From COVID-19 to future electrification: Assessing traffic impacts on air quality by a machine-learning model.

The large fluctuations in traffic during the COVID-19 pandemic provide an unparalleled opportunity to assess vehicle emission control efficacy. Here we develop a random-forest regression model, based on the large volume of real-time observational data during COVID-19, to predict surface-level NO2, O3, and fine particle concentration in the Los Angeles megacity. Our model exhibits high fidelity in reproducing pollutant concentrations in the Los Angeles Basin and identifies major factors controlling each species. During the strictest lockdown period, traffic reduction led to decreases in NO2 and particulate matter with aerodynamic diameters <2.5 µm by -30.1% and -17.5%, respectively, but a 5.7% increase in O3 Heavy-duty truck emissions contribute primarily to these variations. Future traffic-emission controls are estimated to impose similar effects as observed during the COVID-19 lockdown, but with smaller magnitude. Vehicular electrification will achieve further alleviation of NO2 levels.

Biological bases of cancer immunotherapy.

Immunotherapy has changed the landscape of cancer treatment and has significantly improved the outcome of several cancer types including breast, lung, colorectal and prostate. Neoantigen recognition and immune checkpoint inhibitors are nowadays the milestones of different immunotherapeutic regimes; however, high cost, primary and acquired resistance and the high variability of responses make their extensive use difficult. The development of better predictive biomarkers that represent tumour diversity shows promise because there is a significant body of clinical data showing a spectrum of immunotherapeutic responses that might be related back to their specific characteristics. This article makes a conceptual and historical review to summarise the main advances in our understanding of the role of the immune system in cancer, while describing the methodological details that have been successfully implemented on cancer treatments and that may hold the key to improved therapeutic approaches.

PUM1 and RNase P genes as potential cell-free DNA markers in breast cancer.

BACKGROUND: Cell-free DNA (cfDNA) is used in clinical research to identify biomarkers for diagnosis of and follow-up on cancer. Here, we propose a fast and innovative approach using traditional housekeeping genes as cfDNA targets in a copy number analysis. We focus on the application of highly sensitive technology such as digital PCR (dPCR) to differentiate breast cancer (BC) patients and controls by quantifying regions of PUM1 and RPPH1 (RNase P) in plasma samples. METHODS: We conducted a case-control study with 82 BC patients and 82 healthy women. cfDNA was isolated from plasma using magnetic beads and quantified by spectrophotometry to estimate total cfDNA. Then, both PUM1 and RPPH1 genes were specifically quantified by dPCR. Data analysis was calibrated using a reference genomic DNA in different concentrations. RESULTS: We found RNase P and PUM1 values were correlated in the patient group (intraclass correlation coefficient [ICC] = 0.842), but they did not have any correlation in healthy women (ICC = 0.519). In dPCR quantification, PUM1 showed the capacity to distinguish early-stage patients and controls with good specificity (98.67%) and sensitivity (100%). Conversely, RNase P had lower cfDNA levels in triple-negative BC patients than luminal subtypes (p < 0.025 for both), confirming their utility for patient classification. CONCLUSION: We propose the PUM1 gene as a cfDNA marker for early diagnosis of BC and RNase P as a cfDNA marker related to hormonal status and subtype classification in BC. Further studies with larger sample sizes are warranted.

Breast cancer mortality trends in Peruvian women.

BACKGROUND: Breast cancer (BC) is the most common malignancy in Latin American women, but with a wide variability with respect to their mortality. This study aims to estimate the mortality rates from BC in Peruvian women and to assess mortality trends over 15 years. METHODS: We calculated BC age-standardized mortality rate (ASMR) per 100,000 women-years using the world standard SEGI population. We estimated joinpoint regression models for BC in Peru and its geographical areas. The spatial analysis was performed using the Moran's I statistic. RESULTS: In a 15-year period, Peru had a mortality rate of 9.97 per 100,000 women-years. The coastal region had the highest mortality rate (12.15 per 100,000 women-years), followed by the highlands region (4.71 per 100,000 women-years). In 2003, the highest ASMR for BC were in the provinces of Lima, Arequipa, and La Libertad (above 8.0 per 100,000 women-years), whereas in 2017, the highest ASMR were in Tumbes, Callao, and Moquegua (above 13.0 per women-years). The mortality trend for BC has been declining in the coastal region since 2005 (APC = - 1.35, p < 0.05), whereas the highlands region experienced an upward trend throughout the study period (APC = 4.26, p < 0.05). The rainforest region had a stable trend. Spatial analysis showed a Local Indicator of Spatial Association of 0.26 (p < 0.05). CONCLUSION: We found regional differences in the mortality trends over 15 years. Although the coastal region experienced a downward trend, the highlands had an upward mortality trend in the entire study period. It is necessary to implement tailored public health interventions to reduce BC mortality in Peru.

