Immunotherapy in treatment naïve advanced non-small cell lung cancer

A novel sub-regional radiomics model to predict immunotherapy response in non-small cell lung carcinoma

BACKGROUND

Identifying precise biomarkers of immunotherapy response for non-small cell lung carcinoma (NSCLC) before treatment is challenging. This study aimed to construct and investigate the potential performance of a sub-regional radiomics model (SRRM) as a novel tumor biomarker in predicting the response of patients with NSCLC treated with immune checkpoint inhibitors, and test whether its predictive performance is superior to that of conventional radiomics, tumor mutational burden (TMB) score and programmed death ligand-1 (PD-L1) expression.

METHODS

We categorized 264 patients from retrospective databases of two centers into training (n = 159) and validation (n = 105) cohorts. Radiomic features were extracted from three sub-regions of the tumor region of interest using the K-means method. We extracted 1,896 features from each sub-region, resulting in 5688 features per sample. The least absolute shrinkage and selection operator regression method was used to select sub-regional radiomic features. The SRRM was constructed and validated using the support vector machine algorithm. We used next-generation sequencing to classify patients from the two cohorts into high TMB (≥ 10 muts/Mb) and low TMB (< 10 muts/Mb) groups; immunohistochemistry was performed to assess PD-L1 expression in formalin-fixed, paraffin-embedded tumor sections, with high expression defined as ≥ 50% of tumor cells being positive. Associations between the SRRM and progression-free survival (PFS) and variant genes were assessed.

RESULTS

Eleven sub-regional radiomic features were employed to develop the SRRM. The areas under the receiver operating characteristic curve (AUCs) of the proposed SRRM were 0.90 (95% confidence interval [CI] 0.84-0.96) and 0.86 (95% CI 0.76-0.95) in the training and validation cohorts, respectively. The SRRM (low vs. high; cutoff value = 0.936) was significantly associated with PFS in the training (hazard ratio [HR] = 0.35 [0.24-0.50], P < 0.001) and validation (HR = 0.42 [0.26-0.67], P = 0.001) cohorts. A significant correlation between the SRRM and three variant genes (H3C4, PAX5, and EGFR) was observed. In the validation cohort, the SRRM demonstrated a higher AUC (0.86, P < 0.001) than that for PD-L1 expression (0.66, P = 0.034) and TMB score (0.54, P = 0.552).

CONCLUSIONS

The SRRM had better predictive performance and was superior to conventional radiomics, PD-L1 expression, and TMB score. The SRRM effectively stratified the progression-free survival (PFS) risk among patients with NSCLC receiving immunotherapy.

A Radiomics-Clinical Model Predicts Overall Survival of Non-Small Cell Lung Cancer Patients Treated with Immunotherapy: A Multicenter Study

BACKGROUND

Immune checkpoint inhibitors (ICIs) are a great breakthrough in cancer treatments and provide improved long-term survival in a subset of non-small cell lung cancer (NSCLC) patients. However, prognostic and predictive biomarkers of immunotherapy still remain an unmet clinical need. In this work, we aim to leverage imaging data and clinical variables to develop survival risk models among advanced NSCLC patients treated with immunotherapy.

METHODS

This retrospective study includes a total of 385 patients from two institutions who were treated with ICIs. Radiomics features extracted from pretreatment CT scans were used to build predictive models. The objectives were to predict overall survival (OS) along with building a classifier for short- and long-term survival groups. We employed the XGBoost learning method to build radiomics and integrated clinical-radiomics predictive models. Feature selection and model building were developed and validated on a multicenter cohort.

RESULTS

We developed parsimonious models that were associated with OS and a classifier for short- and long-term survivor groups. The concordance indices (C-index) of the radiomics model were 0.61 and 0.57 to predict OS in the discovery and validation cohorts, respectively. While the area under the curve (AUC) values of the radiomic models for short- and long-term groups were found to be 0.65 and 0.58 in the discovery and validation cohorts. The accuracy of the combined radiomics-clinical model resulted in 0.63 and 0.62 to predict OS and in 0.77 and 0.62 to classify the survival groups in the discovery and validation cohorts, respectively.

