Unveiling Prognostic RNA Biomarkers through a Multi-Cohort Study in Colorectal Cancer.

Because cancer is a leading cause of death and is thought to be caused by genetic errors or genomic instability in many circumstances, there have been studies exploring cancer's genetic basis using microarray and RNA-seq methods, linking gene expression data to patient survival. This research introduces a methodological framework, combining heterogeneous gene expression data, random forest selection, and pathway analysis, alongside clinical information and Cox regression analysis, to discover prognostic biomarkers. Heterogeneous gene expression data for colorectal cancer were collected from TCGA-COAD (RNA-seq), and GSE17536 and GSE39582 (microarray), and were integrated with Entrez Gene IDs. Using Cox regression analysis and random forest, genes with consistent hazard ratios and significantly affecting patient survivability were chosen. Predictive accuracy was evaluated using ROC curves. Pathway analysis identified potential RNA biomarkers. The authors identified 28 RNA biomarkers. Pathway analysis revealed enrichment in cancer-related pathways, notably EGFR downstream signaling and IGF1R signaling. Three RNA biomarkers (ZEB1-AS1, PI4K2A, and ITGB8-AS1) and two clinical biomarkers (stage and age) were chosen for a prognostic model, improving predictive performance compared to using clinical biomarkers alone. Despite biomarker identification challenges, this study underscores integration of heterogenous gene expression data for discovery.

Neurofibromatosis Symptom-Lacking B-Cell Lineage Acute Lymphoblastic Leukemia with Only an NF1 Gene Pathogenic Variant.

Next-generation sequencing technology has improved molecular genetic analysis, and many molecular genetic studies have been utilized for diagnostic classification, risk stratification, and prognosis prediction of acute lymphoblastic leukemia (ALL). Inactivation of neurofibromin or Nf1, a protein derived from the NF1 gene, causes Ras pathway regulation failure, which is related to leukemogenesis. Pathogenic variants of the NF1 gene in B-cell lineage ALL are uncommon, and in this study, we reported a pathogenic variant that is not registered in any public database. The patient diagnosed with B-cell lineage ALL had no clinical symptoms of neurofibromatosis. Studies on the biology, diagnosis, and treatment of this uncommon disease, as well as other related hematologic neoplasms, such as acute myeloid leukemia and juvenile myelomonocytic leukemia, were reviewed. Biological studies included epidemiological differences among age intervals and pathways for leukemia, such as the Ras pathway. Diagnostic studies included cytogenetic, FISH, and molecular tests for leukemia-related genes and ALL classification, such as Ph-like ALL or BCR-ABL1-like ALL. Treatment studies included pathway inhibitors and chimeric antigen cell receptor T-cells. Resistance mechanisms related to leukemia drugs were also investigated. We believe that these literature reviews will enhance medical care for the uncommon diagnosis of B-cell lineage ALL.

Coinfection with severe acute respiratory syndrome coronavirus-2 and other respiratory viruses at a tertiary hospital in Korea.

BACKGROUND: Studies have reported coinfection of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), the cause of coronavirus disease-2019 (COVID-19), with other viruses that cause respiratory tract infections (RTIs). We investigated the coinfection rate of SARS-CoV-2 and other RTI-causing viruses, and whether the cycle threshold (Ct) value of a real-time reverse transcriptase PCR (RT-PCR) differed when the coinfection occurred during the first wave of COVID-19 in Daegu, Republic of Korea, in 2020. METHODS: After performing PCR for SARS-CoV-2, we additionally tested for the presence of RTI-causing viruses to check for coinfection. Subsequently, we identified the specific coexisting respiratory viruses and calculated the coinfection rate. In addition, based on the coinfection status, we compared the Ct values obtained from RT-PCR for SARS-CoV-2 in patients who tested positive for COVID-19 PCR. RESULTS: Of 13,717 patients, 123 had positive results on COVID-19 PCR testing and six tested positive for an RTI-causing virus. Thus, the coinfection rate was 4.9%. There were no statistically significant differences in the mean Ct values of SARS-CoV-2 RT-PCR between coinfected and non-coinfected patients. CONCLUSION: This study computed the coinfection rate of SARS-CoV-2 and RTI-causing viruses and revealed that the mean Ct values in SARS-CoV-2 real-time RT-PCR did not differ according to the coinfection status.

Basophil markers for identification and activation in the indirect basophil activation test by flow cytometry for diagnosis of autoimmune urticaria.

BACKGROUND: The indirect basophil activation test using flow cytometry is a promising tool for autoimmune urticaria diagnosis. We aimed to identify better donor basophils (from atopic vs. non-atopic donors and interleukin-3 primed vs. unprimed basophils) and improve basophil identification and activation markers (eotaxin CC chemokine receptor-3 [CCR3] vs. CD123 and CD63 vs. CD203c). METHODS: Donor basophils were obtained from non-atopic and atopic group O donors. Positive control sera were artificially prepared to simulate autoimmune urticaria patients' sera. Patient sera were obtained from nine children with chronic urticaria. Assay sensitivity was compared among each variation by using positive control sera (n=21), applying cutoff values defined from negative control sera (n=20). RESULTS: For basophil identification, a combination of CCR3 and CD123 markers revealed a higher correlation with automated complete blood count (r=0.530) compared with that observed using CD123 (r=0.498) or CCR3 alone (r=0.195). Three activation markers on the atopic donor basophils attained 100% assay sensitivity: CD203c on unprimed basophils, CD63+CD203+ or CD63 alone on primed basophils; however, these markers on the non-atopic donor basophils attained lower assay sensitivity. CONCLUSIONS: For basophil identification markers, a combination of CD123 and CCR3 is recommended, while CD123 alone may be used as an alternative. Donor basophils should be obtained from an atopic donor. For basophil activation markers, either CD203c alone on unprimed basophils or CD203c and CD63 on primed basophils are recommended, while CD63 alone on primed basophils may be used as an alternative.