The use of next-generation sequencing (NGS) techniques for variant detection has become increasingly important in clinical research and in clinical practice in oncology. Many cancer patients are currently being treated in clinical practice or in clinical trials with drugs directed against specific genomic alterations. In this scenario, the development of reliable and reproducible bioinformatics tools is essential to derive information on the molecular characteristics of each patient’s tumor from the NGS data. The development of bioinformatics pipelines based on the use of machine learning and statistical methods is even more relevant for the determination of complex biomarkers. In this review, we describe some important technologies, computational algorithms and models that can be applied to NGS data from Whole Genome to Targeted Sequencing, to address the problem of finding complex cancer-associated biomarkers. In addition, we explore the future perspectives and challenges faced by bioinformatics for precision medicine both at a molecular and clinical level, with a focus on an emerging complex biomarker such as homologous recombination deficiency (HRD).

Targeted sequencing of circulating cell-free DNA (cfDNA) is used in routine clinical diagnostics for the identification of predictive biomarkers in cancer patients in an advanced stage. The presence of KRAS mutations associated with clonal hematopoiesis of indeterminate potential (CHIP) might represent a confounding factor. We used an amplicon-based targeted sequencing panel, covering selected regions of 52 genes, for circulating cell-free total nucleic acid (cfTNA) analysis of 495 plasma samples from cancer patients. The cfDNA test failed in 4 cases, while circulating cell-free RNA (cfRNA) sequencing was invalid in 48 cases. In the 491 samples successfully tested on cfDNA, at least one genomic alteration was found in 222 cases (45.21%). We identified 316 single nucleotide variants (SNVs) in 21 genes. The most frequently mutated gene was TP53 (74 variants), followed by KRAS (71), EGFR (56), PIK3CA (33) and BRAF (19). Copy number variations (CNVs) were detected in 36 cases, while sequencing of cfRNA revealed 6 alterations. Analysis with droplet digital PCR (ddPCR) of peripheral blood leukocyte (PBL)-derived genomic DNA did not identify any KRAS mutations in 39 cases that showed KRAS mutations at cfDNA analysis. These findings suggest that the incidence of CHIP-associated KRAS mutations is relatively rare in routine clinical diagnostics.

Epidermal growth factor receptor (EGFR)-mutant non-small-cell lung cancer (NSCLC) patients treated with EGFR–tyrosine kinase inhibitors (TKIs) inevitably develop resistance through several biological mechanisms. However, little is known on the molecular mechanisms underlying acquired resistance to suboptimal EGFR-TKI doses, due to pharmacodynamics leading to inadequate drug exposure. To evaluate the effects of suboptimal EGFR-TKI exposure on resistance in NSCLC, we obtained HCC827 and PC9 cell lines resistant to suboptimal fixed and intermittent doses of gefitinib and compared them to cells exposed to higher doses of the drug. We analyzed the differences in terms of EGFR signaling activation and the expression of epithelial–mesenchymal transition (EMT) markers, whole transcriptomes byRNA sequencing, and cell motility. We observed that the exposure to low doses of gefitinib more frequently induced a partial EMT associated with an induced migratory ability, and an enhanced transcription of cancer stem cell markers, particularly in the HCC827 gefitinib-resistant cells. Finally, the HCC827 gefitinib-resistant cells showed increased secretion of the EMT inducer transforming growth factor (TGF)-β1, whose inhibition was able to partially restore gefitinib sensitivity. These data provide evidence that different levels of exposure to EGFR-TKIs in tumor masses might promote different mechanisms of acquired resistance.

Mechanisms of primary and acquired resistance are responsible for treatment failure with the Epidermal Growth Factor Receptor-Tyrosine Kinase Inhibitors (EGFR-TKIs) in the majority of patients with advanced Non-Small-Cell Lung Cancer (NSCLC) carrying EGFR-activating mutations. MicroRNAs (miRNAs) are important modulators of EGFR signaling in lung cancer. Recent studies suggested the role of miR-23c as a tumor suppressor or oncogenic miRNA in different tumor types. However, the role of miR-23c in NSCLC carrying EGFR mutations and its involvement in resistance to EGFR-TKIs has not been explored yet. We found that miR-23c was strongly downregulated in H1975 and HCC827-Gefitinib-Resistant (GR) NSCLC cell lines with intrinsic and acquired resistance to gefitinib, respectively, as compared to gefitinib-sensitive cell lines. Moreover, we demonstrated that miR-23c mimic inhibited proliferation, migration, invasion, and epithelial–mesenchymal transition of resistant cells and that Interleukin-6 Receptor (IL-6R) is a direct target of miR-23c in H1975 and HCC827-GR cell lines. Importantly, miR-23c mimic re-sensitized NSCLC-resistant cells to gefitinib, whereas the combination of miR-23c mimic with a neutralizing IL-6R antibody potentiated the sensitivity to the drug. Collectively, our data demonstrated that miR-23c acts as a tumor suppressor in NSCLC cell lines carrying EGFR mutations and that the axis miR-23c/IL-6R might represent a potential target for the development of therapeutic approaches to overcome resistance to gefitinib.