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Rational: LDCT screening can identify early-stage lung cancers yet introduces excessive false positives and it remains a great challenge to differentiate malignant tumors from benign solitary pulmonary nodules, which calls for better non-invasive diagnostic tools. Methods: We performed DNA methylation profiling by high throughput DNA bisulfite sequencing in tissue samples (nodule size < 3 cm in diameter) to learn methylation patterns that differentiate cancerous tumors from benign lesions. Then we filtered out methylation patterns exhibiting high background in circulating tumor DNA (ctDNA) and built an assay for plasma sample classification. Results: We first performed methylation profiling of 230 tissue samples to learn cancer-specific methylation patterns which achieved a sensitivity of 92.7% (88.3% - 97.1%) and a specificity of 92.8% (89.3% - 96.3%). These tissue-derived DNA methylation markers were further filtered using a training set of 66 plasma samples and 9 markers were selected to build a diagnostic prediction model. From an independent validation set of additional 66 plasma samples, this model obtained a sensitivity of 79.5% (63.5% - 90.7%) and a specificity of 85.2% (66.3% - 95.8%) for differentiating patients with malignant tumor (n = 39) from patients with benign lesions (n = 27). Additionally, when tested on gender and age matched asymptomatic normal individuals (n = 118), our model achieved a specificity of 93.2% (89.0% - 98.3%). Specifically, our assay is highly sensitive towards early‐stage lung cancer, with a sensitivity of 75.0% (55.0%-90.0%) in 20 stage Ia lung cancer patients and 85.7% (57.1%-100.0%) in 7 stage Ib lung cancer patients. Conclusions: We have developed a novel sensitive blood based non‐invasive diagnostic assay for detecting early stage lung cancer as well as differentiating lung cancers from benign pulmonary nodules.

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Pancreatic cancer is an increasingly common cause of cancer mortality with a tight correspondence between disease mortality and incidence. Furthermore, it is usually diagnosed at an advanced stage with a very dismal prognosis. Due to the high heterogeneity, metabolic reprogramming, and dense stromal environment associated with pancreatic cancer, patients benefit little from current conventional therapy. Recent insight into the biology and genetics of pancreatic cancer has supported its molecular classification, thus expanding clinical therapeutic options. In this review, we summarize how the biological features of pancreatic cancer and its metabolic reprogramming as well as the tumor microenvironment regulate its development and progression. We further discuss potential biomarkers for pancreatic cancer diagnosis, prediction, and surveillance based on novel liquid biopsies. We also outline recent advances in defining pancreatic cancer subtypes and subtype-specific therapeutic responses and current preclinical therapeutic models. Finally, we discuss prospects and challenges in the clinical development of pancreatic cancer therapeutics.

Dysregulated lipid metabolism represents an important metabolic alteration in cancer. Fatty acids, cholesterol, and phospholipid are the three most prevalent lipids that act as energy producers, signaling molecules, and source material for the biogenesis of cell membranes. The enhanced synthesis, storage, and uptake of lipids contribute to cancer progression. The rewiring of lipid metabolism in cancer has been linked to the activation of oncogenic signaling pathways and cross talk with the tumor microenvironment. The resulting activity favors the survival and proliferation of tumor cells in the harsh conditions within the tumor. Lipid metabolism also plays a vital role in tumor immunogenicity via effects on the function of the noncancer cells within the tumor microenvironment, especially immune‐associated cells. Targeting altered lipid metabolism pathways has shown potential as a promising anticancer therapy. Here, we review recent evidence implicating the contribution of lipid metabolic reprogramming in cancer to cancer progression, and discuss the molecular mechanisms underlying lipid metabolism rewiring in cancer, and potential therapeutic strategies directed toward lipid metabolism in cancer. This review sheds new light to fully understanding of the role of lipid metabolic reprogramming in the context of cancer and provides valuable clues on therapeutic strategies targeting lipid metabolism in cancer.