Clinical characteristics and outcomes of patients with small cell lung cancer detected by CT screening

Characteristics and Outcomes of Small Cell Lung Cancer Detected by CT Screening

BACKGROUND

Previous studies with a limited number of patients have reported divergent findings on whether screening can detect small cell lung cancer (SCLC) at an earlier stage and whether there might be a survival benefit.

METHODS

This study examined the characteristics of SCLC detected by using low-dose CT (LDCT) screening in the National Lung Screening Trial, a randomized study of individuals at high risk for developing lung cancer comparing LDCT imaging vs chest radiography. SCLC was denoted as screen detected if diagnosed ≤ 1 year of a positive screen or after a longer period but with no time gap between diagnostic procedures of > 1 year; interval detected if diagnosed ≤ 1 year of a negative screen; and nonscreen detected if the subject did not receive any screens or otherwise as postscreening.

RESULTS

A total of 143 cases of SCLC were diagnosed, including 49 (34.2%) screen detected, 15 (10.5%) interval detected, and 79 (55.2%) nonscreened/postscreening. Of the screening phase-diagnosed cases (ie, screen or interval detected), a higher proportion of SCLC cases compared with NSCLC cases were interval detected (23% vs 5%; P < .0001). A higher proportion of all SCLC cases compared with NSCLC cases were advanced stage (III/IV: 86% vs 36%; P < .0001). The unfavorable SCLC stage distribution extended across screen-detected (80% stage III/IV), interval-detected (86%), and nonscreened/postscreening (90%) cancers. Among screen-detected SCLC, only 63.3% had ≥ 1 noncalcified nodule in the cancer lobe compared with 85.4% of NSCLC cases (P < .0001). Even with very small LDCT screen-detected nodules, a high proportion of SCLC cases were late stage. There was no significant difference in survival between screen- and interval-detected or postscreening SCLC.

CONCLUSIONS

"Early detection" with the use of LDCT imaging had no impact on SCLC outcomes. A successful screening modality should ideally detect SCLC earlier than when it can be detected on LDCT scans.

Histopathological transformation to small-cell lung carcinoma in non-small cell lung carcinoma tumors

Lung cancer is the principal cause of cancer-related death worldwide. The use of targeted therapies, especially tyrosine kinase inhibitors (TKIs), in specific groups of patients has dramatically improved the prognosis of this disease, although inevitably some patients will develop resistance to these drugs during active treatment. The most common cancer-associated acquired mutation is the epidermal growth factor receptor (EGFR) Thr790Met (T790M) mutation. During active treatment with targeted therapies, histopathological transformation to small-cell lung carcinoma (SCLC) can occur in 3-15% of patients with non-small-cell lung carcinoma (NSCLC) tumors. By definition, SCLC is a high-grade tumor with specific histological and genetic characteristics. In the majority of cases, a good-quality hematoxylin and eosin (H&E) stain is enough to establish a diagnosis. Immunohistochemistry (IHC) is used to confirm the diagnosis and exclude other neoplasia such as sarcomatoid carcinomas, large-cell carcinoma, basaloid squamous-cell carcinoma, chronic inflammation, malignant melanoma, metastatic carcinoma, sarcoma, and lymphoma. A loss of the tumor-suppressor protein retinoblastoma 1 (RB1) is found in 100% of human SCLC tumors; therefore, it has an essential role in tumorigenesis and tumor development. Other genetic pathways probably involved in the histopathological transformation include neurogenic locus notch homolog (NOTCH) and achaete-scute homolog 1 (ASCL1). Histological transformation to SCLC can be suspected in NSCLC patients who clinically deteriorate during active treatment. Biopsy of any new lesion in this clinical setting is highly recommended to rule out a SCLC transformation. New studies are trying to assess this histological transformation by noninvasive measures such as measuring the concentration of serum neuron-specific enolase.

