New research has revealed that lung cancer growth can be reduced by 40 to 50% in a mouse model using downregulation of noncoding RNA activity. The research, published in Nature Communications earlier this week, was conducted at the Sahlgrenska Academy, a part of the University of Gothenburg, Sweden.

The National Cancer Institute estimates that, in the last year, lung cancer has caused roughly 26% of all cancer deaths and accounts for 13% of new cancer diagnoses in the US alone. The prevalence of the disease has encouraged large amounts of research into possible treatments and cures for the condition. One such study was carried out by researchers at Sahlgrenska Academy, who were investigating the role of long noncoding RNA (lncRNA) in the development of tumours.

The majority of RNA in a cell is involved in transcribing and translating DNA, and protein biosynthesis, but there isn’t always the case. Some RNA molecules are known as noncoding, and do not appear to be involved in the protein synthesis pathway. Initially, researchers thought that these RNA molecules may be inactive, but subsequent work has demonstrated that they seem to be involved in cell division.

Because of their role in cell division, the Swedish team hoped to investigate what link may be present between lncRNA and lung cancer tumour growth. To do so, the team analysed 6,419 solid tumours that accounted for 16 different types of cancer and 701 healthy tissue sample controls using RNA sequencing.

“Since there is a strong link between cell division cycle and cancer, we are using it as the basis for identifying the important long noncoding RNA molecules that play a key role in cancer growth,” said Chandrasekhar Kanduri, lead researcher  of the study and Professor of Medical Biochemistry and Cell Biology at the Academy, when speaking with MedicalNewsToday. “Higher expression of some of these long noncoding RNA molecules during the cell division cycle may cause cells to divide uncontrollably to become cancerous.”

Through this approach, the team identified 570 lncRNA molecules that were expressed differently in healthy and cancerous tissues. Further, they were able to uncover 633 previously unknown biomarkers that could act as predictive tools for 14 cancer types.

The team then used this knowledge to try to treat mice that had been grafted with human lung cancer tissue. They injected each mouse with an agent that blocked the activity of the relevant lnRNA (locked nucleic acid antisense oligonucleotides) twice a week and examined the effects to the tumours. They found that within 15 days, their treatment had led to a tumour size reduction of almost 50%.

“Thus we have identified a new method, optimized it in a lab environment, and identified long noncoding RNA molecules that are involved in uncontrolled cell division,” Kanduri told MNT. “By taking aim at these specific molecules, we have reduced cancer growth. Furthermore, the molecules can also be used to predict the disease.”

While this research is still in the early phases, the team hope that their work will ultimately aid the development of more effective treatments for lung cancer.

“Based on these observations, we suggest that a combinatorial treatment strategy involving SCAT7 repression alongside treatment with potent FGFRs inhibitors or TKIs will hold promise for lncRNA-based therapeutics,” the authors concluded. “Collectively, we provide a comprehensive list of lncRNA-based oncogenic drivers with potential prognostic value. More importantly, this systematically analyzed functional and clinically relevant lncRNAs can serve as a resource for delineating the functional link between lncRNA and tumor development and progression.”