Lung Cancer in the Young.

INTRODUCTION: Median age at diagnosis of lung cancer is 70 years. Its presentation in patients 40 or younger is uncommon and it has been proposed that maybe it is a different disease due to its clinical characteristics and genetic makeup. There are a limited number of studies in this population and they report different clinic-pathological characteristics in comparison with older patients. METHODS: We described the incidence of lung cancer patients diagnosed at age 40 or younger at the Instituto Nacional de Enfermedades Neoplasicas (INEN), Lima-Peru; from 2009 to 2017 and evaluated the characteristic of NSCLC. Epidemiologic and clinic-pathological data was collected from clinical files. Analysis was carried out using SPSSvs19 software. RESULTS: We identified 3823 patients with lung cancer seen at INEN during the study period. Among these, 166 (4.3%) patients were 40 years or younger, and 137/166 (82.5%) were NSCLC. Median age at diagnosis was 36 years (range 14-40 years) and 59.1% of patients were female. A smoking history was present in 14.4% of patients. Frequent symptoms at diagnosis were cough (62.0%), chest pain (51.8%) and dyspnea (40.9%). Adenocarcinoma was the most common histological type (63.3%). Most patients had advanced disease at diagnosis (84.7%). The median overall survival was 8.2 months. CONCLUSIONS: The proportion of young patients with lung cancer in our population is higher than that reported in the most recent literature. Lung cancer in the young is mostly sporadic, more frequent in women, usually adenocarcinoma type and it presents with advanced disease, resulting in a very poor survival.

Lymph node ratio as best prognostic factor in triple-negative breast cancer patients with residual disease after neoadjuvant chemotherapy.

Although lymph node status (ypN) is one of the most important prognostic factors of survival, the lymph node ratio (LNR) has emerged as an equitable factor. We aimed to compare the prognostic value of both ypN and LNR in patients with residual triple-negative breast cancer (TNBC) after neo-adjuvant chemotherapy (NAC). This was a retrospective cohort study of patients treated in a tertiary care center during the period 2000-2014. We stratified the population based on LNR (≤0.20, 0.20-0.65, and >0.65) and ypN (N1, N2, and N3) status. The overall survival (OS) and progression-free survival (PFS) were estimated with Kaplan-Meier curves and the log-rank + test. We further compared patient mortality and disease recurrence using multivariate Cox regression analysis. We evaluated 169 patients with a median follow-up of 87 months. At 2 years of follow-up, patients with low-risk LNR compared to those with moderate and high risk had a higher PFS (54% vs 31% vs 18%, respectively; P < .001) and OS (74% vs 64% vs 45%, respectively; P < .001). Moreover, ypN1 patients compared to ypN2 and ypN3 showed similar results in PFS (53% vs 35% vs 19%, respectively; P = .001) and OS (73% vs 69% vs 43%, respectively; P < .001). Compared to the low-risk population, patients with moderate (hazard ratio [HR]: 3.50; 95% confidence interval [CI]: 1.41-8.71) and high risk (HR: 6.90; 95% CI: 2.29-20.77) had a worse PFS. Regarding OS, moderate-risk (HR: 2.85; 95% CI: 1.10-7.38) and high-risk patients (HR: 6.48; 95% CI: 2.13-19.76) showed considerably worse outcomes. On the other hand, ypN staging was not associated with PFS or OS in the multivariate analysis. The LNR is a better prognostic factor of survival than ypN. The LNR should be considered in the stratification of risk after NAC in patients with TNBC.

From colorectal cancer pattern to the characterization of individuals at risk: Picture for genetic research in Latin America.

