The recent development of imaging and sequencing technologies enables systematic advances in the clinical study of lung cancer. Meanwhile, the human mind is limited in effectively handling and fully utilizing the accumulation of such enormous amounts of data. Machine learning-based approaches play a critical role in integrating and analyzing these large and complex datasets, which have extensively characterized lung cancer through the use of different perspectives from these accrued data. In this review, we provide an overview of machine learning-based approaches that strengthen the varying aspects of lung cancer diagnosis and therapy, including early detection, auxiliary diagnosis, prognosis prediction, and immunotherapy practice. Moreover, we highlight the challenges and opportunities for future applications of machine learning in lung cancer.

Detection of circulating tumor DNA in patients with advanced non-small cell lung cancer

The voltage-gated proton channel Hv1 is a newly discovered ion channel that is highly conserved among species. It is known that Hv1 is not only expressed in peripheral immune cells but also one of the major ion channels expressed in tissue-resident microglia of the central nervous systems (CNS). One key role for Hv1 is its interaction with NADPH oxidase 2 (NOX2) to regulate reactive oxygen species (ROS) and cytosolic pH. Emerging data suggest that excessive ROS production increases and requires proton currents through Hv1 in the injured CNS, and manipulations that ablate Hv1 expression or induce loss of function may provide neuroprotection in CNS injury models including stroke, traumatic brain injury, and spinal cord injury. Recent data demonstrating microglial Hv1-mediated signaling in the pathophysiology of the CNS injury further supports the idea that Hv1 channel may function as a key mechanism in posttraumatic neuroinflammation and neurodegeneration. In this review, we summarize the main findings of Hv1, including its expression pattern, cellular mechanism, role in aging, and animal models of CNS injury and disease pathology. We also discuss the potential of Hv1 as a therapeutic target for CNS injury.

Atherosclerosis (AS) is a severe vascular disease that results in millions of cases of mortality each year. The development of atherosclerosis is associated with vascular structural lesions, characterized by the accumulation of immune cells, mesenchymal cells, lipids, and an extracellular matrix at the intimal resulting in the formation of an atheromatous plaque. AS involves complex interactions among various cell types, including macrophages, endothelial cells (ECs), and smooth muscle cells (SMCs). Endothelial dysfunction plays an essential role in the initiation and progression of AS. Endothelial dysfunction can encompass a constellation of various non-adaptive dynamic alterations of biology and function, termed “endothelial reprogramming”. This phenomenon involves transitioning from a quiescent, anti-inflammatory state to a pro-inflammatory and proatherogenic state and alterations in endothelial cell identity, such as endothelial to mesenchymal transition (EndMT) and endothelial-to-immune cell-like transition (EndIT). Targeting these processes to restore endothelial balance and prevent cell identity shifts, alongside modulating epigenetic factors, can attenuate atherosclerosis progression. In the present review, we discuss the role of endothelial cells in AS and summarize studies in endothelial reprogramming associated with the pathogenesis of AS.

Calmodulin (CaM) is a small protein that acts as a ubiquitous signal transducer and regulates neuronal plasticity, muscle contraction, and immune response. It interacts with ion channels and plays regulatory roles in cellular electrophysiology. CaM modulates the voltage-gated sodium channel gating process, alters sodium current density, and regulates sodium channel protein trafficking and expression. Many mutations in the CaM-binding IQ domain give rise to diseases including epilepsy, autism, and arrhythmias by interfering with CaM interaction with the channel. In the present review, we discuss CaM interactions with the voltage-gated sodium channel and modulators involved in CaM regulation, as well as summarize CaM-binding IQ domain mutations associated with human diseases in the voltage-gated sodium channel family.

Uncovering the functionally essential variations related to tumorigenesis and tumor progression from cancer genomics data is still challenging due to the genetic diversity among patients, and extensive inter- and intra-tumoral heterogeneity at different levels of gene expression regulation, including but not limited to the genomic, epigenomic, and transcriptional levels. To minimize the impact of germline genetic heterogeneities, in this study, we establish multiple primary cultures from the primary and recurrent tumors of a single patient with hepatocellular carcinoma (HCC). Multi-omics sequencing was performed for these cultures that encompass the diversity of tumor cells from the same patient. Variations in the genome sequence, epigenetic modification, and gene expression are used to infer the phylogenetic relationships of these cell cultures. We find the discrepancy among the relationships revealed by single nucleotide variations (SNVs) and transcriptional/epigenomic profiles from the cell cultures. We fail to find overlap between sample-specific mutated genes and differentially expressed genes (DEGs), suggesting that most of the heterogeneous SNVs among tumor stages or lineages of the patient are functionally insignificant. Moreover, copy number alterations (CNAs) and DNA methylation variation within gene bodies, rather than promoters, are significantly correlated with gene expression variability among these cell cultures. Pathway analysis of CNA/DNA methylation-related genes indicates that a single cell clone from the recurrent tumor exhibits distinct cellular characteristics and tumorigenicity, and such an observation is further confirmed by cellular experiments both in vitro and in vivo. Our systematic analysis reveals that CNAs and epigenomic changes, rather than SNVs, are more likely to contribute to the phenotypic diversity among subpopulations in the tumor. These findings suggest that new therapeutic strategies targeting gene dosage and epigenetic modification should be considered in personalized cancer medicine. This culture model may be applied to the further identification of plausible determinants of cancer metastasis and relapse.