Person: Armisen, Ricardo
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Publication Advances in machine learning for tumour classification in cancer of unknown primary: A mini-review(2024) Oróstica, Karen; Mardones, Felipe; Bernal, Yanara; Molina, Samuel; Orchard, Marcos; Verdugo, Ricardo; Carvajal-Hausdorf, Daniel; Marcelain, Katherine; Contreras, Seba; Armisen, RicardoCancers of unknown primary (CUP) are a heterogeneous group of aggressive metastatic cancers where standardised diagnostic techniques fail to identify the organ where it originated, resulting in a poor prognosis and resistance to treatment. Recent advances in large-scale sequencing techniques have enabled the identification of mutational signatures specific to particular tumour subtypes, even from liquid biopsy samples such as blood. This breakthrough paves the way for the development of new cost-effective diagnostic strategies. This mini-review explores recent advancements in Machine Learning (ML) and its application to tumour classification methods for CUP patients, identifying its weaknesses and strengths when classifying the tumour type. In the era of multi-omics, integrating several sources of information (e.g., imaging, molecular biomarkers, and family history) requires important theoretical advancements: increasing the dimensionality of the problem can result in lowering the predictive accuracy and robustness when data is scarce. Here, we review and discuss different architectures and strategies for incorporating cutting-edge machine learning into CUP diagnosis, aiming to bridge the gap between theory and clinical practice.Publication MET Exon 14 Skipping and Novel Actionable Variants: Diagnostic and Therapeutic Implications in Latin American Non-Small-Cell Lung Cancer Patients(2024) Rivas, Solange; Sepúlveda, Romina V.; Tapia, Ignacio; Estay, Catalina; Soto, Vicente; Blanco, Alejandro; González, Evelin; Armisen, RicardoTargeted therapy indications for actionable variants in non-small-cell lung cancer (NSCLC) have primarily been studied in Caucasian populations, with limited data on Latin American patients. This study utilized a 52-genes next-generation sequencing (NGS) panel to analyze 1560 tumor biopsies from NSCLC patients in Chile, Brazil, and Peru. The RNA sequencing reads and DNA coverage were correlated to improve the detection of the actionable MET exon 14 skipping variant (METex14). The pathogenicity of MET variants of uncertain significance (VUSs) was assessed using bioinformatic methods, based on their predicted driver potential. The effects of the predicted drivers VUS T992I and H1094Y on c-MET signaling activation, proliferation, and migration were evaluated in HEK293T, BEAS-2B, and H1993 cell lines. Subsequently, c-Met inhibitors were tested in 2D and 3D cell cultures, and drug affinity was determined using 3D structure simulations. The prevalence of MET variants in the South American cohort was 8%, and RNA-based diagnosis detected 27% more cases of METex14 than DNA-based methods. Notably, 20% of METex14 cases with RNA reads below the detection threshold were confirmed using DNA analysis. The novel actionable T992I and H1094Y variants induced proliferation and migration through c-Met/Akt signaling. Both variants showed sensitivity to crizotinib and savolitinib, but the H1094Y variant exhibited reduced sensitivity to capmatinib. These findings highlight the importance of RNA-based METex14 diagnosis and reveal the drug sensitivity profiles of novel actionable MET variants from an understudied patient populationPublication Methylated Reprimo Cell-Free DNA as a Non-Invasive Biomarker for Gastric Cancer(2025) Maturana, María; Padilla, Oslando; Santoro, Pablo; Alarcón, Maria; Olivares, Wilda; Blanco, Alejandro; Armisen, Ricardo; Garrido, Marcelo; Aravena, Edmundo; Barrientos, Carlos; Calvo, Alfonso; Corvalán, AlejandroRestrictions resulting from the COVID-19 pandemic abruptly reversed the slow decline of the diagnosis and mortality rates of gastric cancer (GC). This scenario highlights the importance of developing cost-effective methods for mass screening and evaluation of treatment response. In this study, we evaluated a non-invasive method based on the circulating methylated cell-free DNA (cfDNA) of Reprimo (RPRM), a tumor suppressor gene associated with the development of GC. Methylated RPRM cfDNA was analyzed in three de-identified cohorts: Cohort 1 comprised 