-risk group (HR 0.26, 95% CI 0.12 to 0.56, p=0.00025; HR 0.30, 95% CI 0.10 to 0.91, p=0.024, respectively). Regarding the whole cohort, LIPS also predicted progression-free survival (PFS). The identified LIPS was not affected by clinicopathological features with the exception of brain metastases. NKT cells and neutrophils of the LIPS can be used as dynamic predictive biomarkers for OS and PFS after first administration of the ICI.

Conclusion

Our study identified a predictive LIPS for survival of patients with cancer treated with PD-1/PD-L1 ICI, which is based on immune cell subsets in the peripheral whole blood.

Trial registration number

NCT03453892.

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.

Meta-analysis of tumor- and T cell-intrinsic mechanisms of sensitization to checkpoint inhibition

Checkpoint inhibitors (CPIs) augment adaptive immunity. Systematic pan-tumor analyses may reveal the relative importance of tumor-cell-intrinsic and microenvironmental features underpinning CPI sensitization. Here, we collated whole-exome and transcriptomic data for >1,000 CPI-treated patients across seven tumor types, utilizing standardized bioinformatics workflows and clinical outcome criteria to validate multivariable predictors of CPI sensitization. Clonal tumor mutation burden (TMB) was the strongest predictor of CPI response, followed by total TMB and CXCL9 expression. Subclonal TMB, somatic copy alteration burden, and histocompatibility leukocyte antigen (HLA) evolutionary divergence failed to attain pan-cancer significance. Dinucleotide variants were identified as a source of immunogenic epitopes associated with radical amino acid substitutions and enhanced peptide hydrophobicity/immunogenicity. Copy-number analysis revealed two additional determinants of CPI outcome supported by prior functional evidence: 9q34 (TRAF2) loss associated with response and CCND1 amplification associated with resistance. Finally, single-cell RNA sequencing (RNA-seq) of clonal neoantigen-reactive CD8 tumor-infiltrating lymphocytes (TILs), combined with bulk RNA-seq analysis of CPI-responding tumors, identified CCR5 and CXCL13 as T-cell-intrinsic markers of CPI sensitivity.

KRASG12C/TP53 co-mutations identify long-term responders to first line palliative treatment with pembrolizumab monotherapy in PD-L1 high (≥50%) lung adenocarcinoma

Background

Pembrolizumab is a standard of care as first line palliative therapy in PD-L1 overexpressing (≥50%) non-small cell lung cancer (NSCLC). This study aimed at the identification of KRAS and TP53-defined mutational subgroups in the PD-L1 high population to distinguish long-term responders from those with limited benefit.

Methods

In this retrospective, observational study, patients from 4 certified lung cancer centers in Berlin, Germany, having received pembrolizumab monotherapy as first line palliative treatment for lung adenocarcinoma (LuAD) from 2017 to 2018, with PD-L1 expression status and targeted NGS data available, were evaluated.

Results

A total of 119 patients were included. Rates for KRAS, TP53 and combined mutations were 52.1%, 47.1% and 21.9%, respectively, with no association given between KRAS and TP53 mutations (P=0.24). By trend, PD-L1 expression was higher in KRAS-positive patients (75% vs. 65%, P=0.13). Objective response rate (ORR), median progression-free survival (PFS) and overall survival (OS) in the KRAS^G12C group (n=32, 51.6%) were 63.3%, 19.8 months (mo.) and not estimable (NE), respectively. Results in KRAS^other and wild type patients were similar and by far lower (42.7%, P=0.06; 6.2 mo., P<0.001; 23.4 mo., P=0.08). TP53 mutations alone had no impact on response and survival. However, KRAS^G12C/TP53 co-mutations (n=12) defined a subset of long-term responders (ORR 100.0%, PFS 33.3 mo., OS NE). In contrast, patients with KRAS^other/TP53 mutations showed a dismal prognosis (ORR 27.3%, P=0.002; PFS 3.9 mo., P=0.001, OS 9.7 mo., P=0.02).

Conclusions

A comprehensive assessment of KRAS subtypes and TP53 mutations allows a highly relevant prognostic differentiation of patients with metastatic, PD-L1 high LuAD treated upfront with pembrolizumab.

