Serum Biomarkers Associated with Clinical Outcomes Fail to Predict Brain Metastases in Patients with Stage IV Non-Small Cell Lung Cancers

Multi-Omics Analysis of Brain Metastasis Outcomes Following Craniotomy

Background

The incidence of brain metastasis continues to increase as therapeutic strategies have improved for a number of solid tumors. The presence of brain metastasis is associated with worse prognosis but it is unclear if distinctive biomarkers can separate patients at risk for CNS related death.

Methods

We executed a single institution retrospective collection of brain metastasis from patients who were diagnosed with lung, breast, and other primary tumors. The brain metastatic samples were sent for RNA sequencing, proteomic and metabolomic analysis of brain metastasis. The primary outcome was distant brain failure after definitive therapies that included craniotomy resection and radiation to surgical bed. Novel prognostic subtypes were discovered using transcriptomic data and sparse non-negative matrix factorization.

Results

We discovered two molecular subtypes showing statistically significant differential prognosis irrespective of tumor subtype. The median survival time of the good and the poor prognostic subtypes were 7.89 and 42.27 months, respectively. Further integrated characterization and analysis of these two distinctive prognostic subtypes using transcriptomic, proteomic, and metabolomic molecular profiles of patients identified key pathways and metabolites. The analysis suggested that immune microenvironment landscape as well as proliferation and migration signaling pathways may be responsible to the observed survival difference.

Conclusion

A multi-omics approach to characterization of brain metastasis provides an opportunity to identify clinically impactful biomarkers and associated prognostic subtypes and generate provocative integrative understanding of disease.

Initial Approach to Patients with a Newly Diagnosed Solitary Brain Metastasis

Solitary brain metastasis is defined by a single metastatic brain lesion as the only site of metastasis. The initial approach to this condition consists of radiographical evaluation to establish diagnosis, followed by assessment of functional and prognostic status. Neurologic symptom management consists of using dexamethasone and antiepileptic medications. Treatment consists of a combination of surgical and radiation therapy. Surgical treatment is indicated where there is a need for tissue diagnosis or immediate alleviation of neurologic symptoms and mass effect. Stereotactic radiosurgery has become an effective treatment modality. Whole-brain radiation therapy may have a role as an adjunctive therapy.

The clinical value of carcinoembryonic antigen for tumor metastasis assessment in lung cancer

Background

Carcinoembryonic antigen (CEA) as a diagnostic or prognostic marker has been widely studied in patients with lung cancer. However, the relationship between serum CEA and tumor metastasis in lung cancer remains controversial. This study aimed to investigate the ability of serum CEA to assess tumor metastasis in lung cancer patients.

Methods

We performed a retrospective analysis of 238 patients diagnosed with lung cancer from January to December 2016 at pneumology department of Dazhou Central Hospital (Dazhou, China). Serum CEA levels were quantified in each patient at the time of diagnosis of lung cancer. Metastasis was confirmed by computed tomography (CT), and/or positron emission tomography (PET) and/or surgery or other necessary detecting methods.

Results

Of the 213 patients eligible for final analysis, 128 were diagnosed with metastasis and 85 were diagnosed without metastasis. Compared to non-metastatic patients, the serum CEA was markedly higher in patients with metastasis (p < 0.001), and the area under the curve (AUC) was 0.724 (95% CI [0.654–0.793]). Subsequent analyses regarding the number and location of tumor metastases showed that CEA also had clinical value for multiple metastases versus single metastasis (AUC = 0.780, 95% CI [0.699–0.862]) and distant metastasis versus non-distant metastasis (AUC = 0.815, 95% CI [0.733–0.897]). In addition, we found that tumor size, histology diagnosis, age and gender had no impact on the assessment performance of CEA.

Conclusion

Our study suggested the serum CEA as a valuable marker for tumor metastases assessment in newly diagnosed lung cancer patients, which could have some implications in clinical application.

Identification of CD37, cystatin A, and IL-23A gene expression in association with brain metastasis: analysis of a prospective trial

PURPOSE/OBJECTIVES

We aimed to assess the predictive value of a lung cancer gene panel for the development of brain metastases.

