An Update on Predictive Biomarkers for Treatment Selection in Non-Small Cell Lung Cancer

Biomarkers in lung cancer treatment

Lung carcinoma (LC) is the primary cause of millions of deaths worldwide. As LC is typically diagnosed at a later stage, its prevention and treatment are difficult. The pathological basis of both types of LC, namely non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC), is highly determined. The only treatments available for LC are surgical resection and chemotherapy, which require sophisticated new treatments. Biomarkers are promising treatment options, because they can be used for both diagnosis and treatment. Typical signaling molecules known as biomarkers identify abnormalities in cellular activity and serve as prognostic and diagnostic indicators. Biomarkers show great promise in clinical decision making, early and quick diagnosis, recurrence of illness, and tracking the effectiveness of cancer treatments. This review provides an overview of biomarkers, their benefits, and future directions for those new to the field of biomarker research in LC therapy.

The prevalence and clinical significance of EGFR mutations in non-small cell lung cancer patients in Egypt: a screening study

BACKGROUND

Lung cancer is a form of cancer that is responsible for the largest incidence of deaths attributed to cancer worldwide. Non-small cell lung cancer (NSCLC) is the most prevalent of all the subtypes of the disease. Treatment with tyrosine kinase inhibitors (TKI) may help some people who have been diagnosed with non-small cell lung cancer. The presence of actionable mutations in the epidermal growth factor receptor (EGFR) gene is a key predictor of how a patient will respond to a TKI. Thus, the frequency of identification of mutations in EGFR gene in patients with NSCLC can facilitate personalized treatment.

OBJECTIVE

The objective of this study was to screen for mutations in the EGFR gene and to investigate whether there is a correlation between the screened mutations and various clinical and pathological factors, such as gender, smoking history, and age, in tissue samples from patients with NSCLC.

METHODS

The study comprised 333 NSCLC tissue samples from 230 males and 103 females with an average age of 50 years. Exons 18-21 of the EGFR gene have been examined using real-time PCR. Using SPSS, correlations between clinical and demographic variables were examined, and EGFR mutation and clinical features associations were studied.

RESULTS

The study's findings revealed that the incidence rate of EGFR mutation was 24.32% (81/333), with partial deletion of exon 19 (19-Del) and a point mutation of L858R in exon 21 accounting for 66.67% (P < 0.001) and 28.40% (P < 0.001) of the mutant cases, respectively. Patients who had the T790M mutation represent 4.94% (P = 0.004) of total number of patients. Females harbored EGFR mutations (54.32%) with higher frequency than men (45.68%) (P < 0.001), while nonsmokers had EGFR mutations (70.37%) more frequently than current smokers (29.63%) (P < 0.001).

CONCLUSION

The screening study conducted in Egypt reported that the EGFR mutations prevalence was 24.32% among Egyptians with NSCLC. The study also found a slight gender bias, with females having an incidence rate of these mutations higher than males. Additionally, nonsmokers had higher rates of mutations in EGFR gene compared to smokers. According to the findings, somatic EGFR mutations can be employed as a diagnostic tool for non-small cell lung cancer in Egypt, and they can be implemented in conjunction with clinical criteria to identify which patients are more likely to respond favorably to TKIs.

Nonparametric Biomarker Based Treatment Selection With Reproducibility Data

We consider evaluating biomarkers for treatment selection under assay modification. Survival outcome, treatment, and Affymetrix gene expression data were attained from cancer patients. Consider migrating a gene expression biomarker to the Illumina platform. A recent novel approach allows a quick evaluation of the migrated biomarker with only a reproducibility study needed to compare the two platforms, achieved by treating the original biomarker as an error-contaminated observation of the migrated biomarker. However, its assumptions of a classical measurement error model and a linear predictor for the outcome may not hold. Ignoring such model deviations may lead to sub-optimal treatment selection or failure to identify effective biomarkers. To overcome such limitations, we adopt a nonparametric logistic regression to model the relationship between the event rate and the biomarker, and the deduced marker-based treatment selection is optimal. We further assume a nonparametric relationship between the migrated and original biomarkers and show that the error-contaminated biomarker leads to sub-optimal treatment selection compared to the error-free biomarker. We obtain the estimation via B-spline approximation. The approach is assessed by simulation studies and demonstrated through application to lung cancer data.

Prognostic Indicators for Precision Treatment of Non-Small Cell Lung Carcinoma

Non-small cell lung cancer (NSCLC) has established predictive biomarkers that enable decisions on treatment regimens for many patients. However, resistance to therapy is widespread. It is therefore essential to have a panel of molecular biomarkers that may help overcome therapy resistance and prevent adverse effects of treatment. We performed in silico analysis of NSCLC prognostic indicators, separately for adenocarcinomas and squamous carcinomas, by using The Cancer Genome Atlas (TCGA) and non-TCGA data sources in cBioPortal as well as UALCAN. This review describes lung cancer biology, elaborating on the key genetic alterations and specific genes responsible for resistance to conventional treatments. Importantly, we examined the mechanisms associated with resistance to immune checkpoint inhibitors. Our analysis indicated that a robust prognostic biomarker was lacking for NSCLC, especially for squamous cell carcinomas. In this work, our screening uncovered previously unidentified prognostic gene expression indicators, namely, MYO1E, FAM83 homologs, and DKK1 for adenocarcinoma, and FGA and TRIB1 for squamous cell carcinoma. It was further observed that overexpression of these genes was associated with poor prognosis. Additionally, FAM83 homolog and TRIB1 unexpectedly harbored copy number amplifications. In conclusion, this study elucidated novel prognostic indicators for NSCLC that may serve as targets to overcome therapy resistance toward improved patient outcomes.

Metastatic non-small-cell lung cancer without driver mutations: projections by therapy line in Western Europe, 2021-2026

Aim: To estimate the incidence, prevalence and treated prevalence by line of therapy (LOT) for non-small-cell lung cancer (NSCLC) patients without driver mutations from 2021 to 2026. Materials & methods: Country-specific registry data for Western Europe were used to project incidence and prevalence of NSCLC; LOT information was obtained from CancerMPact® Treatment Architecture physician surveys. Results: Incidence, prevalence and treated prevalence across LOTs for NSCLC are projected to increase across five WE countries, including for stage IV patients without driver mutations (184,966 cases [2021] to 197,925 [2026]). Pembrolizumab monotherapy is utilized by ∼50% of NSCLC patients with programmed death-ligand 1 expression ≥50%. Conclusion: Improved treatment options for NSCLC patients without known driver mutations are important for combating the projected increase in prevalence.

Establishment of a prognostic risk prediction modelfor non-small cell lung cancer patients with brainmetastases: a retrospective study

Background

Patients with non-small cell lung cancer (NSCLC) who develop brain metastases (BM) have a poor prognosis. This study aimed to construct a clinical prediction model to determine the overall survival (OS) of NSCLC patients with BM.

Methods

A total of 300 NSCLC patients with BM at the Yunnan Cancer Centre were retrospectively analysed. The prediction model was constructed using the least absolute shrinkage and selection operator-Cox regression. The bootstrap sampling method was employed for internal validation. The performance of our prediction model was compared using recursive partitioning analysis (RPA), graded prognostic assessment (GPA), the update of the graded prognostic assessment for lung cancer using molecular markers (Lung-molGPA), the basic score for BM (BSBM), and tumour-lymph node-metastasis (TNM) staging.

Results

The prediction models comprising 15 predictors were constructed. The area under the curve (AUC) values for the 1-year, 3-year, and 5-year time-dependent receiver operating characteristic (curves) were 0.746 (0.678-0.814), 0.819 (0.761-0.877), and 0.865 (0.774-0.957), respectively. The bootstrap-corrected AUC values and Brier scores for the prediction model were 0.811 (0.638-0.950) and 0.123 (0.066-0.188), respectively. The time-dependent C-index indicated that our model exhibited significantly greater discrimination compared with RPA, GPA, Lung-molGPA, BSBM, and TNM staging. Similarly, the decision curve analysis demonstrated that our model displayed the widest range of thresholds and yielded the highest net benefit. Furthermore, the net reclassification improvement and integrated discrimination improvement analyses confirmed the enhanced predictive power of our prediction model. Finally, the risk subgroups identified by our prognostic model exhibited superior differentiation of patients' OS.