Colorectal cancer (CRC) is one of the most common cancers in Latin America and the Caribbean, with the highest rates reported for Uruguay, Brazil and Argentina. We provide a global snapshot of the CRC patterns, how screening is performed, and compared/contrasted to the genetic profile of Lynch syndrome (LS) in the region. From the literature, we find that only nine (20%) of the Latin America and the Caribbean countries have developed guidelines for early detection of CRC, and also with a low adherence. We describe a genetic profile of LS, including a total of 2,685 suspected families, where confirmed LS ranged from 8% in Uruguay and Argentina to 60% in Peru. Among confirmed LS, path_MLH1 variants were most commonly identified in Peru (82%), Mexico (80%), Chile (60%), and path_MSH2/EPCAM variants were most frequently identified in Colombia (80%) and Argentina (47%). Path_MSH6 and path_PMS2 variants were less common, but they showed important presence in Brazil (15%) and Chile (10%), respectively. Important differences exist at identifying LS families in Latin American countries, where the spectrum of path_MLH1 and path_MSH2 variants are those most frequently identified. Our findings have an impact on the evaluation of the patients and their relatives at risk for LS, derived from the gene affected. Although the awareness of hereditary cancer and genetic testing has improved in the last decade, it is remains deficient, with 39%-80% of the families not being identified for LS among those who actually met both the clinical criteria for LS and showed MMR deficiency.

First report of a KELnull phenotype in Peru and a lesson of invisible genetic disparity.

Blood banks in developing countries have limited capability to typify common blood groups creating disparities in the access to blood units for patients with rare blood genotypes. We report the case of a Peruvian woman with metastatic breast cancer with KELnull phenotype (K0), a rare blood group characterized by the lack of expression of all Kell antigens on the red blood cells (RBCs). The molecular studies identified that the patient's RBCs were homozygous for the nonsense c.1546C > T mutation predicted to encode p.Arg516Ter (KEL*02 N.17 allele), which confirmed the K0 phenotype. We conducted a local and international search of compatible blood units. Finally, the Japanese Red Cross donated the blood units for the patient. We present here the first report for a K0 phenotype in Peru and the challenging genetic disparities that many patients have to face to access to blood units in our country.

Light absorption properties and radiative effects of primary organic aerosol emissions.

Organic aerosols (OAs) in the atmosphere affect Earth's energy budget by not only scattering but also absorbing solar radiation due to the presence of the so-called "brown carbon" (BrC) component. However, the absorptivities of OAs are not represented or are poorly represented in current climate and chemical transport models. In this study, we provide a method to constrain the BrC absorptivity at the emission inventory level using recent laboratory and field observations. We review available measurements of the light-absorbing primary OA (POA), and quantify the wavelength-dependent imaginary refractive indices (kOA, the fundamental optical parameter determining the particle's absorptivity) and their uncertainties for the bulk POA emitted from biomass/biofuel, lignite, propane, and oil combustion sources. In particular, we parametrize the kOA of biomass/biofuel combustion sources as a function of the black carbon (BC)-to-OA ratio, indicating that the absorptive properties of POA depend strongly on burning conditions. The derived fuel-type-based kOA profiles are incorporated into a global carbonaceous aerosol emission inventory, and the integrated kOA values of sectoral and total POA emissions are presented. Results of a simple radiative transfer model show that the POA absorptivity warms the atmosphere significantly and leads to ∼27% reduction in the amount of the net global average POA cooling compared to results from the nonabsorbing assumption.

Toward verifying fossil fuel CO2 emissions with the CMAQ model: motivation, model description and initial simulation.

