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The discovery that protein-coding genes represent less than 2% of all human genome, and the evidence that more than 90% of it is actively transcribed, changed the classical point of view of the central dogma of molecular biology, which was always based on the assumption that RNA functions mainly as an intermediate bridge between DNA sequences and protein synthesis machinery. Accumulating data indicates that non-coding RNAs are involved in different physiological processes, providing for the maintenance of cellular homeostasis. They are important regulators of gene expression, cellular differentiation, proliferation, migration, apoptosis, and stem cell maintenance. Alterations and disruptions of their expression or activity have increasingly been associated with pathological changes of cancer cells, this evidence and the prospect of using these molecules as diagnostic markers and therapeutic targets, make currently non-coding RNAs among the most relevant molecules in cancer research. In this paper we will provide an overview of non-coding RNA function and disruption in lung cancer biology, also focusing on their potential as diagnostic, prognostic and predictive biomarkers.

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Lung cancer is the leading cause of cancer deaths worldwide, with non-small cell lung cancer (NSCLC) accounting for 80% of all lung cancers. Kirsten rat sarcoma viral oncogene homolog (KRAS) is one of the deadliest cancer-related proteins and plays a pivotal role in the most aggressive and lethal human cancers, including lung adenocarcinoma where it represents one of the most frequently mutated oncogene. Although therapeutic progresses have made an impact over the last decade, median survival for patients with advanced lung cancer remains disappointing, with a 5-year worldwide survival rate of <15%. For more than 20 years it has been recognized that constitutively active signaling downstream of KRAS is a fundamental driver of lung tumorigenesis. However, years of pursuit have failed to yield a drug that can safely curb KRAS activity; up to now no approved therapies exist for KRAS-mutant NSCLC. The aim of this review is to discuss the current knowledge of KRAS-mutated NSCLC, touching upon KRAS clinical relevance as a prognostic and predictive biomarker, with an emphasis on novel therapeutic approaches for the treatment of KRAS-variant NSCLC.

Background: Non-small cell lung cancer (NSCLC) is the primary cause of cancer-related deaths worldwide. Epidermal Growth Factor Receptor (EGFR)-mutated patients usually benefit from TKIs treatment, but a significant portion show unresponsiveness due to primary resistance mechanisms. We investigated the role of TP53 mutations in predicting survival and response to EGFR-TKIs in EGFR-mutated NSCLC patients, to confirm, on an independent case series, our previous results. Methods: An independent retrospective cohort study was conducted, on a case series of 136 EGFR-mutated NSCLC patients receiving first or second generation TKIs as a first line therapy, and a smaller fraction of patients who acquired the T790M resistance mutation and were treated with third generation TKIs in the second or further line of treatment. TP53 mutations were evaluated in relation to disease control rate (DCR), objective response rate (ORR), progression-free survival (PFS) and overall survival (OS) of the patients. Results: Forty-two patients (30.9%) showed a TP53 mutation. Considered together, TP53 mutations had no significant impact on time-to-event endpoints. Considering the different TP53 mutations separately, exon 8 mutations confirmed their negative effect on PFS (HR 3.16, 95% 1.59-6.28, p = 0.001). In patients who developed the T790M resistance mutation, treated with third generation TKIs, the TP53 exon 8 mutations predicted worse PFS (even though not statistically significant), and OS (HR 4.86, 95% CI: 1.25-18.90, p = 0.023). Conclusions: TP53 exon 8 mutations confirmed their negative prognostic impact in patients treated with first and second generation TKIs and demonstrated a role in affecting clinical outcome in patients treated with third generation TKIs.

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