Conclusion

The clinical prediction model constructed by us shows promise in predicting OS for NSCLC patients with BM. Its predictability is superior compared with RPA, GPA, Lung-molGPA, BSBM, and TNM staging.

Protein Tyrosine Phosphatase Non-Receptor 11 (PTPN11/Shp2) as a Driver Oncogene and a Novel Therapeutic Target in Non-Small Cell Lung Cancer (NSCLC)

PTPN11 encodes the SHP2 protein tyrosine phosphatase that activates the mitogen-activated protein kinase (MAPK) pathway upstream of KRAS and MEK. PTPN11/Shp2 somatic mutations occur frequently in Juvenile myelomonocytic leukaemia (JMML); however, the role of mutated PTPN11 in lung cancer tumourigenesis and its utility as a therapeutic target has not been fully addressed. We applied mass-spectrometry-based genotyping to DNA extracted from the tumour and matched the normal tissue of 356 NSCLC patients (98 adenocarcinomas (LUAD) and 258 squamous cell carcinomas (LUSC)). Further, PTPN11 mutation cases were identified in additional cohorts, including TCGA, Broad, and MD Anderson datasets and the COSMIC database. PTPN11 constructs harbouring PTPN11 E76A, A72D and C459S mutations were stably expressed in IL-3 dependent BaF3 cells and NSCLC cell lines (NCI-H1703, NCI-H157, NCI-H1299). The MAPK and PI3K pathway activation was evaluated using Western blotting. PTPN11/Shp2 phosphatase activity was measured in whole-cell protein lysates using an Shp2 assay kit. The Shp2 inhibitor (SHPi) was assessed both in vitro and in vivo in a PTPN11-mutated cell line for improved responses to MAPK and PI3K targeting therapies. Somatic PTPN11 hotspot mutations occurred in 4/98 (4.1%) adenocarcinomas and 7/258 (2.7%) squamous cells of 356 NSCLC patients. Additional 26 PTPN11 hotspot mutations occurred in 23 and 3 adenocarcinomas and squamous cell carcinoma, respectively, across the additional cohorts. Mutant PTPN11 significantly increased the IL-3 independent survival of Ba/F3 cells compared to wildtype PTPN11 (p < 0.0001). Ba/F3, NCI-H1703, and NCI-H157 cells expressing mutant PTPN11 exhibited increased PTPN11/Shp2 phosphatase activity and phospho-ERK1/2 levels compared to cells expressing wildtype PTPN11. The transduction of the PTPN11 inactivating mutation C459S into NSCLC cell lines led to decreased phospho-ERK, as well as decreased phospho-AKT in the PTPN11-mutated NCI-H661 cell line. NCI-H661 cells (PTPN11-mutated, KRAS-wild type) were significantly more sensitive to growth inhibition by the PI3K inhibitor copanlisib (IC50: 13.9 ± 4.7 nM) compared to NCI-H1703 (PTPN11/KRAS-wild type) cells (IC50: >10,000 nM). The SHP2 inhibitor, in combination with the PI3K targeting therapy copanlisib, showed no significant difference in tumour development in vivo; however, this significantly prevented MAPK pathway induction in vitro (p < 0.0001). PTPN11/Shp2 demonstrated the in vitro features of a driver oncogene and could potentially sensitize NSCLC cells to PI3K inhibition and inhibit MAPK pathway activation following PI3K pathway targeting.

Replication of Real-World Evidence in Oncology Using Electronic Health Record Data Extracted by Machine Learning

Meaningful real-world evidence (RWE) generation requires unstructured data found in electronic health records (EHRs) which are often missing from administrative claims; however, obtaining relevant data from unstructured EHR sources is resource-intensive. In response, researchers are using natural language processing (NLP) with machine learning (ML) techniques (i.e., ML extraction) to extract real-world data (RWD) at scale. This study assessed the quality and fitness-for-use of EHR-derived oncology data curated using NLP with ML as compared to the reference standard of expert abstraction. Using a sample of 186,313 patients with lung cancer from a nationwide EHR-derived de-identified database, we performed a series of replication analyses demonstrating some common analyses conducted in retrospective observational research with complex EHR-derived data to generate evidence. Eligible patients were selected into biomarker- and treatment-defined cohorts, first with expert-abstracted then with ML-extracted data. We utilized the biomarker- and treatment-defined cohorts to perform analyses related to biomarker-associated survival and treatment comparative effectiveness, respectively. Across all analyses, the results differed by less than 8% between the data curation methods, and similar conclusions were reached. These results highlight that high-performance ML-extracted variables trained on expert-abstracted data can achieve similar results as when using abstracted data, unlocking the ability to perform oncology research at scale.

Interim analysis of the efficiency and safety of neoadjuvant PD-1 inhibitor (sintilimab) combined with chemotherapy (nab-paclitaxel and carboplatin) in potentially resectable stage IIIA/IIIB non-small cell lung cancer: a single-arm, phase 2 trial

INTRODUCTION

While some clinical studies have shown that PD-1 and PD-L1 can also be an effective neoadjuvant treatment for early-stage non-small cell lung cancer (NSCLC), no evidence has been available for the use of the PD-1 inhibitor sintilimab combined with chemotherapy as a neoadjuvant treatment for potentially resectable NSCLC in the Chinese population.

METHODS

This prospective, single-center, single-arm, phase 2 clinical trial (registration number: NCT04326153) included treatment-naive patients with potentially resectable NSCLC (stage IIIA/IIIB) who received sintilimab plus nab-paclitaxel and carboplatin for two to three cycles before systematic nodal dissection 30 to 45 days after neoadjuvant treatment. After surgery, patients needed to complete two cycles of adjuvant chemoimmunotherapy (sintilimab + nab-paclitaxel + carboplatin). The primary endpoint was disease-free survival rate at 24 months, whereas secondary endpoints included major pathological response (MPR) and pathologic complete response (pCR) rates, the proportion of patients who achieved tumor downstaging, overall survival, objective response rate (ORR), and adverse effects. PD-L1 status before and after treatment was also determined.

RESULTS

Among the 20 patients who received neoadjuvant chemoimmunotherapy, 16 underwent radical resection. The disease control rate and ORR were 90% and 70%, respectively. Among the 16 patients who underwent surgery, 10 (62.5%) and 5 (31.25%) achieved MPR and pCR, respectively. Squamous cell NSCLC exhibited superior response rates compared to adenocarcinoma (pCR 35.7% vs. 0%). Moreover, 14 patients (70%) experienced grade 1 or 2 neoadjuvant treatment-related adverse events (TRAEs), whereas 6 (30%) experienced grade 3 TRAEs. Bronchopleural fistula (BPF) was found in the current study as an adverse reaction of concern. The rate of BPF was 20% (4/20), of which three patients were in grade 1-2, and one patient died. The occurrence of BPF had no significant correlation with basic disease history, nutritional status, anemia, hypoalbuminemia, surgical procedure, pathological remission, and PD-L1 expression. However, during neoadjuvant treatment, no adverse events prompted dose reduction, treatment discontinuation, surgery delay, or death. Although PD-L1 expression may change after chemoimmunotherapy, no regular pattern was noted. PD-L1 expression, neither at baseline nor after neoadjuvant chemoimmunotherapy, was associated with pathological remission.

CONCLUSIONS

The current study found similar ORR, slightly lower MPR and pCR rates, and lower grade 3 TRAEs among patients with potentially resectable stage IIIA/IIIB NSCLC compared to the NADIM trial, as well as a greater ORR, MPR rate, pCR rate, and grade 3 TRAEs compared to Gao's study involving sintilimab for Chinese patients with resectable stage IA-IIIB NSCLC. Though neoadjuvant chemoimmunotherapy had been found to promote a high risk of BPF for patients with stage IIIA/IIIB disease, it offered greater potential for radical cure. Therefore, the current study suggests that neoadjuvant chemoimmunotherapy can be a safe approach in increasing the efficiency of treatment and hopefully improving the prognosis of patients with potentially resectable locally advanced NSCLC.