UNLABELLED: Motivated by the question of whether and how a state-of-the-art regional chemical transport model (CTM) can facilitate characterization of CO2 spatiotemporal variability and verify CO2 fossil-fuel emissions, we for the first time applied the Community Multiscale Air Quality (CMAQ) model to simulate CO2. This paper presents methods, input data, and initial results for CO2 simulation using CMAQ over the contiguous United States in October 2007. Modeling experiments have been performed to understand the roles of fossil-fuel emissions, biosphere-atmosphere exchange, and meteorology in regulating the spatial distribution of CO2 near the surface over the contiguous United States. Three sets of net ecosystem exchange (NEE) fluxes were used as input to assess the impact of uncertainty of NEE on CO2 concentrations simulated by CMAQ. Observational data from six tall tower sites across the country were used to evaluate model performance. In particular, at the Boulder Atmospheric Observatory (BAO), a tall tower site that receives urban emissions from Denver CO, the CMAQ model using hourly varying, high-resolution CO2 fossil-fuel emissions from the Vulcan inventory and Carbon Tracker optimized NEE reproduced the observed diurnal profile of CO2 reasonably well but with a low bias in the early morning. The spatial distribution of CO2 was found to correlate with NO(x), SO2, and CO, because of their similar fossil-fuel emission sources and common transport processes. These initial results from CMAQ demonstrate the potential of using a regional CTM to help interpret CO2 observations and understand CO2 variability in space and time. The ability to simulate a full suite of air pollutants in CMAQ will also facilitate investigations of their use as tracers for CO2 source attribution. This work serves as a proof of concept and the foundation for more comprehensive examinations of CO2 spatiotemporal variability and various uncertainties in the future. IMPLICATIONS: Atmospheric CO2 has long been modeled and studied on continental to global scales to understand the global carbon cycle. This work demonstrates the potential of modeling and studying CO2 variability at fine spatiotemporal scales with CMAQ, which has been applied extensively, to study traditionally regulated air pollutants. The abundant observational records of these air pollutants and successful experience in studying and reducing their emissions may be useful for verifying CO2 emissions. Although there remains much more to further investigate, this work opens up a discussion on whether and how to study CO2 as an air pollutant.

Antibody-Drug Conjugates in Breast Cancer: Toward a Molecular Perspective Into Clinical Practice.

Antibody-drug conjugates (ADCs) are at the forefront of cancer therapy, combining targeted precision with potent cytotoxicity. Conceived by Paul Ehrlich in the early 1900s, the concept of a magic bullet selectively eliminating cancer cells has evolved alongside bioengineering and cancer biology advancements. ADCs consist of a monoclonal antibody, linker, and cytotoxic payload, designed to target specific antigens on tumor cells while minimizing collateral damage. Mechanistically, ADCs are internalized via endocytosis, releasing the cytotoxic payload within the lysosome, potentially affecting neighboring tumor cells. ADC development has progressed through multiple generations, each addressing limitations of its predecessors. From gemtuzumab ozogamicin to trastuzumab emtansine (T-DM1), and now to third-generation agents such as trastuzumab deruxtecan (DS-8201) and disitamab vedotin (RC48), improvements have been made in target selectivity, potency, linker stability, and reduced off-target effects. Significant success has been seen in ADCs targeting human epidermal growth factor receptor 2 and trophoblast cell-surface antigen 2 antigens, especially in patients with breast cancer, including those resistant to previous therapies. The future of ADCs includes exploring new surface antigens, bispecific antibodies, immune-activating antibodies, radiopharmaceutical-loaded ADCs, and masked ADCs for tissue-specific activation. Ongoing research aims to optimize treatment efficacy while minimizing toxicity, expanding the potential of combination therapy. ADCs represent a promising frontier in precision cancer treatment, with continued research enhancing their potential in breast cancer and beyond. This review provides a comprehensive exploration of ADCs' evolution in breast cancer therapy, offering a molecular perspective to inform clinical practice and update colleagues on this dynamic field.

Host-Pathogen Interaction: Biology and Public Health.

Interactions between host and pathogenic microorganisms are common in nature and have a significant impact on host health, often leading to several types of infections. These interactions have evolved as a result of the ongoing battle between the host's defense mechanisms and the pathogens' invasion strategies. In this chapter, we will explore the evolution of host-pathogen interactions, explore their molecular mechanisms, examine the different stages of interaction, and discuss the development of pharmacological treatments. Understanding these interactions is crucial for improving public health, as it enables us to develop effective strategies to prevent and control infectious diseases. By gaining insights into the intricate dynamics between pathogens and their hosts, we can work towards reducing the burden of such diseases on society.

Socioeconomic disparities and the genomic landscape of gastric cancer.