Risk factors assessment and risk prediction models in lung cancer screening candidates

From February 2015, low-dose computed tomography (LDCT) screening entered the armamentarium of diagnostic tools broadly available to individuals at high-risk of developing lung cancer. While a huge number of pulmonary nodules are identified, only a small fraction turns out to be early lung cancers. The majority of them constitute a variety of benign lesions. Although it entails a burden of the diagnostic work-up, the undisputable benefit emerges from: (I) lung cancer diagnosis at earlier stages (stage shift); (II) additional findings enabling the implementation of a preventive action beyond the realm of thoracic oncology. This review presents how to utilize the risk factors from distinct categories such as epidemiology, radiology and biomarkers to target the fraction of population, which may benefit most from the introduced screening modality.

Clinical outcomes in patients with small cell lung cancer in a single institute: Comparative analysis of radiographic screening with symptom-prompted patients

OBJECTIVES

The present study was performed to evaluate the differences in clinical characteristics and survival outcomes of patients with small cell lung cancer (SCLC) according to methods used for detecting the disease: radiographic screening or symptomatically prompted.

MATERIALS AND METHODS

The clinical findings and actual treatment outcomes were estimated according to three means of detection of SCLC: computed tomography (CT), radiographic test, and symptom-prompted cases.

RESULTS

We identified 147 patients (male/female ratio: 127/20; mean age: 68.1 years old) between 2000 and 2011. The patients were divided into three categories according to method of detection: chest CT (CT; n=24), radiographic screening (CXR; n=37), and symptom-prompted cases (symptom; n=86). There was no significant shift to early TNM stage distribution in the CT or CXR group compared with the symptom group. However, the rates of limited disease (LD)-SCLC were significantly higher in the CT and CXR groups than the symptom group. Median survival times were 17.0 months (95% confidence interval (CI): 11.6-22.4) in the CT group, 19.0 months (95%CI: 11.7-126.3) in the CXR group, and 12.0 months (95%CI: 9.6-14.4) in the symptom group. There were statistically significant differences in overall survival between CT and symptom groups (P<0.05) and between CXR and symptom groups (P<0.001). However, there was no significant difference in survival between CT and CXR groups.

CONCLUSIONS

Radiographic (CT plus CXR) testing contributes to better clinical outcome in patients with SCLC.

Gene expression profiles on predicting protein interaction network and exploring of new treatments for lung cancer

In the present study, we aimed to explore disease-associated genes and their functions in lung cancer. We downloaded the gene expression profile GSE4115 from Gene Expression Omnibus (GEO) database. Total 97 lung cancer and 90 adjacent non-tumor lung tissue (normal) samples were applied to identify the differentially expressed genes (DEGs) by paired t test and variance analysis in spectral angle mapper (SAM) package in R. Gene Ontology (GO) functional enrichment analysis of DEGs were performed with Database for Annotation Visualization and Integrated Discovery, followed by construction of protein-protein interaction (PPI) network from Human Protein Reference Database (HPRD). Finally, network modules were analyzed by the MCODE algorithm to detect protein complexes in the PPI network. Total 3,102 genes were identified as DEGs at FDR < 0.05, including 1,146 down-regulated and 1,956 up-regulated DEGs. GO functional enrichment analysis revealed that up-regulated DEGs mainly participated in cell cycle and intracellular related functions, and down-regulated DEGs might influence cell functions. There were 39,240 pairs of PPIs in human obtained from HPRD databases, 3,102 DEGs were mapped to this PPI network, in which 2,429 pairs of PPIs and 1,342 genes were identified. With MCODE algorithm, 48 modules were selected, including five corresponding modules and three modules with differences in gene expressing profiles. In addition, three DGEs, FXR2, ARFGAP1 and ELAVL1 were discovered as potential lung cancer related genes. The discovery of featured genes which were probably related to lung cancer, has a great significance on studying mechanism, distinguishing normal and cancer tissues, and exploring new treatments for lung cancer.