Optimal diagnostic strategies for pleural diseases and identifying high-risk patients

INTRODUCTION

Pleural diseases encompass a broad range of conditions with diverse and heterogenous etiologies. Diagnostics in pleural diseases thus represents a challenging field with a wide array of available testing to distinguish between the numerous causes of pleural disease. Nonetheless, deploying best practice diagnostics in this area is essential in reducing both duration o the investigation pathway and symptom burden.

AREAS COVERED

This article critically appraises the optimal diagnostic strategies and pathway in patients with pleural disease, reviewing the latest evidence and key practice points in achieving a treatable diagnosis in patients with pleural disease. We also cover future and novel directions that are likely to influence pleural diagnostics in the near future. PubMed was searched for articles related to pleural diagnostics (search terms below), with the date ranges including June 2012 to June 2022.

EXPERT OPINION

No single test will ever be sufficient to provide a diagnosis in pleural conditions. The key to reducing procedure burden and duration to diagnosis lies in personalizing the investigation pathway to patients and deploying tests with the highest diagnostic yield early (such as pleural biopsy in infection and malignancy). Novel biomarkers may also allow earlier diagnostic precision in the near future.

A study of non small cell lung cancer (NSCLC) patients with brain metastasis: A single centre experience

BACKGROUND

Lung cancer is the leading cause of cancer death with the majority of cases being non-small cell lung cancer (NSCLC) [1]. A common complication of NSCLC is brain metastasis (BM) [2, 3], where the prognosis remains poor despite new treatments. Real world data complements data gained from clinical trials, providing information on patients excluded from prospective research [4]. However, information from patient notes may prove incomplete and difficult to extract. We developed an algorithm to identify patients in our clinical database with brain metastasis from the electronic health record (EHR).

METHODS

We retrospectively extracted data from the EHR of patients managed at a large teaching hospital between 2007 and 2018. Using the ICD-10 code C34, for lung cancer, our algorithm used phrases associated with BMs to search the unstructured text of radiology reports. Summary statistics and univariant analysis was performed for overall survival.

RESULTS

818 patients were identified as potentially having BM and 453 patients were confirmed on clinical review of their records. The median age of patients was 69 years, 50% were female and 66% had a performance status of >2. 12.2% had an identifiable mutation and 11.5% were identified as PD-L1 positive. In the first line setting, 65% of patients received symptomatic treatment, 23% received systemic anticancer therapy (SACT), 6.1% surgery and 10% radiotherapy, of which 6.5% had external beam and 3.5% stereotactic radiosurgery. Regarding those treated with SACT, 35% had an intracranial response to treatment (3% had complete response, 32% had a partial response). Median survival was 2 months (1.9 - 2.4 months 95% CI).

CONCLUSION

The real-world prognosis for NSCLC patients with BMs is poor. By using an algorithm, we have reported outcomes on a comprehensive cohort of patients which helps identify those for whom an active treatment approach is appropriate.

Novel Radiomic Measurements of Tumor-Associated Vasculature Morphology on Clinical Imaging as a Biomarker of Treatment Response in Multiple Cancers

PURPOSE

The tumor-associated vasculature (TAV) differs from healthy blood vessels by its convolutedness, leakiness, and chaotic architecture, and these attributes facilitate the creation of a treatment-resistant tumor microenvironment. Measurable differences in these attributes might also help stratify patients by likely benefit of systemic therapy (e.g., chemotherapy). In this work, we present a new category of computational image-based biomarkers called quantitative tumor-associated vasculature (QuanTAV) features, and demonstrate their ability to predict response and survival across multiple cancer types, imaging modalities, and treatment regimens involving chemotherapy.

EXPERIMENTAL DESIGN

We isolated tumor vasculature and extracted mathematical measurements of twistedness and organization from routine pretreatment radiology (CT or contrast-enhanced MRI) of a total of 558 patients, who received one of four first-line chemotherapy-based therapeutic intervention strategies for breast (n = 371) or non-small cell lung cancer (NSCLC, n = 187).

RESULTS

Across four chemotherapy-based treatment strategies, classifiers of QuanTAV measurements significantly (P < 0.05) predicted response in held out testing cohorts alone (AUC = 0.63-0.71) and increased AUC by 0.06-0.12 when added to models of significant clinical variables alone. Similarly, we derived QuanTAV risk scores that were prognostic of recurrence-free survival in treatment cohorts who received surgery following chemotherapy for breast cancer [P = 0.0022; HR = 1.25; 95% confidence interval (CI), 1.08-1.44; concordance index (C-index) = 0.66] and chemoradiation for NSCLC (P = 0.039; HR = 1.28; 95% CI, 1.01-1.62; C-index = 0.66). From vessel-based risk scores, we further derived categorical QuanTAV high/low risk groups that were independently prognostic among all treatment groups, including patients with NSCLC who received chemotherapy only (P = 0.034; HR = 2.29; 95% CI, 1.07-4.94; C-index = 0.62). QuanTAV response and risk scores were independent of clinicopathologic risk factors and matched or exceeded models of clinical variables including posttreatment response.

CONCLUSIONS

Across these domains, we observed an association of vascular morphology on CT and MRI-as captured by metrics of vessel curvature, torsion, and organizational heterogeneity-and treatment outcome. Our findings suggest the potential of shape and structure of the TAV in developing prognostic and predictive biomarkers for multiple cancers and different treatment strategies.

Natural Products in Preventing Tumor Drug Resistance and Related Signaling Pathways

Drug resistance is still an obstacle in cancer therapy, leading to the failure of tumor treatment. The emergence of tumor drug resistance has always been a main concern of oncologists. Therefore, overcoming tumor drug resistance and looking for new strategies for tumor treatment is a major focus in the field of tumor research. Natural products serve as effective substances against drug resistance because of their diverse chemical structures and pharmacological effects. We reviewed the signaling pathways involved in the development of tumor drug resistance, including Epidermal growth factor receptor (EGFR), Renin-angiotensin system (Ras), Phosphatidylinositol-3-kinase/protein kinase B (PI3K/Akt), Wnt, Notch, Transforming growth factor-beta (TGF-β), and their specific signaling pathway inhibitors derived from natural products. This can provide new ideas for the prevention of drug resistance in cancer therapy.

Efficacy and safety of first-line therapies in EGFR-mutated advanced non-small-cell lung cancer: a network meta-analysis

Aim: To evaluate the comparative efficacy and safety of identified first-line therapies for patients with EGFR mutation-positive (EGFRm+) advanced non-small-cell lung cancer (NSCLC), with a focus on ramucirumab + erlotinib. Methods: In the absence of head-to-head studies, a Bayesian network meta-analysis was conducted using randomized clinical trial data to evaluate first-line systemic therapies with erlotinib/gefitinib as the reference treatment. Results: For progression-free survival, ramucirumab + erlotinib was comparable to osimertinib and dacomitinib in the primary analysis. Conclusion: The analysis showed ramucirumab + erlotinib efficacy to be comparable to best-in-class treatment options for previously untreated patients with EGFRm+ advanced NSCLC. Registration information: PROSPERO ID: CRD42020136247.

Small molecule based EGFR targeting of biodegradable nanoparticles containing temozolomide and Cy5 dye for greatly enhanced image-guided glioblastoma therapy

Current glioblastoma multiforme (GBM) treatment is insufficient, facing obstacles like poor tumor accumulation and dose limiting side effects of chemotherapeutic agents. Targeted nanomaterials offer breakthrough potential in GBM treatment; however, traditional antibody-based targeting poses challenges for live brain application. To overcome current obstacles, we introduce here the development of a small molecule targeting agent, CFMQ, coupled to biocompatible chitosan coated poly(lactic-co-glycolic) acid nanoparticles. These targeted nanoparticles enhance cellular uptake and show rapid blood-brain barrier (BBB) permeability in-vitro, demonstrating the ability to effectively deliver their load to tumor cells. Encapsulation of the chemotherapeutic agent, temozolomide (TMZ), decreases the IC₅₀ ~34-fold compared to free-drug. Also, CFMQ synergistically suppresses tumor cell progression, reducing colony formation (98%), cell migration (84%), and cell invasion (77%). Co-encapsulation of Cy5 enables optical image guided therapy. This biocompatible theranostic nanoformulation shows early promise in significantly enhancing the efficacy of TMZ, while providing potential for image-guided therapy for GBM.