The genomic characteristics of Peruvian patients with gastric adenocarcinoma from diverse socioeconomic backgrounds were examined in consideration of the possibility that patients from different socioeconomic backgrounds may be exposed to different risk factors. We conducted a prospective pilot study in two Peruvian cities (Lima and Ica). This study enrolled 15 patients from low socioeconomic status (LSES) and 15 patients from medium/high socioeconomic status (MHSES). The genomic profiling of gastric adenocarcinoma samples was done through the FoundationOne CDx platform. We compared the genomic characteristics and the need for targeted therapy and immunotherapy between LSES and MHSES. The genes with higher rates of alterations were TP53 (73.3% vs. 50.0%, P = 0.2635); CDH1 (26.7% vs. 28.6%, P = 1); CDKN2A (20.0% vs. 28.6%, P = 1); KRAS (33.3% vs. 7.1%, P = 0.1686); ARID1A (20.0% vs. 14.3%, P = 1); MLL2 (13.3% vs. 21.4%, P = 1) and SOX9 (33.3% vs. 0.0%, P = 0.0421) in LSES versus HMSES, respectively. There was no significant difference in tumor mutational burden (P = 0.377) or microsatellite status (P = 1). The LSES group had a higher need for targeted therapy or immunotherapy according to gene involvement and alterations. A significant genomic difference exists among patients with gastric adenocarcinoma of different socioeconomic status, which may result in a different need for targeted therapy and immunotherapy.

Genomic profiling of tissue and blood predicts survival outcomes in patients with resected pleural mesothelioma.

PURPOSE: Pleural mesothelioma (PM) is an aggressive tumor still considered incurable, in part due to the lack of predictive biomarkers. Little is known about the clinical implications of molecular alterations in resectable PM tissues and blood. Here, we characterized genetic alterations to identify prognostic and predictive biomarkers in patients with resected PM. EXPERIMENTAL DESIGN: Targeted next-generation sequencing was performed in retrospective pleural tumor tissue and paired plasma samples from stage IB-IIIB resected PM. Association between prognosis and presence of specific mutations was validated in silico. RESULTS: Thirty PM tissues and paired blood samples from 12 patients were analyzed. High tissue tumor mutational burden (TMB) (>10 mutations/Mb), tissue median minor allele frequency (MAF) (>9 mutations/Mb), and blood TMB (>6 mutations/Mb), tissue KMT2C, PBRM1, PKHD1,EPHB1 and blood LIFR mutations correlated with longer disease-free survival and/or overall survival. High concordance (>80%) between tissue and blood was found for some mutations. CONCLUSIONS: Tissue TMB and MAF, blood TMB, and specific mutations correlated with outcomes in patients with resected PM and should be further studied to validate their role as prognostic biomarkers and potentially predictive factors for combinations with immune-checkpoint inhibitors. This suggest that molecular profiling could identify longer survivors in patients with resected PM.

Feasibility of collagen matrix tiles with cesium-131 brachytherapy for use in the treatment of head and neck cancer.

BACKGROUND: Locoregional failure is a unique and challenging problem in head and neck cancer with controversy surrounding the use of re-irradiation in the treatment. We aimed to evaluate the dosimetry and technical parameters in utilizing a collagen matrix with embedded Cesium-131 (Cs-131) radioactive isotope seeds as it relates to dose distribution and dose to carotid artery. METHODS AND MATERIALS: Cadaveric feasibility study randomizing Cs-131 strands alone or Cs-131 with collagen matrix to be placed into neck dissection defects. For the dose computation, physicists employed the TG-43 dosimetry calculation algorithm with a point source assumption to compute the dose. Carotid arteries were contoured in MIM-Symphony software and the carotid artery maximum and mean doses were calculated in accordance with TG-43 specifications. Ease of use of collagen matrix tiles on a 7-point Likert scale and mean radiation dose to the carotid artery. RESULTS: Ease of use score was higher in collagen matrix compared to stranded seeds with a mean score of 6.3 +/- 1.2 compared to 4.5 +/- 0.87. Time of implantation was statistically significantly, p = 0.031, lower in the collagen matrix group (M = 5.17 min, SD = 4.62) compared to stranded seeds (M = 15.83 min, SD = 3.24). Mean radiation dose to the carotid artery was 62.8 Gy +/- 9.46 in the collagen matrix group compared to 108.2 Gy +/- 55.6 in the traditional Cs-131 seeds group. CONCLUSIONS: We present a feasibility and concept cadaveric study using a collagen matrix with Cesium-131 demonstrating preliminary evidence to support its ease of use, decreased time to implantation, and decreased dose delivered to the carotid artery.