CONCLUSIONS

We developed and validated novel radiomics and integrated radiomics-clinical survival models among NSCLC patients treated with ICIs. This model has important translational implications, which can be used to identify a subset of patients who are not likely to benefit from immunotherapy. The developed imaging biomarkers may allow early prediction of low-group survivors, though additional validation of these radiomics models is warranted.

Patient-reported outcomes with cemiplimab monotherapy for first-line treatment of advanced non-small cell lung cancer with PD-L1 of ≥50%: The EMPOWER-Lung 1 study

BACKGROUND

In the EMPOWER-Lung 1 trial (ClinicalTrials.gov, NCT03088540), cemiplimab conferred longer survival than platinum-doublet chemotherapy for advanced non-small cell lung cancer (NSCLC) with programmed cell death-ligand 1 (PD-L1) ≥50%. Patient-reported outcomes were evaluated among trial participants.

METHODS

Adults with NSCLC and Eastern Cooperative Oncology Group performance status 0 to 1 were randomly assigned cemiplimab 350 mg every 3 weeks or platinum-doublet chemotherapy. At baseline and day 1 of each treatment cycle, patients were administered the European Organization for Research and Treatment of Cancer Quality of Life-Core 30 (QLQ-C30) and Lung Cancer Module (QLQ-LC13) questionnaires. Mixed-model repeated measures analysis estimated overall change from baseline for PD-L1 ≥50% and intention-to-treat populations. Kaplan-Meier analysis estimated time to definitive deterioration.

RESULTS

In PD-L1 ≥50% patients (cemiplimab, n = 283; chemotherapy, n = 280), baseline QLQ-C30 and QLQ-LC13 scores showed moderate-to-high functioning and low symptom burden. Change from baseline favored cemiplimab on global health status/quality of life (GHS/QOL), functioning, and most symptom scales. Risk of definitive deterioration across functioning scales was reduced versus chemotherapy; hazard ratios were 0.48 (95% CI, 0.32-0.71) to 0.63 (95% CI, 0.41-0.96). Cemiplimab showed lower risk of definitive deterioration for disease-related (dyspnea, cough, pain in chest, pain in other body parts, fatigue) and treatment-related symptoms (peripheral neuropathy, alopecia, nausea/vomiting, appetite loss, constipation, diarrhea) (nominal p < .05). Results were similar in the intention-to-treat population.

CONCLUSIONS

Results support cemiplimab for first-line therapy of advanced NSCLC from the patient's perspective. Improved survival is accompanied by improvements versus platinum-doublet chemotherapy in GHS/QOL and functioning and reduction in symptom burden.

Cemiplimab monotherapy for first-line treatment of advanced non-small-cell lung cancer with PD-L1 of at least 50%: a multicentre, open-label, global, phase 3, randomised, controlled trial

BACKGROUND

We aimed to examine cemiplimab, a programmed cell death 1 inhibitor, in the first-line treatment of advanced non-small-cell lung cancer with programmed cell death ligand 1 (PD-L1) of at least 50%.

METHODS

In EMPOWER-Lung 1, a multicentre, open-label, global, phase 3 study, eligible patients recruited in 138 clinics from 24 countries (aged ≥18 years with histologically or cytologically confirmed advanced non-small-cell lung cancer, an Eastern Cooperative Oncology Group performance status of 0-1; never-smokers were ineligible) were randomly assigned (1:1) to cemiplimab 350 mg every 3 weeks or platinum-doublet chemotherapy. Crossover from chemotherapy to cemiplimab was allowed following disease progression. Primary endpoints were overall survival and progression-free survival per masked independent review committee. Primary endpoints were assessed in the intention-to-treat population and in a prespecified PD-L1 of at least 50% population (per US Food and Drug Administration request to the sponsor), which consisted of patients with PD-L1 of at least 50% per 22C3 assay done according to instructions for use. Adverse events were assessed in all patients who received at least one dose of the assigned treatment. This study is registered with ClinicalTrials.gov, NCT03088540 and is ongoing.

