Acute lymphoblastic leukemia (ALL) is a hematological disease characterized by the dysfunction of the hematopoietic system that leads to arrest at a specific stage of stem cells development, suppressing the average production of cellular hematologic components. BCP-ALL is a neoplasm of the B-cell lineage progenitor. BCP-ALL is caused and perpetuated by several mechanisms that provide the disease with its tumor potential and genetic and cytological characteristics. These pathological features are used for diagnosis and the prognostication of BCP-ALL. However, most of these paraclinical tools can only be obtained by bone marrow aspiration, which, as it is an invasive study, can delay the diagnosis and follow-up of the disease, in addition to the anesthetic risk it entails for pediatric patients. For this reason, it is crucial to find noninvasive and accessible ways to supply information concerning diagnosis, prognosis, and the monitoring of the disease, such as circulating biomarkers. In oncology, a biomarker is any measurable indicator that demonstrates the presence of malignancy, tumoral behavior, prognosis, or responses to treatments. This review summarizes circulating molecules associated with BCP-ALL with potential diagnostic value, classificatory capacity during monitoring specific clinic features of the disease, and/or capacity to identify each BCP-ALL stage regarding its evolution and outcome of the patients with BCP-ALL. In the same way, we provide and classify biomarkers that may be used in further studies focused on clinical approaches or therapeutic target identification for BCP-ALL.

Chronic hyperglycemia increases the risk of developing severe COVID-19 symptoms, but the related mechanisms are unclear. A mean glucose level upon hospital admission >166 mg/dl correlates positively with acute respiratory distress syndrome in patients with hyperglycemia. The objective of this study was to evaluate the relationship between sustained hyperglycemia and the outcome of hospitalized patients with severe COVID-19. We also evaluated the effect of high glucose concentrations on the expression of angiotensin-converting enzyme 2 (ACE2). We carried out a case-control study with hospitalized patients with severe COVID-19 with and without sustained hyperglycemia. In a second stage, we performed in vitro assays evaluating the effects of high glucose concentrations on ACE2 gene expression. Fifty hospitalized patients with severe COVID-19 were included, of which 28 (56%) died and 22 (44%) recovered. Patients who died due to COVID-19 and COVID-19 survivors had a high prevalence of hyperglycemia (96.4% versus 90.9%), with elevated central glucose upon admission (197.7 mg/dl versus 155.9 mg/dl, p = 0.089) and at discharge (185.2 mg/dl versus 134 mg/dl, p = 0.038). The mean hypoxemia level upon hospital admission was 81% in patients who died due to COVID-19 complications and 88% in patients who survived (p = 0.026); at the time of discharge, hypoxemia levels were also different between the groups (68% versus 92%, p ≤ 0.001). In vitro assays showed that the viability of A549 cells decreased (76.41%) as the glucose concentration increased, and the ACE2 gene was overexpressed 9.91-fold after 72 h (p ≤ 0.001). The relationship between hyperglycemia and COVID-19 in hospitalized patients with COVID-19 plays an important role in COVID-19-related complications and the outcome for these patients. In patients with chronic and/or sustained hyperglycemia, the upregulation of ACE2, and its potential glycation and malfunction, could be related to complications observed in patients with COVID-19.

SARS-CoV-2 is the etiological agent of COVID-19 and may evolve from asymptomatic disease to fatal outcomes. Real-time reverse-transcription polymerase chain reaction (RT-PCR) screening is the gold standard to diagnose severe accurate respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, but this test is not 100% accurate, as false negatives can occur. We aimed to evaluate the potential false-negative results in hospitalized patients suspected of viral respiratory disease but with a negative previous SARS-CoV-2 RT-PCR and analyze variables that may increase the success of COVID-19 diagnosis in this group of patients. A total of 55 hospitalized patients suspected of viral respiratory disease but with a previous negative RT-PCR result for SARS-CoV-2 were included. All the participants had clinical findings related to COVID-19 and underwent a second SARS-CoV-2 RT-PCR. Chest-computed axial tomography (CT) was used as an auxiliary tool for COVID-19 diagnosis. After the second test, 36 patients (65.5%) were positive for SARS-CoV-2 (COVID-19 group), and 19 patients (34.5%) were negative (controls). There were differences between the groups in the platelet count and the levels of D-dimer, procalcitonin, and glucose (p < 0.05). Chest CT scans categorized as COVID-19 Reporting and Data System 5 (CO-RADS 5) were more frequent in the COVID-19 group than in the control group (91.7% vs. 52.6%; p = 0.003). CO-RADS 5 remained an independent predictor of COVID-19 diagnosis in a second SARS-CoV-2 screening (p = 0.013; odds ratio = 7.0, 95% confidence interval 1.5–32.7). In conclusion, chest CT classified as CO-RADS 5 was an independent predictor of a positive second SARS-CoV-2 RT-PCR, increasing the odds of COVID-19 diagnosis by seven times. Based on our results, in hospitalized patients with a chest CT classified as CO-RADS 5, a second SARS-CoV-2 RT-PCR test should be mandatory when the first one is negative. This approach could increase SARS-CoV-2 detection up to 65% and could allow for isolation and treatment, thus improving the patient outcome and avoiding further contagion.