Genomic Profiling of Circulating Tumor DNA from Patients with Extensive-Stage Small Cell Lung Cancer Identifies Potentially Actionable Alterations

Prognostic value of circulating tumor DNA using target next-generation sequencing in extensive-stage small-cell lung cancer

BACKGROUND

Chemotherapy remains the mainstay of treatment for small-cell lung cancer (SCLC). Liquid biopsies provide a convenient and non-invasive detection method for monitoring disease progression in patients with SCLC.

METHODS

We performed next-generation sequencing of 159 plasma samples from 69 patients with extensive-stage (ES)-SCLC. Circulating tumor (ct)DNA levels were quantified in haploid genome equivalents per mL (hGE/mL). MuTect2 was used to detect single nucleotide variants and short insertions/deletions. The "enrichKEGG" function in the "clusterProfiler" R package was used to enrich the mutated genes that only appeared during disease progression.

RESULTS

In our cohort, 66 of 69 (95.7%) plasma samples at the time of diagnosis had detectable somatic mutations; TP53 (89%) and RB1(56%) were the most frequent mutations, as well as copy number variations in some common SCLC-related genes such as RB1. Combination ctDNA and tissue testing improved the overall detection rate of actionable mutations from 19.4% to 26.9% compared with that of tissue detection alone. In addition, ctDNA levels changed dynamically during the course of treatment and were significantly associated with decreased progression-free survival. Notably, actionable mutations were detected at the time of diagnosis and during disease progression.

CONCLUSIONS

Our study revealed a dynamic somatic mutation profile through continuous ctDNA detection and confirmed that ctDNA levels can reflect tumor burden and predict PFS in patients with extensive stage-SCLC. Furthermore, we demonstrated that plasma ctDNA assays can provide real-time information on somatic mutations for potential targeted therapies for SCLC.

PI3K/AKT/mTOR pathway, hypoxia, and glucose metabolism: Potential targets to overcome radioresistance in small cell lung cancer

Small cell lung cancer (SCLC) is a highly aggressive tumor type for which limited therapeutic progress has been made. Platinum-based chemotherapy with or without thoracic radiotherapy remains the backbone of treatment, but most patients with SCLC acquire therapeutic resistance. Given the need for more effective therapies, better elucidation of the molecular pathogenesis of SCLC is imperative. The phosphoinositide 3-kinase (PI3K)/protein kinase B (AKT)/mammalian target of rapamycin (mTOR) pathway is frequently activated in SCLC and strongly associated with resistance to ionizing radiation in many solid tumors. This pathway is an important regulator of cancer cell glucose metabolism, and its activation probably effects radioresistance by influencing bioenergetic processes in SCLC. Glucose metabolism has three main branches-aerobic glycolysis, oxidative phosphorylation, and the pentose phosphate pathway-involved in radioresistance. The interaction between the PI3K/AKT/mTOR pathway and glucose metabolism is largely mediated by hypoxia-inducible factor 1 (HIF-1) signaling. The PI3K/AKT/mTOR pathway also influences glucose metabolism through other mechanisms to participate in radioresistance, including inhibiting the ubiquitination of rate-limiting enzymes of the pentose phosphate pathway. This review summarizes our understanding of links among the PI3K/AKT/mTOR pathway, hypoxia, and glucose metabolism in SCLC radioresistance and highlights promising research directions to promote cancer cell death and improve the clinical outcome of patients with this devastating disease.

Evolution of small cell lung cancer tumor mutation: from molecular mechanisms to novel viewpoints

Small cell lung cancer (SCLC) is a clinically common malignant tumor originating from the lung neuroendocrine stem cells, which has a poor prognosis and accounts for approximately 15% of all lung cancer cases. However, research on its treatment has been slow, and the 5-year survival rate of patients with SCLC has been < 5% for many years. In recent years, the development and popularization of gene sequencing technology have facilitated the understanding of the gene mutation landscape and tumor evolution of SCLC, thereby leading to a more accurate prediction of the prognosis of SCLC and the development of individualized treatment. In this review, we aimed to discuss the mutation evolution of SCLC from the perspective of a tumor evolution theory and described the sequence of mutation evolution in the occurrence and development of SCLC. In addition, we summarized the existing whole-exome sequencing (WES) data of SCLC cases at our center along with relevant publications on sequencing. Thereafter, we discuss the role of different mutated pathways in the occurrence of SCLC to predict its prognosis more accurately and summarized individualized treatment strategies.

