Serum Protein Expression Predicts Recurrence in Patients With Early-Stage Lung Cancer After Resection

Prognostic evaluation of preoperative serum tumor marker-negative cases in non-small cell lung cancer: A retrospective study

BACKGROUND

The role of various serum tumor markers (TMs) has been reported in non-small cell lung cancer (NSCLC). However, the prognosis of patients with multiple TM-negative NSCLC remain unclear.

AIMS

This study aimed to describe the characteristics and outcomes of patients with NSCLC undergoing surgery and to investigate their prognostic association with preoperative serum TM-negative cases.

METHODS AND RESULTS

We retrospectively evaluated 442 patients who underwent complete resection of stage I NSCLC between January 2004 and December 2019. These 442 patients were classified into a group whose preoperative serum levels of carcinoembryonic antigen (CEA), cytokeratin-19 fragment (CYFRA21-1), carbohydrate antigen 19-9 (CA19-9), and squamous cell carcinoma antigen (SCC Ag) were all negative (TM-negative group; n = 249, 56%) and a group with at least one positive marker (TM-positive group; n = 193, 44%). Among all patients, the TM-negative group showed higher 5-year recurrence-free survival (RFS) (92.6% vs. 79.1%; p < .01), and overall survival (OS) rates (86.3% vs. 68.6%; p < .01). After propensity score matching, patients in the TM-negative group still exhibited good 5-year RFS (92.1% vs. 81.4%; p = .01) and OS rates (87.6% vs. 72.6%; p < .01).

CONCLUSION

Our study suggests that NSCLC patients who are preoperatively negative for all serum TMs, such as CEA, CYFRA21-1, CA19-9, and SCC Ag, represent a subgroup with a particularly good prognosis.

Prognostic and predictive biomarkers in early stage NSCLC: CTCs and serum/plasma markers

Resection of early stage non-small cell lung cancer (NSCLC) offers patients the best hope of cure, however recurrence rates post-resection remain high suggesting the presence of micro-metastatic disease at the time of surgery undetected by standard staging methods. A critical step in the metastatic cascade is the entry of tumor cells into the circulation enabling their distribution to and seeding of distant organs. This review explores the evidence for predictive and prognostic circulating biomarkers in the early stage NSCLC population. We summarize studies that have explored a variety of targets including circulating proteins, nucleic acids and more recently circulating tumor cells (CTCs) as potentially clinically relevant biomarkers in the early stage setting. Circulating biomarkers may add clinically relevant information about the biological behavior of tumors over and above that provided by pathological staging. Improvement in the stratification of patients according to the likelihood of metastatic relapse after radical treatments such as surgical resection could allow more effective targeting of systemic therapies such as adjuvant chemotherapy.

Synthesis and biological characterization of protease-activated prodrugs of doxazolidine

Doxazolidine (doxaz) is a new anthracycline anticancer agent. While structurally similar to doxorubicin (dox), doxaz acts via a distinct mechanism to selectively enhance anticancer activity over cardiotoxicity, the most significant clinical impediment to successful anthracycline treatment. Here, we describe the synthesis and characterization of a prodrug platform designed for doxaz release mediated by secreted proteolytic activity, a common association with invasiveness and poor prognosis in cancer patients. GaFK-Doxaz is hydrolyzable by the proteases plasmin and cathepsin B, both strongly linked with cancer progression, as well as trypsin. We demonstrate that activation of GaFK-Doxaz releases highly potent doxaz that powerfully inhibits the growth of a wide variety of cancer cells (average IC(50) of 8 nM). GaFK-Doxaz is stable in human plasma and is poorly membrane permeable, thereby limiting activation to locally secreted proteolytic activity and reducing the likelihood of severe side effects.

A multi-analyte serum test for the detection of non-small cell lung cancer

BACKGROUND

In this study, we appraised a wide assortment of biomarkers previously shown to have diagnostic or prognostic value for non-small cell lung cancer (NSCLC) with the intent of establishing a multi-analyte serum test capable of identifying patients with lung cancer.

METHODS

Circulating levels of 47 biomarkers were evaluated against patient cohorts consisting of 90 NSCLC and 43 non-cancer controls using commercial immunoassays. Multivariate statistical methods were used on all biomarkers achieving statistical relevance to define an optimised panel of diagnostic biomarkers for NSCLC. The resulting biomarkers were fashioned into a classification algorithm and validated against serum from a second patient cohort.

RESULTS

A total of 14 analytes achieved statistical relevance upon evaluation. Multivariate statistical methods then identified a panel of six biomarkers (tumour necrosis factor-α, CYFRA 21-1, interleukin-1ra, matrix metalloproteinase-2, monocyte chemotactic protein-1 and sE-selectin) as being the most efficacious for diagnosing early stage NSCLC. When tested against a second patient cohort, the panel successfully classified 75 of 88 patients.

CONCLUSIONS

Here, we report the development of a serum algorithm with high specificity for classifying patients with NSCLC against cohorts of various 'high-risk' individuals. A high rate of false positives was observed within the cohort in which patients had non-neoplastic lung nodules, possibly as a consequence of the inflammatory nature of these conditions.

Establishment of a multi-analyte serum biomarker panel to identify lymph node metastases in non-small cell lung cancer

INTRODUCTION

In non-small cell lung cancer (NSCLC), the presence of locoregional lymph node metastases remains the most important prognostic factor and significantly guides treatment regimens. Unfortunately, currently-available noninvasive staging modalities have limited accuracy. The objective of this study was to create a multianalyte blood test capable of discriminating a patient's true (pathologic) nodal status preoperatively.

METHODS

Pretreatment serum specimens collected from 107 NSCLC patients with localized disease were screened with 47 biomarkers implicated in disease presence or progression. Multivariate statistical algorithms were then used to identify the optimal combination of biomarkers for accurately discerning each patient's nodal status.

RESULTS

We identified 15 candidate biomarkers that met our criteria for statistical relevance in discerning a patient's preoperative nodal status. A 'random forest' classification algorithm was used with these parameters to define a 6-analyte panel, consisting of macrophage inflammatory protein-1alpha, carcinoembryonic antigen, stem cell factor, tumor necrosis factor-receptor I, interferon-gamma, and tumor necrosis factor-alpha, that was the optimum combination of biomarkers for identifying a patient's pathologic nodal status. A Classification and Regression Tree analysis was then created with this panel that was capable of correctly classifying 88% of the patients tested, relative to the pathologic assessments. This value is in contrast to our observed 85% classification rate using conventional clinical methods.

CONCLUSIONS

This study establishes a serum biomarker panel with efficacy in discerning preoperative nodal status. With further validation, this blood test may be useful for assessing nodal status (including occult disease) in NSCLC patients facing tumor resection therapy.

Advances in genomic and proteomic studies of non-small-cell lung cancer: clinical and translational research perspective

Recent years have brought tremendous progress in the development of genomic and proteomic platforms to study cancer biology. Tests based on these platforms are helpful in early diagnosis, prognosis, and prediction of treatment benefit. Molecular studies performed on minimally invasive material (plasma, sputum) from individuals participating in longitudinal or case-control studies have approximately 70%-90% sensitivity and specificity to detect lung cancer. In operable non-small-cell lung cancer, genomic and proteomic studies yield better prognostic information than pathologic staging. There are several examples of successful identification of predictive assays for benefit from chemotherapy (ERCC1, RRM1, p27Kip1, and p53 expression) or targeted therapies (epidermal growth factor receptor [EGFR] gene copy number, EGFR activating mutations, EGFR protein expression, serum proteomic profile). These markers should be prospectively tested in clinical studies before they can be routinely used in the clinic.