The interplay between cancer type, panel size and tumor mutational burden threshold in patient selection for cancer immunotherapy

The tumor mutational burden (TMB) is increasingly recognized as an emerging biomarker that predicts improved outcomes or response to immune checkpoint inhibitors in cancer. A multitude of technical and biological factors make it difficult to compare TMB values across platforms, histologies, and treatments. Here, we present a mechanistic model that explains the association between panel size, histology, and TMB threshold with panel performance and survival outcome and demonstrate the limitations of existing methods utilized to harmonize TMB across platforms.

An increasing number of studies have demonstrated the benefit of tumor mutation burden (TMB), the number of non-silent mutations in the genome, as a predictive biomarker in a clinical setting. Most clinical trials utilize a smaller panel, instead of whole exome sequencing (WES), to estimate the exome-wide mutational load. However, the use of panels introduces panel size dependent sampling noise that could affect the performance of the TMB biomarker. In this work we create a mathematical model of the cancer histology, treatment response, and TMB device system to assess the interplay between cancer type, panel size and tumor mutational burden threshold in patient selection for cancer immunotherapy.

Identification and Utilization of Biomarkers to Predict Response to Immune Checkpoint Inhibitors

Immune checkpoint inhibitors (ICPI) have revolutionized cancer therapy and provided clinical benefit to thousands of patients. Despite durable responses in many tumor types, the majority of patients either fail to respond at all or develop resistance to the ICPI. Furthermore, ICPI treatment can be accompanied by serious adverse effects. There is an urgent need for identification of patient populations that will benefit from ICPI as single agents and when used in combinations. As ICPI have achieved regulatory approvals, accompanying biomarkers including PD-L1 immunohistochemistry (IHC) and tumor mutational burden (TMB) have also received approvals for some indications. The ICPI pembrolizumab was the first example of a tissue-agnostic FDA approval based on tumor microsatellite instability (MSI)/deficient mismatch repair (dMMR) biomarker status, rather than on tumor histology assessment. Several other ICPI-associated biomarkers are in the exploratory stage, including quantification of tumor-infiltrating lymphocytes (TILs), gene expression profiling (GEP) of an inflamed microenvironment, and neoantigen prediction. TMB and PD-L1 expression can predict a subset of responses, but they fail to predict all responses to checkpoint blockade. While a single biomarker is currently limited in its ability to fully capture the complexity of the tumor-immune microenvironment, a combination of biomarkers is emerging as a method to improve predictive power. Here we review the steadily growing impact of comprehensive genomic profiling (CGP) for development and utilization of predictive biomarkers by simultaneously capturing TMB, MSI, and the status of genomic targets that confer sensitivity or resistance to immunotherapy, as well as detecting inflammation through RNA expression signatures.

Discovery through clinical sequencing in oncology

The molecular characterization of tumors now informs clinical cancer care for many patients. This advent of molecular oncology is driven by the expanding number of therapeutic biomarkers that can predict sensitivity to both approved and investigational agents. Beyond its role in driving clinical trial enrollments and guiding therapy in individual patients, large-scale clinical genomics in oncology also represents a rapidly expanding research resource for translational scientific discovery. Here, we review the progress, opportunities, and challenges of scientific and translational discovery from prospective clinical genomic screening programs now routinely conducted in cancer patients.

Emerging drugs for small cell lung cancer: a focused review on immune checkpoint inhibitors

INTRODUCTION

Small cell lung cancer (SCLC) is an aggressive malignancy that accounts for 15% of all lung cancers. It is characterized by initial responsiveness to therapy followed by rapid disease progression that is relatively resistant to further treatment. Recently, the addition of an immune checkpoint inhibitor (ICI) to chemotherapy has improved survival in patients with advanced disease, the first advance in systemic therapy in SCLC in over 30 years.

AREAS COVERED

In this review, we present an overview of SCLC with a focus on the scope of the problem and standard treatment, followed by a critical assessment of scientific rationale for immunotherapy in SCLC and the clinical trials that have been performed with ICIs in SCLC. Finally, we address ongoing hurdles for the development of ICIs in SCLC and potential avenues for further study.

EXPERT OPINION

Despite solid biological rationale, the results of clinical trials of ICIs in SCLC have yielded modest benefits. A small subset of patients does achieve long-term benefit, but further development of ICIs in SCLC will depend on the identification of predictive biomarkers and the design of combination regimens that take advantage of the molecular alterations that drive the immune-avoidance mechanisms and survival of SCLC cells.