Early Detection of Lung Cancer Using Small RNAs.

INTRODUCTION: Lung cancer remains the deadliest cancer in the world, and lung cancer survival is heavily dependent on tumor stage at the time of detection. Low-dose computed tomography screening can reduce mortality; however, annual screening is limited by low adherence in the United States of America and still not broadly implemented in Europe. As a result, less than 10% of lung cancers are detected through existing programs. Thus, there is a great need for additional screening tests, such as a blood test, that could be deployed in the primary care setting. METHODS: We prospectively recruited 1384 individuals meeting the National Lung Screening Trial demographic eligibility criteria for lung cancer and collected stabilized whole blood to enable the pipetting-free collection of material, thus minimizing preanalytical noise. Ultra-deep small RNA sequencing (20 million reads per sample) was performed with the addition of a method to remove highly abundant erythroid RNAs, and thus open bandwidth for the detection of less abundant species originating from the plasma or the immune cellular compartment. We used 100 random data splits to train and evaluate an ensemble of logistic regression classifiers using small RNA expression of 943 individuals, discovered an 18-small RNA feature consensus signature (miLung), and validated this signature in an independent cohort (441 individuals). Blood cell sorting and tumor tissue sequencing were performed to deconvolve small RNAs into their source of origin. RESULTS: We generated diagnostic models and report a median receiver-operating characteristic area under the curve of 0.86 (95% confidence interval [CI]: 0.84-0.86) in the discovery cohort and generalized performance of 0.83 in the validation cohort. Diagnostic performance increased in a stage-dependent manner ranging from 0.73 (95% CI: 0.71-0.76) for stage I to 0.90 (95% CI: 0.89-0.90) for stage IV in the discovery cohort and from 0.76 to 0.86 in the validation cohort. We identified a tumor-shed, plasma-bound ribosomal RNA fragment of the L1 stalk as a dominant predictor of lung cancer. The fragment is decreased after surgery with curative intent. In additional experiments, results of dried blood spot collection and sequencing revealed that small RNA analysis could potentially be conducted through home sampling. CONCLUSIONS: These data suggest the potential of a small RNA-based blood test as a viable alternative to low-dose computed tomography screening for early detection of smoking-associated lung cancer.

An unusual case of phytobezoar-induced small bowel obstruction.

Bezoars, and to lesser extent phytobezoars, are among the rare causes of small bowel obstruction. A bezoar generally describes retained concretions of indigestible foreign material that accumulate and conglomerate in the gastrointestinal tract, most commonly in the stomach. We present an unusual case of phytobezoar-induced sub-acute small bowel obstruction originating from unfamiliar plant material in a 74-year-old woman. The past history was insignificant regarding comorbidities other than depression. Presenting complaints were history of abdominal pain and vomiting. Imaging studies and physical examination suggested small bowel obstruction. The patient underwent exploratory laparotomy after 1 day of conservative treatment. We found a 4.5 cm obstructing phytobezoar intraoperatively. The undigested plant material caused the obstruction. Postoperatively, the plant was identified as Scorzonera papposa. The patient was discharged uneventfully. The elderly patients should avoid semi-cooked vegetables, plants of unknown origin and high-fibre diet.