Characterization With KRAS Mutant Is a Critical Determinant in Immunotherapy and Other Multiple Therapies for Non-Small Cell Lung Cancer

Non-small cell lung cancer (NSCLC) is a frequent type of cancer, which is mainly characterized clinically by high aggressiveness and high mortality. KRAS oncoprotein is the most common molecular protein detected in NSCLC, accounting for 25% of all oncogenic mutations. Constitutive activation of the KRAS oncoprotein triggers an intracellular cascade in cancer cells, leading to uncontrolled cell proliferation of cancer cells and aberrant cell survival states. The results of multiple clinical trials have shown that different KRAS mutation subtypes exhibit different sensitivities to different chemotherapy regimens. Meanwhile, anti-angiogenic drugs have shown differential efficacy for different subtypes of KRAS mutated lung cancer. It was explored to find if the specificity of the KRAS mutation subtype would affect PD-L1 expression, so immunotherapy would be of potential clinical value for the treatment of some types of KRAS mutations. It was discovered that the specificity of the KRAS mutation affected PD-L1, which opened up immunotherapy as a potential clinical treatment option. After several breakthrough studies, the preliminary test data of many early clinical trials showed that it is possible to directly inhibit KRAS G12C mutation, which has been proved to be a targeted treatment that is suitable for about 10%-12% of patients with advanced NSCLC, having a significant impact on the prolongation of their survival and the improvement of their quality of life. This article reviews the latest progress of treatments for NSCLC with KRAS mutation, in order to gain insight into the biological diversity of lung cancer cells and their potential clinical implications, thereby enabling individualized treatment for patients with KRAS-mutant NSCLC.

Malignant pleural effusion: Updates in diagnosis, management and current challenges

Malignant pleural effusion (MPE) is a common condition which often causes significant symptoms to patients and costs to healthcare systems. Over the past decade, the management of MPE has progressed enormously with large scale, randomised trials answering key questions regarding optimal diagnostic strategies and effective management strategies. Despite a number of management options, including talc pleurodesis, indwelling pleural catheters and combinations of the two, treatment for MPE remains symptom directed and centered around drainage strategy. The future goals for providing improved care for patients lies in changing the treatment paradigm from a generic pathway to personalised care, based on probability of malignancy type and survival. This article reviews the current evidence base, new discoveries and future directions in the diagnosis and management of MPE.

Factors associated with immunotherapy respond and survival in advanced non-small cell lung cancer patients

OBJECTIVES

This study aimed to explore factors associated with immunotherapy respond and survival in advanced non-small cell lung cancer (aNSCLC) patients treated with immune checkpoint inhibitors (ICIs).

METHODS

A total of 101 patients with aNSCLC receiving ICIs were included. The association between clinical factors and multiple endpoints including objective response rate (ORR), disease control rate (DCR), overall survival (OS) and progression-free survival (PFS) were investigated by multivariate analyses.

RESULTS

Multivariate logistic analyses revealed that clinical stage, lactate dehydrogena (LDH), and any grade immune-related adverse events (irAEs) were independent predictors of ORR, while LDH and ICIs treatment type were independent predictors of DCR. In Multivariate Cox analysis, Eastern Cooperative Oncology Group performance status (ECOG PS), LDH, albumin (Alb), platelet to lymphocyte ratio (PLR), and any grade irAEs were independent factors for OS. Similarly, clinical stage, LDH, Alb, and any grade irAEs were independent factors for PFS. Pre-treatment prognostic score was established based on clinical stage, ECOG PS, LDH, Alb and PLR to classify patients into three groups: the good group (0-1 score), the intermediate group (2 scores) and the poor group (3-4 scores). The immunotherapy response was significantly different in various prognostic groups. Subset analyses showed pre-treatment prognostic score ≥ 3 tended to have a strong negative impact on survival among patients with programmed cell death-ligand 1 (PD-L1) expression ≥ 50%.

CONCLUSIONS

Pre-treatment prognostic score based on clinical stage, ECOG PS, LDH, Alb and PLR may help to identify aNSCLC patients who may benefit from ICIs.

High-resolution computed tomography findings independently predict epidermal growth factor receptor mutation status in ground-glass nodular lung adenocarcinoma

BACKGROUND

For lung adenocarcinoma with epidermal growth factor receptor (EGFR) gene mutation, small molecule tyrosine kinase inhibitors are more effective. Some patients could not obtain enough histological specimens for EGFR gene mutation detection. Specific imaging features can predict EGFR mutation status to a certain extent.

AIM

To assess the associations of EGFR mutations with high-resolution computerized tomography (HRCT) features in ground-glass nodular lung adenocarcinoma.

METHODS

This study retrospectively assessed patients with ground-glass nodular lung adenocarcinoma diagnosed between January 2011 and March 2017. EGFR gene mutations in exons 18-21 were detected. The patients were classified into mutant EGFR and wild-type groups, and general data and HRCT image characteristics were assessed.

RESULTS

Among 98 patients, 31 (31.6%) and 67 (68.4%) had mutated and wild-type EGFR in exons 18-21, respectively. Gender, age, smoking history, location of lesions, morphology, edges, borders, pleural indentations, and associations of nodules with bronchus and blood vessels were comparable in both groups (all P > 0.05). Patients with mutant EGFR had larger nodules than those with the wild-type (17.19 ± 6.79 and 14.37 ± 6.30 mm, respectively; P = 0.047). Meanwhile, the vacuole/honeycomb sign was more frequent in the mutant EGFR group (P = 0.011). The logistic regression prediction model included the combination of nodule size and vacuole/honeycomb sign (OR = 1.120, 95%CI: 1.023-1.227, P = 0.014) revealed a sensitivity of 83.9%, a specificity of 52.2% and an AUC of 0.698 (95%CI: 0.589-0.806; P = 0.002).

CONCLUSION

Nodule size and vacuole/honeycomb features could independently predict EGFR mutation status in ground-glass nodular lung adenocarcinoma.

Diagnostic, Predictive, and Prognostic Biomarkers in Non-Small Cell Lung Cancer (NSCLC) Management

Lung cancer is the leading cause of cancer-related deaths worldwide. Despite growing efforts for its early detection by screening populations at risk, the majority of lung cancer patients are still diagnosed in an advanced stage. The management of lung cancer has dramatically improved in the last decade and is no longer based on the "one-fits-all" paradigm or the general histological classification of non-small cell versus small cell lung cancer. Emerging options of targeted therapies and immunotherapies have shifted the management of lung cancer to a more personalized treatment approach, significantly influencing the clinical course and outcome of the disease. Molecular biomarkers have emerged as valuable tools in the prognosis and prediction of therapy response. In this review, we discuss the relevant biomarkers used in the clinical management of lung tumors, from diagnosis to prognosis. We also discuss promising new biomarkers, focusing on non-small cell lung cancer as the most abundant type of lung cancer.

One-Step Polymerase Chain Reaction-Free Nanowire-Based Plasma Cell-Free DNA Assay to Detect EML4-ALK Fusion and to Monitor Resistance in Lung Cancer

BACKGROUND

Next-generation sequencing has mostly been used for genotyping cell-free DNA (cfDNA) in plasma. However, this assay has several clinical limitations. We evaluated the clinical utility of a novel polymerase chain reaction-free nanowire (NW)-based plasma cfDNA assay for detecting ALK fusion and mutations.

PATIENTS, MATERIALS, AND METHODS

We consecutively enrolled 99 patients with advanced non-small cell lung cancer undergoing a fluorescence in situ hybridization (FISH) test for ALK fusion; ALK-positive (n = 36). The NW-based assay was performed using 50-100 μL of plasma collected at pretreatment and every 8 weeks during ALK inhibitor treatment.

RESULTS

There was high concordance between the NW-based assay and the FISH test for identification of ALK fusion (94.9% with a kappa coefficient value of 0.892, 95% confidence interval [CI], 0.799-0.984). There was no difference in the response rate to the first anaplastic lymphoma kinase inhibitor between the ALK-positive patients identified by the NW-based assay and by the FISH test (73.5% vs. 72.2%, p = .931). In the ALK variant analysis, variants 1 and 3 subgroups were detected in 27 (75.0%) and 8 (22.2%) patients, respectively. Among 24 patients treated with crizotinib, variant 3 subgroup was associated with worse median overall survival than variant 1 subgroup (36.5 months; 95% CI, 0.09-87.6 vs. 19.8 months; 95% CI, 9.9-not reached, p = .004]. A serial assessment identified that ALK L1196M resistance mutation emerged before radiologic progression during crizotinib treatment.