Super-infection by multiple microorganisms in COVID-19 patients.

Introduction: This study aimed to describe the clinical characteristics of patients with COVID-19 co-infected with multiple multidrug-resistant bacteria. Methods: Patients hospitalized in the AUNA network between January and May 2021, diagnosed with COVID-19 and at least two other infecting microorganisms, were retrospectively included in the analysis. Clinical and epidemiological data were extracted from clinical records. The susceptibility levels of the microorganisms were determined using automated methods. Antibiotic resistance was established among infecting bacteria accounting for ≥5 isolates. Results: A total of 27 patients (21 male and 6 female patients) met the inclusion criteria, with a maximum of eight co-infecting bacteria or fungi during admission time. Seven patients (25.9%) died, with a higher but not significant lethality among women (50% vs. 19.0%). A total of 15 patients presented at least one established comorbidity, with hypertension being the most frequent. The time elapsed between COVID-19 diagnosis and hospital attendance was 7.0 days, with that of patients with a fatal outcome being longer than that of living patients (10.6 vs. 5.4). Up to 20 different microorganisms were isolated, with Pseudomonas aeruginosa being the most common (34 isolates). In general, antibiotic resistance levels were high, especially in Acinetobacter baumannii isolates, with resistance levels of 88.9% to all antimicrobial agents tested, except colistin (0%). Conclusion: In conclusion, the present results show the presence of multiple microorganisms that co-infect COVID-19 patients. When fatal outcome rates are in the range of other reports, the presence of a series of multidrug-resistant microorganisms is of concern, showing the need to reinforce control measures to limit the expansion of almost untreatable microorganisms.

Frequency of SARS-CoV-2 variants identified by real-time PCR in the AUNA healthcare network, Peru.

Introduction: In Peru, on 11 February 2023, the Ministry of Health registered 4 million patients infected with COVID-19 and around 219,260 deaths. In 2020, the SARS-CoV-2 virus was acquiring mutations that impacted the properties of transmissibility, infectivity, and immune evasion, leading to new lineages. In the present study, the frequency of COVID-19 variants was determined during 2021 and 2022 in patients treated in the AUNA healthcare network. Methods: The methodology used to detect mutations and identify variants was the Allplex™ SARS-CoV-2 Variants Assay I, II, and VII kit RT-PCR. The frequency of variants was presented by epidemiological weeks. Results: In total, 544 positive samples were evaluated, where the Delta, Omicron, and Gamma variants were identified. The Delta variant was found in 242 (44.5%) patients between epidemiological weeks 39 and 52 in 2021. In the case of Gamma, it was observed in 8 (1.5%) patients at weeks 39, 41, 43, 45, and 46 of 2021. The Omicron variant was the most frequent with 289 (53.1%) patients during weeks 49 to 52 of 2021 and 1 to 22 of 2022. During weeks 1 through 22 of 2022, it was possible to discriminate between BA. 1 (n = 32) and BA.2 (n = 82). Conclusion: The rapid identification of COVID-19 variants through the RT-PCR methodology contributes to timely epidemiological surveillance, as well as appropriate patient management.

Subpopulation treatment effect pattern plot analysis: a prognostic model for distant recurrence-free survival to estimate delayed adjuvant chemotherapy initiation effect in triple-negative breast cancer.