MATERIALS/METHODS

Between 2011 and 2015, 102 patients with lung cancer were prospectively enrolled in a clinical trial in which a diagnostic fine-needle aspirate was obtained. Gene expression was conducted on all samples that rendered a diagnosis of non-small cell lung cancer (NSCLC). Subsequent retrospective analysis of brain metastases-related outcomes was performed by reviewing patient electronic medical records. A competing risk multivariable regression was performed to estimate the adjusted hazard ratio for the development of brain metastases and non-brain metastases from NSCLC.

RESULTS

A total of 49 of 102 patients had died by the last follow-up. Median time of follow-up was 13 months (range 0.23-67 months). A total of 17 patients developed brain metastases. Median survival time after diagnosis of brain metastases was 3.58 months (95% confidence interval (CI) 2.17, not available). A total of 30 patients developed metastases without any evidence of brain metastases until the time of death or last follow-up. Competing risk analysis identified three genes that were downregulated differentially in the patients with brain metastases versus non-brain metastatic disease: CD37 (0.017), cystatin A (0.022), and IL-23A (0.027). Other factors associated with brain metastases include: stage T ( P ⩽ 8.3e^-6) and stage N ( P= 6.8e^-4).

CONCLUSIONS

We have identified three genes, CD37, cystatin A, and IL-23A, for which downregulation of gene expression was associated with a greater propensity for developing brain metastases. Validation of these biomarkers could have implications on surveillance patterns in patients with brain metastases from NSCLC.

A Comprehensive Meta-Analysis of Association between EGFR Mutation Status and Brain Metastases in NSCLC

Non-small cell lung cancer (NSCLC) with epidermal growth factor receptor (EGFR) mutation have different clinicopathological characteristics compared with EGFR wild type NSCLC. A growing number of studies focused on the relevance between EGFR mutation status and brain metastases (BM) in NSCLC, but it remains controversial. Therefore, this study performed a comprehensive meta-analysis to untangle this issue. Several electronic databases including Pubmed, Embase, Web of science and Cochrane database were thoroughly searched. The odds ratio (OR) with 95% confidence interval (95%CI) was pooled to evaluate the relevance. Meta-regression analysis and subgroup analysis were conducted according to the heterogeneity. A total of 26 studies were identified finally in this meta-analysis. The overall OR was 1.58 (95%CI: 1.36-1.84), which indicated that EGFR mutation had a positive association with BM of NSCLC. The subgroup analysis resulted from eleven studies with lung adenocarcinoma revealed a higher possibility of BM in NSCLC with EGFR mutation compared with EGFR wild (p < 0.05). There was no significant difference in the risk of BM between NSCLC EGFR exon 19 mutation and exon 21 point mutation (p = 0.23). This meta-analysis suggests that EGFR mutation can be a risk factor for BM in NSCLC.

Early detection of lung cancer biomarkers through biosensor technology: A review

Lung cancer is undoubtedly one of the most serious health issues of the 21 st century. It is the second leading cause of cancer-related deaths in both men and women　worldwide, accounting for about 1.5 million deaths annually. Despite advances in the treatment of lung cancer with new pharmaceutical products and technological improvements, morbidity and mortality rates remains a significant challenge for the cancer biologists and oncologists. The vast majority of lung cancer patients present with advanced-stage of pathological process that ultimately leads to poor prognosis and a five-year survival rate less than 20%. Early and accurate screening and analysis using cost-effective means are urgently needed to effectively diagnose the disease, improve the survival rate or to reduce mortality and morbidity associated with lung cancer patients. Thus, the only hope for early recognition of risk factors and timely diagnosis and treatment of lung cancer is biosensors technology. Novel biosensing based diagnostics approaches for predicting metastatic risks are likely to have significant therapeutic and clinical impact in the near future. This article systematically provides a brief overview of various biosensing platforms for identification of lung cancer disease biomarkers, with a specific focus on recent advancements in electrochemical and optical biosensors, analytical performances of different biosensors, challenges and further research opportunities for routine clinical analysis.

Clinical implications for pro-GRP in small cell lung cancer. A single center experience

BACKGROUND

Recently, pro-gastrin-releasing peptide (pro-GRP) became available as an alternative sensitive, specific and reliable tumor marker for patients with small cell lung cancer (SCLC), both in limited (LD) and diffuse disease (DD).