CONCLUSION

The newly developed simple NW-based cfDNA assay may be clinically applicable for rapid diagnosis of ALK fusion with its variant forms and early detection of resistance.

IMPLICATIONS FOR PRACTICE

The authors developed a novel one-step polymerase chain reaction-free nanowire (NW)-based plasma cell-free DNA (cfDNA) assay. This study evaluated the clinical utility of this novel method for the diagnosis of EML4-ALK fusion in advanced non-small cell lung cancer (NSCLC). The NW-based assay and FISH test showed high concordance rate in 99 patients with advanced NSCLC. Serial cfDNA assessment demonstrated this method provided early detection of resistance before radiologic progression during crizotinib treatment. Taken together, plasma cfDNA genotyping by the NW-based cfDNA assay may be useful for the rapid diagnosis of ALK fusion, classifying variants, and early detection of resistance.

Treatment patterns and survival outcomes for patients with non-small cell lung cancer in the UK in the preimmunology era: a REAL-Oncology database analysis from the I-O Optimise initiative

OBJECTIVES

To report characteristics, treatment and overall survival (OS) trends, by stage and pathology, of patients diagnosed with non-small cell lung cancer (NSCLC) at Leeds Teaching Hospital NHS Trust in 2007-2018.

DESIGN

Retrospective cohort study based on electronic medical records.

SETTING

Large NHS university hospital in Leeds.

PARTICIPANTS

3739 adult patients diagnosed with incident NSCLC from January 2007 to August 2017, followed up until March 2018.

MAIN OUTCOME MEASURES

Patient characteristics at diagnosis, treatment patterns and OS.

RESULTS

34.3% of patients with NSCLC were clinically diagnosed (without pathological confirmation). Among patients with known pathology, 45.2% had non-squamous cell carcinoma (NSQ) and 33.3% had squamous cell carcinoma (SQ). The proportion of patients diagnosed at stage I increased (16.4%-27.7% in 2010-2017); those diagnosed at stage IV decreased (57.0%-39.1%). Surgery was the most common initial treatment for patients with pathologically confirmed stage I NSCLC. Use of radiotherapy alone increased over time in patients with clinically diagnosed stage I NSCLC (39.1%-60.3%); chemoradiation increased in patients with stage IIIA NSQ (21.6%-33.3%) and SQ (24.2%-31.9%). Initial treatment with systemic anticancer therapy (SACT) increased in patients with stages IIIB-IV NSQ (49.0%-67.5%); the proportion of untreated patients decreased (30.6%-15.0%). Median OS improved for patients diagnosed with stage I NSQ and SQ and stage IIIA NSQ over time. Median OS for patients with stages IIIB-IV NSQ and SQ remained stable, <10% patients were alive 3 years after diagnosis. Median OS for clinically diagnosed stages IIIB-IV patients was 1.2 months in both periods.

CONCLUSIONS

OS for stage I and IIIA patients improved over time, likely due to increased use of stereotactic ablative radiation, surgery (stage I) and chemoradiation (stage IIIA). Conversely, OS outcomes remained poor for stage IIIB-IV patients despite increasing use of SACT for NSQ. Many patients with advanced-stage disease remained untreated.

Status quo of ALK testing in lung cancer: results of an EQA scheme based on in-situ hybridization, immunohistochemistry, and RNA/DNA sequencing

With this external quality assessment (EQA) scheme, we aim to investigate the diagnostic performance of the currently available methods for the detection of ALK alterations in non-small cell lung cancer on a national scale, namely, in situ hybridization (ISH), immunohistochemistry (IHC), and RNA/DNA sequencing (NGS). The EQA scheme cohort consisted of ten specimens, including four ALK positive and six ALK negative samples, which were thoroughly pretested using IHC, ISH, and RNA/DNA NGS. Unstained tumor sections were provided to the 57 participants, and the results were retrieved via an online questionnaire. ISH was used by 29, IHC by 38, and RNA/DNA sequencing by 19 participants. Twenty-eight institutions (97%) passed the ring trial using ISH, 33 (87%) by using IHC, and 18 (95%) by using NGS. The highest sensitivity and interrater agreement (Fleiss ‘ kappa) was observed for RNA/DNA sequencing (99%, 0.975), followed by ISH (94%, 0.898) and IHC (92%, 0.888). However, the proportion of samples that were not evaluable due to bad tissue quality was also higher for RNA/DNA sequencing (4%) compared with ISH (0.7%) and IHC (0.5%). While all three methods produced reliable results between the different institutions, the highest sensitivity and concordance were observed for RNA/DNA sequencing. These findings encourage the broad implementation of this method in routine diagnostic, although the application might be limited by technical capacity, economical restrictions, and tissue quality of formalin-fixed samples.

Radiation and Modulation of the Tumor Immune Microenvironment in Non-Small Cell Lung Cancer

Immune checkpoint inhibitors are approved for a variety of indications for locally advanced and metastatic non-small cell lung cancer (NSCLC), and trials are ongoing in the early-stage setting. There is an unmet need to understand which patients may derive benefit from immunotherapies and how to harness combined modality therapies to improve overall response rates and durability. Here, we review studies from the bench-to-bedside to examine the role of radiation therapy (RT) on the tumor immune microenvironment in NSCLC with an eye toward augmenting antitumor immunity. Together, these data provide a foundation for developing future clinical trials harnessing RT to augment antitumor immunity and highlight the need for correlative translational studies to directly characterize the impact of RT on the human NSCLC tumor immune microenvironment.

Generation of osimertinib-resistant cells from epidermal growth factor receptor L858R/T790M mutant non-small cell lung carcinoma cell line

BACKGROUND

Lung cancer contributes to high cancer mortality worldwide with 80% of total cases diagnosed as non-small cell lung cancer (NSCLC). Epidermal growth factor receptor (EGFR) tyrosine kinase (TK) domain serves as a druggable target in NSCLC patients with exon 19 deletion and L858R mutation. However, patients eventually succumbed to resistance to first- and second-generation EGFR-TK inhibitors through activation of T790M mutation. Third-generation EGFR-TKI, Osimertinib exhibits high efficacy in patients with exon 19 deletion/L858R/T790M mutation but they experienced acquired resistance thereafter. Available treatment options in NSCLC patients remains a challenge due to unknown molecular heterogeneity responsible for acquired resistance to EGFR-TKI. In this study, we aim to generate Osimertinib-resistant (OR) cells from H1975 carrying L858R/T790M double mutation which can be used as a model to elucidate mechanism of resistance.

METHODS

OR cells were established via stepwise-dose escalation and limiting single-cell dilution method. We then evaluated Osimertinib resistance potential via cell viability assay. Proteins expression related to EGFR-signalling, epithelial to mesenchymal transition (EMT), and autophagy were analyzed via western blot.

RESULTS

OR cell lines exhibited increased drug resistance potential compared to H1975. Distinguishable mesenchymal-like features were observed in OR cells. Protein expression analysis revealed EGFR-independent signaling involved in the derived OR cells as well as EMT and autophagy activity.

CONCLUSION

We generated OR cell lines in-vitro as evidenced by increased drug resistance potential, increased mesenchymal features, and enhanced autophagy activity. Development of Osimertinib resistance cells may serve as in-vitro model facilitating discovery of molecular aberration present during acquired mechanism of resistance.

Immune checkpoint blockade in the treatment of advanced non-small cell lung cancer - predictors of response and impact of previous radiotherapy

BACKGROUND

The implementation of immune checkpoint inhibitors (ICI) into the standard care of advanced non-small cell lung cancer (NSCLC) has improved prognosis for this group of patients. However, long-term survival is rare. The aim of the study was to identify predictors of response and, especially, to investigate the impact radiotherapy might have on duration of response.

MATERIAL AND METHODS

The association between pretreatment patient/tumor characteristics and progression-free survival (PFS), overall survival (OS), and lung cancer-specific survival was investigated in 78 patients receiving an ICI as ≥2nd line treatment for advanced NSCLC, using Cox regression analysis. Due to competing risk, cause-specific deaths were also examined with cumulative incidence plots.