Introduction: Triple-negative breast cancer (TNBC) is a heterogeneous disease associated with a poor prognosis. Delaying in time to start adjuvant chemotherapy (TTC) has been related to an increased risk of distant recurrence-free survival (DRFS). We aimed to develop a prognostic model to estimate the effects of delayed TTC among TNBC risk subgroups. Materials and methods: We analyzed 687 TNBC patients who received adjuvant chemotherapy at the Instituto Nacional de Enfermedades Neoplasicas (Lima, Peru). Database was randomly divided to create a discovery set (n=344) and a validation set (n=343). Univariate and multivariate Cox regression models were performed to identify prognostic factors for DRFS. Risk stratification was implemented through two models developed based on proportional hazard ratios from significant clinicopathological characteristics. Subpopulation treatment effect pattern plot (STEPP) analysis was performed to determine the best prognostic cut-off points for stratifying TNBC subgroups according to risk scores and estimate Kaplan-Meier differences in 10-year DRFS comparing TTC (≤30 vs.>30 days). Results: In univariate analysis, patients aged ≥70 years (HR=4.65; 95% CI: 2.32-9.34; p=<0.001), those at stages pT3-T4 (HR=3.28; 95% CI: 1.57-6.83; p=0.002), and pN2-N3 (HR=3.00; 95% CI: 1.90-4.76; p=<0.001) were notably associated with higher risk. STEPP analysis defined three risk subgroups for each model. Model N°01 categorized patients into low (score: 0-31), intermediate (score:32-64), and high-risk (score: 65-100) cohorts; meanwhile, Model N°02: low (score: 0-26), intermediate (score: 27-55), and high (score: 56-100). Kaplan-Meier plots showed that in the discovery set, patients with TTC>30 days experienced a 17.5% decrease in 10-year DRFS rate (95%CI=6.7-28.3), and the impact was more remarkable in patients who belong to the high-risk subgroup (53.3% decrease in 10 years-DRFS rate). Similar results were found in the validation set. Conclusions: We developed two prognostic models based on age, pT, and pN to select the best one to classify TNBC. For Model N°02, delayed adjuvant chemotherapy conferred a higher risk of relapse in patients ≥70 years and who were characterized by pT3/T4 and pN2/N3. Thus, more efforts should be considered to avoid delayed TTC in TNBC patients, especially those in high-risk subgroups.

First report of CrpP prevalence in a South American country.

The presence of crpP was established in 201 Pseudomonas aeruginosa isolates from 9 Peruvian hospitals. The 76.6% (154/201) of the isolates presented the crpP gene. Overall, 123/201 (61.2%) isolates were non-susceptible to ciprofloxacin. The prevalence of crpP-possessing P. aeruginosa in Peru is higher than in other geographical areas.

Landscape of germline BRCA1/BRCA2 variants in breast and ovarian cancer in Peru.

Background: There is an increasing amount of data from Latin America on the characterization of BRCA variants; however, there is limited information from Peru. We conducted a retrospective study to describe germline pathogenic/likely pathogenic(P/LP) variants and variants of uncertain/unknown significance (VUS) in the BRCA1 and BRCA2 genes in Peru, in patients with breast and ovarian cancer, candidates for treatment with poly (adenosine diphosphate-ribose) polymerase (PARP) inhibitors. Methods: The patients were evaluated during the period 2019-2021. Genomic DNA was isolated from peripheral blood samples and targeted sequencing was performed using the Ampliseq BRCA panel. Genetic variant interpretation was carried out in accordance with the recommendations of the American College of Medical Genetics and ClinVar. During this period, 525 patients (143 with breast cancer and 382 with ovarian cancer) were studied. Results: We found that 14.7% (21/143) of breast cancer patients and 20.7% (79/382) of ovarian cancer patients were carriers of P/LP variants in BRCA1/2. The most frequent pathogenic variants detected in BRCA1 were c.2105dupT (BIC: 2224insT, n=12, 18.75%), c.68_69delAG (BIC: 185delAG, n=6, 9.38%), c.140G>T and c.815_824dupAGCCATGTGG (n=5, 7.81%), while in BRCA2 were c.8023A>G (n=6, 16.67%), c.6024dupG (BIC: 6252insG, n=4, 11.11%), and c.9235delG (BIC: 9463delG, n=3, 8.33%). Regarding VUS, we found that 6.99% (10/143) of breast cancer patients and 7.33% (28/382) of ovarian cancer patients were carriers of a VUS in BRCA1/2. For BRCA1, the most frequent VUS was c.93C>G (n=2), and for BRCA2, c.5465A>T (n=4), c.3101T>C (n=3), c.205C>A and c.437T>C (n=2). Conclusion: We found a frequency of 14.7% germline mutations in breast cancer patients and 20.7% in ovarian cancer patients. The most recurrent mutations were BRCA1 c.2105dupT and BRCA2 c.8023A>G. We found that BRCA2 c.8023A>G, c.6024dupG, and c.9235delG were not previously reported in Peruvian patients. BRCA1 c.2344dupA is a novel mutation that has not been previously reported in any database. The frequency of VUS in our cohort was 7.2%.