METHODS

We retrospectively analyzed pro-GRP, neuron-specific enolase (NSE) and CEA in patients with SCLC and non-small cell lung cancer (NSCLC). Serum pro-GRP level was measured with electrochemiluminescence at our laboratory (cutoff 77.8 pg/mL). Continuous variables were analyzed with the Mann-Whitney test, contingency data with Fisher's exact test. Receiver operator characteristic (ROC) curve analysis was performed to identify threshold values to set the highest sensitivity (Sn) and specificity (Sp) values.

RESULTS

A total of 65 patients were studied (49 men, median age 67 years, range 27-79). Thirty-seven patients had SCLC (29 DD, 8 LD) and 28 advanced NSCLC. Median pro-GRP level was 919 pg/mL (range 22-147,350) in SCLC and 32 pg/mL (range 10-119.2) in NSCLC (p<0.0001). NSE was 4.38-fold higher in SCLC patients (p = 0.0005); CEA did not reveal significant differences between groups. Pro-GRP Sn and Sp were 86.4% and 96.4%, respectively. With ROC curve analysis, a cutoff value of 329.3 pg/mL showed a Sn of 75.8% and Sp of 87.5% in discriminating DD from LD. Pro-GRP was not influenced by either liver metastases or renal impairment.

CONCLUSIONS

Pro-GRP is sensitive for SCLC diagnosis. Since high marker levels are related to high disease burden, pro-GRP may have a negative prognostic significance. Follow-up studies are required to define its role in clinical practice in monitoring responses to treatment and early relapses.

Beyond the Biomarker: Understanding the Diverse Roles of Human Epididymis Protein 4 in the Pathogenesis of Epithelial Ovarian Cancer

Human epididymis protein 4 (HE4) is an important clinical biomarker used for the detection of epithelial ovarian cancer (EOC). While much is known about the predictive power of HE4 clinically, less has been reported regarding its molecular role in the progression of EOC. A deeper understanding of HE4’s mechanistic functions may help contribute to the development of novel targeted therapies. Thus far, it has been difficult to recommend HE4 as a therapeutic target owing to the fact that its role in the progression of EOC has not been extensively evaluated. This review summarizes what is collectively known about HE4 signaling and how it functions to promote tumorigenesis, chemoresistance, and metastasis in EOC, with the goal of providing valuable insights that will have the potential to aide in the development of new HE4-targeted therapies.

Baseline and On-Treatment Characteristics of Serum Tumor Markers in Stage IV Oncogene-Addicted Adenocarcinoma of the Lung

INTRODUCTION

The role of serum tumor markers in the modern management of advanced NSCLC remains poorly described.

METHODS

A single-center retrospective analysis of available carcinoembryonic antigen, CA125, CA19.9, and CA27.29 levels at baseline and during treatment of stage IV lung adenocarcinoma by oncogenic driver was conducted.

RESULTS

A total of 142 patients were analyzed (60 with anaplastic lymphoma kinase gene [ALK] rearrangement, 50 with EGFR mutation, four with ROS1 rearrangement, and 29 with KRAS mutation). Of these, 82% had at least one marker (95% if all four markers were measured), with CA27.29 being the most commonly increased and CA19.9 the rarest. Only CA27.29 differed significantly by oncogene (it was less common in KRAS) (p = 0.016). The median times to nadir during tyrosine kinase inhibitor (TKI) therapy in EGFR and ALK cases were 16.4 and 20 weeks, respectively. Of the 41 patients with EGFR mutation or ALK or ROS1 rearrangement, 24 (59%) demonstrated an initial increase within the first 4 weeks of TKI therapy, 58% of whom then had their levels fall below baseline. An increase in marker level of 10% or more from nadir occurred in 53% of systemic and 22% of central nervous system-only progression.

CONCLUSIONS

Serum tumor markers are frequently increased in lung adenocarcinoma regardless of driver oncogene. Changes within the first 4 weeks of therapy may be misleading. Progression is associated with marker increases, especially in sites other than the central nervous system.