81 participants with GC and 137 healthy donors (HDs); Cohort 2 comprised 27 participants with GC undergoing gastrectomy and/or chemotherapy analyzed at the beginning and after three months of treatment; and Cohort 3 comprised 1105 population-based participants in a secondary prevention program who underwent esophagogastroduodenal (EGD) endoscopy. This cohort includes 180 normal participants, 845 participants with premalignant conditions (692 with chronic atrophic gastritis [AG] and 153 with gastric intestinal metaplasia/low-grade dysplasia [GIM/LGD]), 21 with high-grade dysplasia/early GC [HGD/eGC], and 59 with advanced GC [aGC]). A nested case-control substudy was performed using a combination of methylated RPRM cfDNA and pepsinogens (PG)-I/II ratio. The dense CpG island of the promoter region of the RPRM gene was bisulfite sequenced and analyzed to develop a fluorescence-based real-time PCR assay (MethyLight). This assay allows the determination of the absolute number of copies of methylated RPRM cfDNA. A targeted sequence of PCR amplicon products confirmed the gastric origin of the plasma-isolated samples. In Cohort 1, the mean value of GCs (32,240.00 copies/mL) was higher than that of the HD controls (139.00 copies/mL) (p < 0.0001). After dividing this cohort into training–validation subcohorts, we identified an area under the curve of 0.764 (95% confidence interval (CI) = 0.683–0.845) in the training group. This resulted in a cut-off value of 87.37 copies/mL (sensitivity 70.0% and specificity 80.2%). The validation subcohort predicted sensitivity of 66.67% and a specificity of 83.33%. In Cohort 2 (monitoring treatment response), RPRM levels significantly decreased in responders (p = 0.0042) compared to non-responders. In Cohort 3 (population-based participants), 18.9% %, 24.1%, 30.7%, 47.0%, and 71.2% of normal, AG, GIM/LGD, HGD/eGC, and aGC participants tested positive for methylated RPRM cfDNA, respectively. Overall sensitivity and specificity in distinguishing normal/premalignant conditions vs. GC were 65.0% (95% CI 53.52% to 75.33%) and 75.9% (95% CI 73.16% to 78.49%), respectively, with an accuracy of 75.11% (95% CI 72.45% to 77.64%). Logistic regression analyses revealed an OR of 1.85 (95% CI 1.11–3.07, p = 0.02) and an odds ratio (OR) of 3.9 (95% CI 1.53–9.93, p = 0.004) for the risk of developing GIM/LGD and HGD/eGC, respectively. The combined methylated RPRM cfDNA and PG-I/II ratio reached a sensitivity of 78.9% (95% CI 54.43% to 93.95%) and specificity of 63.04% (95% CI 52.34% to 72.88%) for detecting HGD/eGC vs. three to six age- and sex-matched participants with premalignant conditions. Our results demonstrate that methylated RPRM cfDNA should be considered a direct biomarker for the non-invasive detection of GC and a predictive biomarker for treatment response.Publication Predator-Prey Model for Simulating the Genetic Carcinogenicity of Aggressive Toxicant-Related Cancer(2025) Fernández, Mauricio; Armisen, Ricardo; Fernández Arancibia, MarioThe mechanism of how toxicant exposure leads to aggressive tumors remains unresolved. A genetic-based hypothesis predicts that under stress, the transcription of growth-related genes will be inhibited by the activation of mitogenic pathways, redirecting energy toward stress response and increasing survival. This hypothesis fails to explain why epidemiological data suggest that growth and stress response are activated, as patients exposed to toxicants exhibit more aggressive growth than nonexposed individuals. This co-occurrence requires increased energy availability to prevent the activation of mitogenic pathways, as seen in the Warburg effect. We hypothesize that if pollutant effects cease, it might drive aggressive cancer, as excess energy that is no longer used for stress response can fuel rapid growth. We model this allocation between growth and stress response as a trophic competition using the Lotka-Volterra equations and using as input RNA-Seq data from growth- and stress-related genes obtained from cancer cells exposed to copper, cadmium, and carboplatin. Our findings suggest that the energy allocation to growth and its rate of allocation is higher in exposed than nonexposed tumors and results in overgrowth in unexposed cells. This study helps to understand how certain scenarios, such as partial or total cessation of exposure, in toxicant-related cancer can drive cancer aggressiveness.