FINDINGS

Between June 27, 2017 and Feb 27, 2020, 710 patients were randomly assigned (intention-to-treat population). In the PD-L1 of at least 50% population, which consisted of 563 patients, median overall survival was not reached (95% CI 17·9-not evaluable) with cemiplimab (n=283) versus 14·2 months (11·2-17·5) with chemotherapy (n=280; hazard ratio [HR] 0·57 [0·42-0·77]; p=0·0002). Median progression-free survival was 8·2 months (6·1-8·8) with cemiplimab versus 5·7 months (4·5-6·2) with chemotherapy (HR 0·54 [0·43-0·68]; p<0·0001). Significant improvements in overall survival and progression-free survival were also observed with cemiplimab in the intention-to-treat population despite a high crossover rate (74%). Grade 3-4 treatment-emergent adverse events occurred in 98 (28%) of 355 patients treated with cemiplimab and 135 (39%) of 342 patients treated with chemotherapy.

INTERPRETATION

Cemiplimab monotherapy significantly improved overall survival and progression-free survival compared with chemotherapy in patients with advanced non-small-cell lung cancer with PD-L1 of at least 50%, providing a potential new treatment option for this patient population.

FUNDING

Regeneron Pharmaceuticals and Sanofi.

The value of immunotherapy for survivors of stage IV non-small cell lung cancer: patient perspectives on quality of life

Purpose

The aim of this study was to examine what personally mattered to 24 patients who received immuno-oncology (IO) therapy for stage IV non-small cell lung cancer (NSCLC), as well as their families and friends, to understand how they evaluated their cancer treatments and the determinants of the quality of life (QoL) of long-term survivors.

Methods

Ethnographic research was conducted with 24 patients who had responded to IO (pembrolizumab, nivolumab, atezolizumab, or durvalumab) for stage IV NSCLC, and their families and friends, evenly split among field sites in Denmark, the USA, and the UK. Data were collected using in-depth qualitative interviews, written exercises, and participant observation. Data analysis methods included interpretative phenomenological analysis, coding, and the development of grounded theory. Researchers spent 2 days with participants in their homes and accompanied them on health-related outings.

Results

Our findings reveal that long-term survivors on IO experienced their journey in two phases: one in which their cancer had taken over their lives mentally, physically, and spiritually, and another in which their cancer consumed only a part of their everyday lives. Patients who survived longer than their initial prognosis existed in a limbo state in which they were able to achieve some semblance of normalcy in spite of being identified as having a terminal condition. This limbo state impacted their life priorities, decision-making, experience of patient support, and health information-seeking behaviors, all of which shaped their definitions and experience of QoL.

Conclusions

The results of this study, which identify the specific challenges of living in limbo, where patients are able to reclaim a portion of their pre-cancer lives while continuing to wrestle with a terminal prognosis, may inform how cancer research can more effectively define and measure the QoL impacts of IO treatments. Also, they may identify approaches that the cancer community can use to support the needs of patients living in a limbo state. These experiences may not be adequately understood by the cancer community or captured by existing QoL measures, which were designed prior to the emergence of IO and without sufficient incorporation of contextual, patient-driven experience.

Implications for Cancer Survivors

Increased awareness of the specific experiences that come with long-term survival on IO may direct how resources should be spent for cancer support for patients and their families. Expanding how QoL is evaluated based on patients’ lived experiences of IO can reflect a more accurate depiction of the treatment’s benefits and harms.