EGFR and KRAS Mutations Predict the Incidence and Outcome of Brain Metastases in Non-Small Cell Lung Cancer

Background: Lung cancer is the leading cause of brain metastases (BM). The identification of driver oncogenes and matched targeted therapies has improved outcome in non-small cell lung cancer (NSCLC) patients; however, a better understanding of BM molecular biology is needed to further drive the process in this field. Methods: In this observational study, stage IV NSCLC patients tested for EGFR and KRAS mutations were selected, and BM incidence, recurrence and patients’ outcome were assessed. Results: A total of 144 patients (142 Caucasian and two Asian) were selected, including 11.27% with EGFR-mutant and 33.10% with KRAS-mutant tumors, and 57.04% patients had developed BM. BM incidence was more frequent in patients with EGFR mutation according to multivariate analyses (MVA) (Odds ratio OR = 8.745 [1.743–43.881], p = 0.008). Among patients with treated BM, recurrence after local treatment was less frequent in patients with KRAS mutation (OR = 0.234 [0.078–0.699], p = 0.009). Among patients with untreated BM, overall survival (OS) was shorter for patients with KRAS mutation according to univariate analysis (OR = 7.130 [1.240–41.012], p = 0.028), but not MVA. Conclusions: EGFR and KRAS mutations have a predictive role on BM incidence, recurrence and outcome in Caucasian NSCLC patients. These results may impact the routine management of disease in these patients. Further studies are required to assess the influence of other biomarkers on NSCLC BM.

Baseline neutrophil-lymphocyte ratio is associated with baseline and subsequent presence of brain metastases in advanced non-small-cell lung cancer

We examined the predictive value of neutrophil–lymphocyte ratio (NLR) by examining their association with the baseline presence and subsequent development of brain metastases in patients with stage IV non-small cell lung cancer (NSCLC). We examined the predictive value of NLR for brain metastasis in 260 stage IV NSCLC. Logistic regression models and competing risk analysis were used to determine the association of NLR with baseline and subsequent presence of brain metastases. Multivariate analysis reveals that patients with high NLR (≥4.95) had significantly more brain metastases at diagnosis than those with low NLR (Odds Ratio = 2.59, P = 0.01). In patients who had no baseline brain metastasis, competing risks analysis revealed that patients with high NLR showed higher cumulative incidence of subsequent brain metastases, compared to those with low NLR (P = 0.017). A high NLR was associated with the baseline presence or the subsequent development of brain metastases, particularly in the group with adenocarcinoma (P = 0.013 and P = 0.044, respectively). Furthermore, an increase in NLR during treatment was associated with subsequent brain metastases (P = 0.004). The NLR is an independent predictive factor for the baseline presence of brain metastases and subsequent brain metastases in stage IV NSCLC.

Diagnostic Value of Combining Tumor and Inflammatory Markers in Lung Cancer

BACKGROUND

Despite major advances in lung cancer treatment, early detection remains the most promising way of improving outcomes. To detect lung cancer in earlier stages, many serum biomarkers have been tested. Unfortunately, no single biomarker can reliably detect lung cancer. We combined a set of 2 tumor markers and 4 inflammatory or metabolic markers and tried to validate the diagnostic performance in lung cancer.

METHODS

We collected serum samples from 355 lung cancer patients and 590 control subjects and divided them into training and validation datasets. After measuring serum levels of 6 biomarkers (human epididymis secretory protein 4 [HE4], carcinoembryonic antigen [CEA], regulated on activation, normal T cell expressed and secreted [RANTES], apolipoprotein A2 [ApoA2], transthyretin [TTR], and secretory vascular cell adhesion molecule-1 [sVCAM-1]), we tested various sets of biomarkers for their diagnostic performance in lung cancer.

RESULTS

In a training dataset, the area under the curve (AUC) values were 0.821 for HE4, 0.753 for CEA, 0.858 for RANTES, 0.867 for ApoA2, 0.830 for TTR, and 0.552 for sVCAM-1. A model using all 6 biomarkers and age yielded an AUC value of 0.986 and sensitivity of 93.2% (cutoff at specificity 94%). Applying this model to the validation dataset showed similar results. The AUC value of the model was 0.988, with sensitivity of 93.33% and specificity of 92.00% at the same cutoff point used in the validation dataset. Analyses by stages and histologic subtypes all yielded similar results.

CONCLUSIONS

Combining multiple tumor and systemic inflammatory markers proved to be a valid strategy in the diagnosis of lung cancer.