RESULTS

Median OS was 12.6 months (95% CI 7.8-18.2) and median PFS 4.1 months (95% CI 3.0-6.2), after median follow-up time of 49.7 months (range 20.9-51.5). Increasing CRP and neutrophil/lymphocyte ratio (NLR), were associated with poor PFS (CRP: HR 1.49, 95% CI 1.12-1.98; NLR: HR 1.59, 95% CI 1.22-1.85) and OS (CRP: HR 1.94, 95% CI 1.47-2.56; NLR: HR 1.54, 95% CI 1.27-1.87). Radiotherapy prior to immunotherapy was not significantly associated with patient outcome. However, when the dataset was split at 6 months of follow-up, to be able to identify early and late predictors of prognosis, we found that patients receiving radiotherapy <6 months prior to immunotherapy had better PFS (HR: 0.27, 95% CI 0.09-0.84) and lung cancer-specific survival (HR: 0.41, 95% CI 0.18-0.95) after the first 6 months of follow-up, while increasing CRP (PFS: HR1.61, 95% CI 1.21-2.14; OS: HR2.04, 95% CI 1.51-2.74) and NLR (PFS: HR 1.57, 95% CI 1.29-1.91; OS: HR 1.63, 95% CI 1.35-1.97) were predictors of poor short-term prognosis.

CONCLUSIONS

Radiotherapy may be of importance to achieve a long-lasting response to immunotherapy, while indicators of systemic inflammation can help in identifying patients with poor short-term prognosis.

Identification of theranostic factors for patients developing metastasis after surgery for early-stage lung adenocarcinoma

Rationale: Lung adenocarcinoma (LUAD) is an aggressive disease with high propensity of metastasis. Among patients with early-stage disease, more than 30% of them may relapse or develop metastasis. There is an unmet medical need to stratify patients with early-stage LUAD according to their risk of relapse/metastasis to guide preventive or therapeutic approaches. In this study, we identified 4 genes that can serve both therapeutic and diagnostic (theranostic) purposes.

Methods: Three independent datasets (GEO, TCGA, and KMPlotter) were used to evaluate gene expression profile of patients with LUAD by unbiased screening approach. Upon significant genes uncovered, functional enrichment analysis was carried out. The predictive power of their expression on patient prognosis were evaluated. Once confirmed their theranostic roles by integrated bioinformatics, we further conducted in vitro and in vivo validation.

Results: We found that four genes (ADAM9, MTHFD2, RRM2, and SLC2A1) were associated with poor patient outcomes with an increased hazard ratio in LUAD. Knockdown of them, both separately and simultaneously, suppressed lung cancer cell proliferation and migration ability in vitro and prolonged survival time in metastatic tumor mouse models. Moreover, these four biomarkers were found to be overexpressed in tumor tissues from LUAD patients, and the total immunohistochemical staining scores correlated with poor prognosis.

Conclusions: These results suggest that these four identified genes could be theranostic biomarkers for stratifying high-risk patients who develop relapse/metastasis in early-stage LUAD. Developing therapeutic approaches for the four biomarkers may benefit early-stage LUAD patients after surgery.

Adverse impact of bone metastases on clinical outcomes of patients with advanced non-small cell lung cancer treated with immune checkpoint inhibitors

Background

Bone metastasis (BoM) is common in patients with advanced non‐small cell lung cancer (NSCLC) and considered as one of the negative prognostic factors. However, the impact of BoM on clinical outcomes of patients with advanced NSCLC treated with immune checkpoint inhibitors (ICIs) remains unclear.

Methods

A total of 103 patients treated with ICI monotherapy and 101 patients treated with ICIs combined with chemotherapy or antiangiogenesis therapy were retrospectively analyzed. The differences in progression‐free survival (PFS), overall survival (OS) and objective response rate (ORR) between BoM+ and BoM− were investigated.

Results

Of those 101 patients who received combination therapy, no significant difference between BoM− and BoM+ in terms of both median PFS and median OS (median PFS, 10.1 vs. 12.1 months, P = 0.6; median OS, NR vs. 24.6 months, P = 0.713) was determined. In contrast, of the 103 patients who received ICI monotherapy, BoM+ patients had an inferior PFS (4.2 vs. 6.7 months, P = 0.0484) and OS (12.5 vs. 23.9 months, P = 0.0036) compared with BoM− patients. The univariate and multivariate analysis in the ICI monotherapy group also identified BoM as an independent factor attenuating the efficacy of ICI monotherapy. Of all BoM+ patients who received ICI monotherapy, neither palliative radiotherapy nor bisphosphonate drugs improved OS (palliative radiotherapy: 12.5 vs. 16.7 months, P = 0.487; bisphosphonate drugs: 12.5 vs. 9.7 months, P = 0.568).

Conclusions

BoM attenuated the efficacy of ICI monotherapy in patients with advanced NSCLC. Of BoM+ patients who received ICI monotherapy, neither palliative radiotherapy nor bisphosphonate drugs improved OS. Other therapeutic strategies are needed for patients with BoM.

Emerging role of phytochemicals in targeting predictive, prognostic, and diagnostic biomarkers of lung cancer

Lung-cancer is the foremost cause of cancer in humans worldwide, of which 80-85% cases are composed of non-small cell lung carcinoma. All treatment decisions depend on the pattern of biomarkers selection to enhance the response to the targeted therapies. Although advanced treatments are available for lung-cancer, the disease treatment remains not adequate. There are several synthetic chemotherapeutic agents available for the treatment of lung cancer. However, due to their toxic effect, survival rate is still 15-18%. Besides, medicinal plants are a huge reservoir of natural products that provide protective effects against lung cancer. Likewise, successful studies of potential phytochemicals in targeting lung-cancer biomarkers have created a novel paradigm for the discovery of potent drugs against lung-cancer. Hence, to defeat severe toxicity and resistance towards the synthetic drugs, detailed studies are required regarding the available phytochemicals and targets responsible for the treatment of lung-cancer. The present review provides a comprehensive information about the lung-cancer biomarkers under the classification of predictive, prognostic, and diagnostic type. Moreover, it discusses and enlists the phytochemicals with mode of action against different biomarkers, effective doses in in vitro, in vivo, and clinical studies, the limitations associated with usage of phytochemicals as a drug to prevent/cure lung-cancer and the latest techniques employed to overcome such issues.

Targeting KRAS Mutant Non-Small-Cell Lung Cancer: Past, Present and Future

Lung cancer is the most frequent cancer with an aggressive clinical course and high mortality rates. Most cases are diagnosed at advanced stages when treatment options are limited and the efficacy of chemotherapy is poor. The disease has a complex and heterogeneous background with non-small-cell lung cancer (NSCLC) accounting for 85% of patients and lung adenocarcinoma being the most common histological subtype. Almost 30% of adenocarcinomas of the lung are driven by an activating Kirsten rat sarcoma viral oncogene homolog (KRAS) mutation. The ability to inhibit the oncogenic KRAS has been the holy grail of cancer research and the search for inhibitors is immensely ongoing as KRAS-mutated tumors are among the most aggressive and refractory to treatment. Therapeutic strategies tailored for KRAS+ NSCLC rely on the blockage of KRAS functional output, cellular dependencies, metabolic features, KRAS membrane associations, direct targeting of KRAS and immunotherapy. In this review, we provide an update on the most recent advances in anti-KRAS therapy for lung tumors with mechanistic insights into biological diversity and potential clinical implications.

Harnessing cell-free DNA: plasma circulating tumour DNA for liquid biopsy in genitourinary cancers

In the era of precision oncology, liquid biopsy techniques, especially the use of plasma circulating tumour DNA (ctDNA) analysis, represent a paradigm shift in the use of genomic biomarkers with considerable implications for clinical practice. Compared with tissue-based tumour DNA analysis, plasma ctDNA is more convenient to test, more readily accessible, faster to obtain and less invasive, minimizing procedure-related risks and offering the opportunity to perform serial monitoring. Additionally, genomic profiles of ctDNA have been shown to reflect tumour heterogeneity, which has important implications for the identification of resistant clones and selection of targeted therapy well before clinical and radiographic changes occur. Moreover, plasma ctDNA testing can also be applied to cancer screening, risk stratification and quantification of minimal residual disease. These features provide an unprecedented opportunity for early treatment of patients, improving the chances of treatment success.