Repression of lncRNA-SVUGP2 mediated by EZH2 contributes to the development of non-small cell lung cancer via brisking Wnt/β-catenin signal

To grab the possible impact of lncRNA-SVUGP2 in the biology and process of non-small cell lung cancer (NSCLC). Sixty paired NSCLC tumour and the adjacent non-tumour lung tissues were collected for detection of lncRNA-SVUGP2. lncRNA-SVUGP2 expression in NSCLC cells (SK-MES-1, A549, SPC-A1, and NCI-H1975) was also detected. lncRNA-SVUGP2 was overexpressed and depressed in A549 and H1975 cells, and the effects of lncRNA-SVUGP2 dysregulation on cell biological performances including viability, colony formation, apoptosis, migration and invasion were grabbed. Furthermore, the regulatory association of lncRNA-SVUGP2 vs. EZH2 in H1975 cells, as well as the association between lncRNA-SVUGP2 and Wnt/β-catenin pathway, was explored. lncRNA-SVUGP2 was depressed in NSCLC tissues and cells. Overexpression of lncRNA-SVUGP2 depressed proliferation, induced apoptosis, and suppressed migration and invasion of A549 and H1975 cells. In addition, lncRNA-SVUGP2 was repressed by EZH2 and was inversely correlated with EZH2 levels in H1975 cells. Repression of lncRNA-SVUGP2 potentially participated in the oncogenic function of EZH2. Besides, overexpression of lncRNA-SVUGP2 depressed the briskness of Wnt/β-catenin signal in H1975 cells. Our data reveal that lncRNA-SVUGP2 is under-expressed in NSCLC cells and the reduced expression of lncRNA-SVUGP2 may enhance the development and process of NSCLC by interacting with EZH2 and activating Wnt/β-catenin pathway.

A review of predictive, prognostic and diagnostic biomarkers for non-small-cell lung cancer: towards personalised and targeted cancer therapy

Introduction:

Lung cancer has a high mortality rate mainly due to the lack of early detection or outward signs and symptoms, thereby often progressing to advanced stages (e.g., stage IV) before it is diagnosed. However, if lung cancers can be diagnosed at an early stage and also if clinicians can prospectively identify patients likely to respond to specific treatments, then there is a very high potential to increase patients’ survival. In recent years, several investigations have been conducted to identify cancer biomarkers for lung cancer risk assessment, early detection and diagnosis, the likelihood of identifying the group of patients who will benefit from a particular treatment and monitoring patient response to treatment.

Materials and Methods:

This paper reports on the review of 19 current clinical and emerging biomarkers used in risk assessment, screening for early detection and diagnosis and monitoring the response of treatment of non-small-cell lung cancers.

Conclusion:

The future holds promise for personalised and targeted medicine from prevention, diagnosis to treatment, which take into account individual patient’s variability, though it depends on the development of effective biomarkers interrogating the key aberrant pathways and potentially targetable with molecular targeted or immunologic therapies. Lung cancer biomarkers have the potential to guide clinical decision-making since they can potentially detect the disease early, measure the risk of developing the disease and the risk of progression, provide accurate information of patient response to a specific treatment and are capable of informing clinicians about the likely outcome of a cancer diagnosis independent of the treatment received. Moreover, lung cancer biomarkers are increasingly linked to specific molecular pathway deregulations and/or cancer pathogenesis and can be used to justify the application of certain therapeutic or interventional strategies.

Utilization of the Veterans Affairs Central Cancer Registry to evaluate lung cancer outcomes

Lung cancer is one of the most common and difficult to treat cancers. Veterans are disproportionately affected by lung cancer, as approximately 20% of all cancers diagnosed within the Veteran Affairs health system are lung cancers. Many Veterans have extensive comorbidities, and thus they are often excluded from clinical trials based on this and other eligibility criteria. Thus, while clinical trials are the gold standard to guide treatment decisions, many Veterans' clinical situations will not align with clinical trial criteria. The Department of Veterans Affairs has established a Central Cancer Registry to aid in evaluation of cancer outcomes and other studies, and data in the registry date back to 1995. This has provided a rich source of data for outcome-based and other research. Here, we highlight studies that utilized the Veterans Affairs Central Cancer Registry to analyze lung cancer outcomes in Veterans treated within the Veterans Affairs health system.

