Rationale:Lung cancer is a series of gene-driven disease. EGFR, ALK, and ROS1 are 3 major driver genes that play an important role in lung cancer development and precision management. Additionally, rare genetic alterations continue to be discovered and may become novel targets for therapy. The RET gene is one of such rare genetic alteration of non-small cell lung cancer (NSCLC). In this report, we present a RET-positive case that benefited from cabozantinib treatment.Patient concern:A 50-year-old male patient was diagnosed with lung adenocarcinoma 2 years ago, at that time he received palliative surgery of pulmonary carcinoma and completed 4 cycles of chemotherapy with gemcitabine and cisplatin. Six months later, he was hospitalized in our cancer center due to the disease recurrence, presenting with pleural metastasis.Diagnosis:Gene alteration was examined using the intraoperative specimen by PCR method, and KIF5B/RET gene fusion was detected. Therefore, the patient was diagnosed with late-stage lung adenocarcinoma with RET gene mutation.Interventions:The patient received treatment with cabozantinib from June 2017.Outcomes:Cabozantinib was administered (140 mg orally, once daily) for approximate 9 months, and his disease achieved stable disease (SD). During that period, there were no severe adverse events (AE), except for a grade II rash (CTCAE 4.0).Lessons:We found that the RET fusion gene is a novel driver molecular of lung adenocarcinoma in patients without common mutations in such genes as EGFR, ALK, and ROS1. This case report supports a rationale for the treatment of lung adenocarcinoma patients with a RET fusion and provides alternative treatment options for these types of NSCLC patients.

Rationale:Comprehensive genomic profiling for non-small cell lung cancer (NSCLC) is likely to identify more patients with rare genetic alterations, including uncommon epidermal growth factor receptor (EGFR) gene mutation.Patient concerns:A 63-year-old Chinese woman who had never smoked visited our lung cancer clinic due to a chronic cough.Diagnosis:The patient was diagnosed with lung adenocarcinoma by transbronchial lung biopsy. An EGFR mutation (exon 20 insertion H773_V774insH, D770_N771insG, V769_D770insASV, D770_N771insSVD) was detected in the biopsy specimen by quantitative real-time PCR.Interventions:The patient was treated with osimertinib first, and the progression-free survival (PFS) was 4.4 months. After the disease progressed, the second genetic test of pleural effusion suggesting the EGFR exon 20-ins mutation site changed to A767delinsASVD only. Then the patient was treated with afatinib with informed consent.Outcomes:The treatment of afatinib in this patient was successful, PFS was 7.4 months.Lessons:To our knowledge, EGFR exon 20-ins mutation A767delinsASVD has never been reported, and the successful treatment of afatinib may provide a new therapeutic option for this type of exon 20 insertion mutations.

Backgrounds Liver hepatocellular carcinoma (HCC) is one of the most malignant tumors, of which prognosis is unsatisfactory in most cases and metastatic of HCC often results in poor prognosis. In this study, we aimed to construct a metastasis- related mRNAs prognostic model to increase the accuracy of prediction of HCC prognosis. Methods Three hundred seventy-four HCC samples and 50 normal samples were downloaded from The Cancer Genome Atlas (TCGA) database, involving transcriptomic and clinical data. Metastatic-related genes were acquired from HCMBD website at the same time. Two hundred thirty-three samples were randomly divided into train dataset and test dataset with a proportion of 1:1 by using caret package in R. Kaplan-Meier method and univariate Cox regression analysis and lasso regression analysis were performed to obtain metastasis-related mRNAs which played significant roles in prognosis. Then, using multivariate Cox regression analysis, a prognostic prediction model was established. Transcriptome and clinical data were combined to construct a prognostic model and a nomogram for OS evaluation. Functional enrichment in high- and low-risk groups were also analyzed by GSEA. An entire set based on The International Cancer Genome Consortium(ICGC) database was also applied to verify the model. The expression levels of SLC2A1, CDCA8, ATG10 and HOXD9 are higher in tumor samples and lower in normal tissue samples. The expression of TPM1 in clinical sample tissues is just the opposite. Results One thousand eight hundred ninety-five metastasis-related mRNAs were screened and 6 mRNAs were associated with prognosis. The overall survival (OS)-related prognostic model based on 5 MRGs (TPM1,SLC2A1, CDCA8, ATG10 and HOXD9) was significantly stratified HCC patients into high- and low-risk groups. The AUC values of the 5-gene prognostic signature at 1 year, 2 years, and 3 years were 0.786,0.786 and 0.777. A risk score based on the signature was a significantly independent prognostic factor (HR = 1.434; 95%CI = 1.275–1.612; P < 0.001) for HCC patients. A nomogram which incorporated the 5-gene signature and clinical features was also built for prognostic prediction. GSEA results that low- and high-risk group had an obviously difference in part of pathways. The value of this model was validated in test dataset and ICGC database. Conclusion Metastasis-related mRNAs prognostic model was verified that it had a predictable value on the prognosis of HCC, which could be helpful for gene targeted therapy.