Overall survival in patients with lung adenocarcinoma harboring "niche" mutations: an observational study

Objective: In addition to the most common somatic lung cancer mutations (i. e., KRAS and EGFR mutations), other genes may harbor mutations that could be relevant for lung cancer. We defined BRAF, c-MET, DDR2, HER2, MAP2K1, NRAS, PIK3CA, and RET mutations as “niche” mutations and analyzed. The aim of this retrospective cohort study was to assess the differences in the overall survival (OS) of patients with lung adenocarcinoma harboring niche somatic mutations.

Results: Data were gathered for 252 patients. Mutations were observed in all genes studied, except c-MET, DDR2, MAP2K1, and RET. The multivariable analysis showed that 1) niche mutations had a higher mortality than EGFR mutations (HR = 2.3; 95% CI = 1.2–4.4; p = 0.009); 2) KRAS mutations had a higher mortality than EGFR mutations (HR = 2.5; 95% CI = 1.4–4.5; p = 0.003); 3) niche mutations presented a similar mortality to KRAS mutations (HR = 0.9; 95% CI = 0.6–1.5; p = 0.797).

Methods: Three cohorts of mutations were selected from patients with lung adenocarcinoma and their OS was compared. Mutations that were searched for, were 1) BRAF, c-MET, DDR2, HER2, MAP2K1, NRAS, PIK3CA, and RET; 2) K-RAS; and 3) EGFR. Differences in OS between these three cohorts were assessed by means of a multivariable Cox model that adjusted for age, sex, smoking habits, clinical stages, and treatments.

Conclusions: Niche mutations exhibited an increased risk of death when compared with EGFR mutations and a similar risk of death when compared with KRAS mutations.

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.

Quality of life analysis in lung cancer: A systematic review of phase III trials published between 2012 and 2018

OBJECTIVES

We previously reported that quality of life (QoL) is not included among trial endpoints and QoL results are underreported in a significant proportion of phase III oncology trials. Here we describe QoL adoption, reporting and methodology of QoL analysis in lung cancer trials.

MATERIALS AND METHODS

We selected all primary publications of lung cancer phase III trials assessing anticancer drugs published between 2012 and 2018 by 11 major journals.

RESULTS

122 publications were included. In 39 (32.0%) publications, QoL was not listed among endpoints: in 10/17 (58.8%) early stage/locally advanced NSCLC, in 15/54 (27.8%) first-line of advanced NSCLC; in 10/41 (24.4%) second and further lines of advanced NSCLC, in 4/10 (40.0%) SCLC. Proportion of trials not including QoL was similar over time: 32.9% publications in 2012-2015 vs. 30.6% in 2016-2018. Out of 83 trials including QoL among endpoints, QoL results were absent in 36 primary publications (43.4%). Proportion of trials without QoL results in primary publication increased over time (30.6% 2012-2015 vs. 61.8% 2016-2018, p = 0.005). Overall, QoL data were not available in 75/122 (61.5%) primary publications, due to the absent endpoint or unpublished results. QoL data were lacking in 48/68 (70.6%) publications of trials with overall survival as primary endpoint, 27/54 (50.0%) with other primary endpoints and 28/54 (51.9%) publications with a positive result. For trials including QoL among endpoints but lacking QoL results in primary publication, probability of secondary publication was 6.3%, 30.1% and 49.8% after 1, 2 and 3 years respectively, without evidence of improvement comparing 2012-2015 vs. 2016-2018.

CONCLUSION

QoL is not assessed or published in many phase III lung cancer trials, a setting where QoL value should be highly considered, due to high symptom burden and generally limited life expectancy. Timely inclusion of results in primary publications is worsening in recent years.

Prediction of response to anti-PD-1 therapy in patients with non-small-cell lung cancer by electronic nose analysis of exhaled breath

BACKGROUND

Immune checkpoint inhibitors have improved survival outcome of advanced non-small-cell lung cancer (NSCLC). However, most patients do not benefit. Therefore, biomarkers are needed that accurately predict response. We hypothesized that molecular profiling of exhaled air may capture the inflammatory milieu related to the individual responsiveness to anti-programmed death ligand 1 (PD-1) therapy. This study aimed to determine the accuracy of exhaled breath analysis at baseline for assessing nonresponders versus responders to anti-PD-1 therapy in NSCLC patients.

METHODS

This was a prospective observational study in patients receiving checkpoint inhibitor therapy using both a training and validation set of NSCLC patients. At baseline, breath profiles were collected in duplicate by a metal oxide semiconductor electronic nose (eNose) positioned at the rear end of a pneumotachograph. Patients received nivolumab or pembrolizumab of which the efficacy was assessed by Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1 at 3-month follow-up. Data analysis involved advanced signal-processing and statistics based on independent t-tests followed by linear discriminant and receiver operating characteristic (ROC) analysis.

RESULTS

Exhaled breath data of 143 NSCLC patients (training: 92, validation: 51) were available at baseline. ENose sensors contributed significantly (P < 0.05) at baseline in differentiating between patients with different responses at 3 months of anti-PD-1 treatment. The eNose sensors were combined into a single biomarker with an ROC-area under the curve (AUC) of 0.89 [confidence interval (CI) 0.82-0.96]. This AUC was confirmed in the validation set: 0.85 (CI 0.75-0.96).

CONCLUSION

ENose assessment was effective in the noninvasive prediction of individual patient responses to immunotherapy. The predictive accuracy and efficacy of the eNose for discrimination of immunotherapy responder types were replicated in an independent validation set op patients. This finding can potentially avoid application of ineffective treatment in identified probable nonresponders.

Moderate Psoriatic Arthritis and Perspectives from Phosphodiesterase-4 Inhibition

Although there is no universally approved definition of moderate psoriatic arthritis (PsA), many clinicians see patients who they feel fit into this category: patients with limited joint involvement, but who might also show other manifestations of the disease, as well as a range of comorbidities. In his presentation, Dr Siebert described the challenges faced in treating this group of patients, who are mostly not captured in clinical trials. Recent advances in PsA treatment have focussed towards the severe end of the spectrum, suggesting that more must be learned around treatment options for patients with moderate disease. This represents a large unmet need. Given the heterogeneity of this patient population, a range of effective treatments is needed. Prof Gladman then presented data from longitudinal cohorts to illustrate the high burden of disease in patients with PsA who had a limited number of affected joints. By comparing patients with oligoarticular PsA (i.e., ≤4 affected joints) with those with polyarticular arthritis (≥5 affected joints), Prof Gladman showed that disease burden is not solely driven by the number of affected joints, but also by other PsA manifestations and/or comorbidities. There are clear gaps in our knowledge of PsA; to address these, population studies and trials of potential treatments are needed. Phosphodiesterase-4 (PDE4) inhibition is one potential treatment strategy that is currently being investigated. Dr Behrens described a post-hoc analysis of data pooled from three Phase III clinical trials that suggests the PDE4 inhibitor apremilast may be an effective treatment for patients with moderate PsA. It is hoped that this will be confirmed by the ongoing FOREMOST trial, a Phase IV study of apremilast in patients with oligoarticular PsA.

Sites of metastasis and association with clinical outcome in advanced stage cancer patients treated with immunotherapy

Background

Selecting the appropriate patients to receive immunotherapy (IO) remains a challenge due to the lack of optimal biomarkers. The presence of liver metastases has been implicated as a poor prognostic factor in patients with metastatic cancer. We investigated the association between sites of metastatic disease and clinical outcomes in patients receiving IO.

Methods

We conducted a retrospective review of 90 patients treated on IO-based phase 1 clinical trials at Winship Cancer Institute of Emory University between 2009 and 2017. Overall survival (OS) and progression-free survival (PFS) were measured from the first dose of IO to date of death or hospice referral and clinical or radiographic progression, respectively. Clinical benefit (CB) was defined as a best response of complete response (CR), partial response (PR), or stable disease (SD). Univariate analysis (UVA) and Multivariate analysis (MVA) were carried out using Cox proportional hazard model or logistic regression model. Covariates included age, whether IO is indicated for the patient’s histology, ECOG performance status, Royal Marsden Hospital (RMH) risk group, number of metastatic sites, and histology.