Impact of Patient Characteristics, Prior Therapy, and Sample Type on Tumor Cell Programmed Cell Death Ligand 1 Expression in Patients with Advanced NSCLC Screened for the ATLANTIC Study

INTRODUCTION

We evaluated the impact of patient characteristics, sample types, and prior non-immunotherapy treatment on tumor cell (TC) programmed cell death ligand 1 (PD-L1) expression using samples from patients with advanced NSCLC.

METHODS

Patients (N = 1590) screened for the ATLANTIC study submitted a recently acquired (≤3 months) or archival (>3 months to >3 years old) tumor sample for PD-L1 assessment using the VENTANA PD-L1 (SP263) Assay with a cutoff of ≥25% of TCs expressing PD-L1 (TC ≥25%). Samples were acquired either before or after the two or more treatment regimens required for study entry and sample age varied among patients. A subset of patients (n = 123) provided both recent and archival samples.

RESULTS

A total of 517 of 1590 (32.5%) patients had TC greater than or equal to 25%: prevalence was greater in smokers versus nonsmokers (p = 0.0005) and those with EGFR- versus EGFR+ tumors (p = 0.0002); these effects were independent. Prevalence of TC greater than or equal to 25% was increased in recent metastatic versus primary (p = 0.005) and recent versus archival (p = 0.039) samples. Chemotherapy or radiotherapy, but not tyrosine kinase inhibition, before sampling was associated with significantly increased PD-L1 prevalence. PD-L1 status (TC ≥25% cutoff) remained unchanged in 74.0% of patients with recent and archival samples; where PD-L1 status changed, it was more likely to increase than decrease over time or with intervening treatment.

CONCLUSIONS

Several factors potentially impact PD-L1 TC greater than or equal to 25% prevalence in advanced NSCLC; however, no characteristic can be considered a surrogate for PD-L1 expression. Fresh biopsy may provide more accurate assessment of current tumoral PD-L1 expression where a low/negative result is seen in an archival sample, especially if the patient has received intervening therapy.

A reliable and feasible way to predict the benefits of Nivolumab in patients with non-small cell lung cancer: a pooled analysis of 14 retrospective studies

Objective: Nivolumab has been used for treating non-small cell lung cancer (NSCLC) worldwide. Whether neutrophil-lymphocyte ratio (NLR) can predict the prognosis of NSCLC treated with Nivolumab is still under debate. This meta-analysis was to assess the significance of NLR as a predictive factor in NSCLC patients receiving Nivolumab. Methods: Databases including PubMed, Embase, and the Cochrane library were searched to identify eligible studies evaluating the role of NLR in predicting prognosis of NSCLC treated with Nivolumab until March 2018 without language restrictions. The meta-analysis was performed using hazard ratio (HR) of progression free survival (PFS) and overall survival (OS) in NSCLC patients with various NLR. Results: A total of 14 retrospective studies consisting of 1225 NSCLC patients were included. The combined results showed that relatively higher baseline NLR was associated with poor PFS (HR = 1.44; 95% confidence interval (CI):1.18-1.77; p < 0.05) and OS (HR = 1.75; 95% CI: 1.33-2.30; p < 0.05) after treatment of Nivolumab. Subgroup analysis suggested that NLR ≥ 5 was more reliable for PFS (HR = 1.73; 95%CI: 1.14, 2.62; p < 0.05) and OS (HR = 1.76; 95%CI: 1.47, 2.10; p < 0.05). In addition, post-treatment NLR also had predictive roles for PFS (HR = 3.17; 95%CI: 1.48, 6.82; p < 0.05) and OS (HR = 2.26; 95%CI: 1.05, 4.86; p < 0.05). Conclusion: Our findings suggest that NLR can be used as a prognostic biomarker for NSCLC treating with Nivolumab, and the recommended cutoff value of NLR is 5.