Budući da rak jetre ima mnogo vrsta, jako nasljeđuje i lako se vraća, identificiranje biomarkera koji mogu predvidjeti napredovanje bolesti ključni je cilj u borbi protiv raka jetre.
Nedavno su istraživači razvili metodu za identificiranje najčešćeg oblika karcinoma jetre-hepatocelularnog karcinoma (HCC) na temelju spajanja biomarkera. Oni vjeruju da se ova metoda može koristiti i za druge vrste raka. Ova studija naglašava kako varijante spajanja RNA doprinose raku i ističe da te varijante mogu postati potencijalni biomarkeri za napredovanje raka.
Spajanje se odnosi na postupak u kojem se RNA informacije kopirane iz podataka kodiranih u genu uređuju prije nego što se mogu upotrijebiti za izradu određene proteinske mape. Gen može proizvesti više RNA poruka, a svaka poruka stvara različitu varijantu proteina ili "izomer". Mnoge bolesti povezane su s pogreškama ili varijacijama u metodama spajanja RNA. Pogreške ili promjene u spajanju mogu rezultirati proteinima s različitim ili abnormalnim funkcijama.
Recent research has identified splicing irregularities in rak jetre cells. Krainer’s team has developed a method that can comprehensively analyze all RNA information produced by a given gene. The team tested their methods of detecting splice variants in HCC by analyzing RNA information from HCC cells collected from hundreds of patients.
They found that the specific splicing isoform of the AFMID gene is associated with the patient’s low survival. These variants result in cells making truncated versions of the AFMID protein. These unusual proteins are associated with mutations in TP53 and ARID1A tumor suppressor genes in adult liver cancer cells.
The researchers hypothesized that these mutations are related to the low level of a molecule called NAD +, which is involved in repairing damaged DNA. Repairing AFMID splicing may lead to increased production of NAD + and increased DNA repair. If we can do this, AFMID stitching can become a therapeutic target and a source of new drugs for liver cancer. Preliminary experiments show that the team’s research is on the right track, and we expect better data results to benefit liver cancer patients.