Results

The median age was 63 years and 53% of patients were men. The most common histologies were melanoma (33%) and gastrointestinal cancers (22%). Most patients (73.3%) had more than one site of distant metastasis. Sites of metastasis collected were lymph node (n = 58), liver (n = 40), lung (n = 37), bone (n = 24), and brain (n = 8). Most patients (80.7%) were RMH good risk. Most patients (n = 62) had received 2+ prior lines of systemic treatment before receiving IO on trial; 27 patients (30.0%) received prior ICB. Liver metastases were associated with significantly shorter OS (HR: 0.38, CI: 0.17–0.84, p = 0.017). Patients with liver metastasis also trended towards having shorter PFS (HR: 0.70, CI: 0.41–1.19, p = 0.188). The median OS was substantially longer for patients without liver metastases (21.9 vs. 8.1 months, p = 0.0048).

Conclusions

Liver metastases may be a poor prognostic factor in patients receiving IO on phase 1 clinical trials. The presence of liver metastases may warrant consideration in updated prognostic models if these findings are validated in a larger prospective cohort.

Downregulating SynCAM and MPP6 expression is associated with ovarian cancer progression

Synaptic cell adhesion molecules (SynCAMs) are single transmembrane proteins that belong to the immunoglobulin superfamily of cell adhesion molecules. In the present study, a decrease in SynCAM levels in ovarian tumor tissues compared with normal tissues is reported; the downregulation was accompanied by the grade malignancy. The observations suggested that SynCAM may be essential for important novel functions in ovarian cancer. Further experiments showed that low SynCAM expression inhibited membrane palmitoylated protein 6 (MPP6) expression, a member of the palmitoylated membrane protein subfamily of peripheral membrane-associated guanylate kinases. In addition, low levels of MPP6 in ovarian tumor tissues correlated with shorter patient survival. A SynCAM-regulated pathway may provide molecular targets for the treatment of ovarian cancer and novel biomarkers to be used in clinical diagnosis.

A Simulation Study Comparing Different Statistical Approaches for the Identification of Predictive Biomarkers

Identification of relevant biomarkers that are associated with a treatment effect is one requirement for adequate treatment stratification and consequently to improve health care by administering the best available treatment to an individual patient. Various statistical approaches were proposed that allow assessing the interaction between a continuous covariate and treatment. Nevertheless, categorization of a continuous covariate, e.g., by splitting the data at the observed median value, appears to be very prevalent in practice. In this article, we present a simulation study considering data as observed in a randomized clinical trial with a time-to-event outcome performed to compare properties of such approaches, namely, Cox regression with linear interaction, Multivariable Fractional Polynomials for Interaction (MFPI), Local Partial-Likelihood Bootstrap (LPLB), and the Subpopulation Treatment Effect Pattern Plot (STEPP) method, and of strategies based on categorization of continuous covariates (splitting the covariate at the median, splitting at quartiles, and using an "optimal" split by maximizing a corresponding test statistic). In different scenarios with no interactions, linear interactions or nonlinear interactions, type I error probability and the power for detection of a true covariate-treatment interaction were estimated. The Cox regression approach was more efficient than the other methods for scenarios with monotonous interactions, especially when the number of observed events was small to moderate. When patterns of the biomarker-treatment interaction effect were more complex, MFPI and LPLB performed well compared to the other approaches. Categorization of data generally led to a loss of power, but for very complex patterns, splitting the data into multiple categories might help to explore the nature of the interaction effect. Consequently, we recommend application of statistical methods developed for assessment of interactions between continuous biomarkers and treatment instead of arbitrary or data-driven categorization of continuous covariates.

Targeting Immune Checkpoints in Lung Cancer: Current Landscape and Future Prospects

Lung cancer is the most prevalent and deadly cancer worldwide. Immune checkpoint therapy, which targets regulatory pathways in T cells to boost anti-tumor immune response, has revolutionized lung cancer treatment paradigms. Inhibitors of the most established immune checkpoints such as programmed death-1 (PD-1)/PD-ligand 1 (PD-L1) have been approved by the US Food and Drug Administration in the management of lung cancer. Despite the pronounced survival benefits that have been seen with immune checkpoint inhibitors, not all lung cancer patients respond to single-agent immunotherapy due to the complexity of the immune microenvironment and tumor resistance. Alternative immune checkpoints beyond PD-1/PD-L1 must be sought so that more patients can benefit from immune checkpoint therapy. Additionally, novel combination strategies of immunotherapy and conventional treatments (e.g., chemotherapy, radiotherapy, and targeted therapy) have shown promise in some clinical trials. Meanwhile, identification of predictive biomarkers is pivotal in selecting eligible patients for immunotherapy and to guide individualized clinical decision-making. The future of immune checkpoint therapy in lung cancer is not devoid of challenges, and more prospective clinical studies are awaited to translate our understanding from bench to bedside.

The immune microenvironment in non-small cell lung cancer is predictive of prognosis after surgery

The impact of the tumor immune microenvironment on overall survival in non‐small cell lung cancer (NSCLC) has been studied, but there is little information on its relevance for risk of relapse after surgery. Understanding more about the immune microenvironment in previously untreated NSCLC could help in identifying high‐risk patients and patients more likely to benefit from neoadjuvant/adjuvant immunotherapy. Here, we examined gene expression in 399 surgically derived NSCLC samples and 47 samples from normal lung, using Agilent microarray and RNA sequencing. In 335 of the tumor samples, programmed death‐ligand 1 (PD‐L1) expression was evaluated by immunohistochemistry. Gene expression was used to estimate content of immune cells and to calculate an immune score. Properties of the immune microenvironment, and its impact on prognosis, were compared in histological subgroups and gene expression subtypes. Tumors with an active immune microenvironment were found for both adenocarcinomas (AD) and squamous cell carcinomas (SCC). In AD, high immune score and high estimates of several immune cell types belonging to the adaptive immune system were associated with better progression‐free survival (PFS), while in SCC, no association between immune characteristics and PFS was found. The immune microenvironment, including PD‐L1 expression, and its impact on prognosis showed clear differences in AD and SCC gene expression subtypes. In conclusion, the NSCLC immune microenvironment is predictive of prognosis after surgery. Lung AD and SCC gene expression subtypes should be investigated as potential prognostic biomarkers in patients treated with immune checkpoint inhibitors.

Defining aggressive or early progressing nononcogene-addicted non-small-cell lung cancer: a separate disease entity?

A substantial proportion of patients with nononcogene-addicted non-small-cell lung cancer (NSCLC) has 'aggressive disease', as reflected in short time to progression or lack of disease control with initial platinum-based chemotherapy. Recently, clinical correlates of aggressive disease behavior during first-line therapy have been shown to predict greater benefit from addition of nintedanib to second-line docetaxel in adenocarcinoma NSCLC. Positive predictive effects of aggressive disease have since been reported with other anti-angiogenic agents (ramucirumab and bevacizumab), while such features may negatively impact on outcomes with nivolumab in nonsquamous NSCLC with low PD-L1 expression. Based on a review of the clinical data, we recommend aggressive nonsquamous NSCLC should be defined by progression within <6-9 months of first-line treatment initiation.

The Roles of Common Variation and Somatic Mutation in Cancer Pharmacogenomics

Cancer pharmacogenomics is the science concerned with understanding genetic alterations and its effects on the pharmacokinetics and pharmacodynamics of anti-cancer drugs, with the aim to provide cancer patients with the precise medication that will achieve a good response and cause low/no incidence of adverse events. Advances in biotechnology and bioinformatics have enabled genomic research to evolve from the evaluation of alterations at the single-gene level to studies on the whole-genome scale using large-scale genotyping and next generation sequencing techniques. International collaborative efforts have resulted in the construction of databases to curate the identified genetic alterations that are clinically significant, and these are currently utilized in clinical sequencing and liquid biopsy screening/monitoring. Furthermore, countless clinical studies have accumulated sufficient evidence to match cancer patients to therapies by utilizing the information of clinical-relevant alterations. In this review we summarize the importance of germline alterations that act as predictive biomarkers for drug-induced toxicity and drug response as well as somatic mutations in cancer cells that function as drug targets. The integration of genomics into the medical field has transformed the era of cancer therapy from one-size-fits-all to cancer precision medicine.