Accurate treatment of small cell lung cancer: Current progress, new challenges and expectations

Small cell lung cancer (SCLC) is a deadly disease with poor prognosis. Fast growing speed, inclination to metastasis, enrichment in cancer stem cells altogether constitute its aggressive nature. In stark contrast to non-small cell lung cancer (NSCLC) that strides vigorously on the road to precision oncology, SCLC has been on the embryonic path to achieve effective personalized treatments. The survival of patients with SCLC have not been improved greatly, which could be possibly due to our inadequate understanding of genetic alterations of SCLC. Recently, encouraging effects have been observed in patients with SCLC undergoing immunotherapy. However, exciting results have only been observed in a small fraction of patients with SCLC, warranting biomarkers predictive of responses as well as novel therapeutic strategies. In addition, SCLC has previously been viewed to be homogeneous. However, perspectives have been changed thanks to the advances in sequencing techniques and platforms, which unfolds the complex heterogeneity of SCLC both genetically and non-genetically, rendering the treatment of SCLC a further step forward into the precision era. To outline the road of SCLC towards precision oncology, we summarize the progresses and achievements made in precision treatment in SCLC in genomic, transcriptomic, epigenetic, proteomic and metabolic dimensions. Moreover, we conclude relevant therapeutic vulnerabilities in SCLC. Clinically tested drugs and clinical trials have also been demonstrated. Ultimately, we look into the opportunities and challenges ahead to advance the individualized treatment in pursuit of improved survival for patients with SCLC.

Multi-omics data identified TP53 and LRP1B as key regulatory gene related to immune phenotypes via EPCAM in HCC

Background

Many studies showed that the prognosis of hepatocellular carcinoma (HCC) was significantly associated with the expressions of TP53 and LRP1B. However, the potential influence of the two genes on the malignant progression of HCC is still to be expounded.

Methods

According to the correlation analysis between immune cells and expression levels of TP53 and LRP1B, we filtered the immune cells to perform unsupervised clustering analysis. Integration of multi‐omic data analysis identified genetic alteration and epigenetic alteration. In addition, pathway analysis was used to explore the potential function of the differentially expressed mRNAs. According to the differentially expressed genes, we established an interaction network to seek the hub gene. Least absolute shrinkage and selection operator (LASSO) regression analysis was used to build a prognosis model.

Results

The unsupervised clustering analysis showed that the cluster A1 showed the highest immune cell levels and the cluster B2 showed the lowest immune cell levels. Multi‐omics data analysis identified that somatic mutations, copy number variations, and DNA methylation levels had significant differences between cluster A1 and cluster B2. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis found that the upregulated mRNAs in the cluster A1 were mainly concentrated in T cell activation, external side of plasma membrane, receptor ligand activity, and cytokine−cytokine receptor interaction. Importantly, the EPCAM was identified as a critical node in the lncRNAs–miRNAs–mRNAs regulatory network correlated with the immune phenotypes. In addition, based on differentially expressed genes between cluster A1 and cluster B2, the prognostic model established by LASSO could predict the overall survival (OS) of HCC accurately.

Conclusions

The results indicated that the TP53 and LRP1B acted as the key genes in regulating the immune phenotypes of HCC via EPCAM.

Genotyping guided ripretinib directly after the progression of first-line imatinib therapy in advanced gastrointestinal stromal tumor: a case report

Gastrointestinal stromal tumor (GIST) is the most common mesenchymal tumor of the gastrointestinal tract. Surgery and tyrosine kinase inhibitor (TKI) therapy are the main choices of treatment. However, the long-term use of TKIs is prone to drug resistance. Herein, we report the case of a 47-year-old female with primary gastric GIST with liver metastases since June 2015. The patient achieved disease control under imatinib therapy and underwent primary lesion resection. She took postoperative imatinib maintenance therapy, but discontinued imatinib for 10 months about 2 years after surgery. The patient suffered from disease progression in May 2019, with recurrence of liver metastases and new abdominal metastases. From then on, imatinib was resumed and partial response (PR) persisted for another 2 years. The patient subsequently experienced tumor progression due to secondary KIT exon 17 mutation confirmed by tissue biopsy and circulating tumor DNA (ctDNA) detection. After multidisciplinary team discussion, the patient received ripretinib as a second-line therapy, and ctDNA monitoring demonstrated that the KIT mutations turned negative. After disease control from ripretinib for 2+ months, she underwent cytoreductive surgery (R0/1) and received ripretinib maintenance treatment postoperatively. We believe that this case provides a reference value for individualized ripretinib precise therapy according to mutational analysis after the progression of first-line GIST treatment, and ctDNA can predict effectiveness to guide treatment.