Coordinated inheritance of extrachromosomal DNAs in cancer cells.

The chromosomal theory of inheritance dictates that genes on the same chromosome segregate together while genes on different chromosomes assort independently. Extrachromosomal DNAs (ecDNAs) are common in cancer and drive oncogene amplification, dysregulated gene expression and intratumoural heterogeneity through random segregation during cell division. Distinct ecDNA sequences, termed ecDNA species, can co-exist to facilitate intermolecular cooperation in cancer cells.

Analysis of the immune landscape in virus-induced cancers using a novel integrative mechanism discovery approach.

Background: The mechanisms of carcinogenesis from viral infections are extraordinarily complex and not well understood. Traditional methods of analyzing RNA-sequencing data may not be sufficient for unraveling complicated interactions between viruses and host cells. Using RNA and DNA-sequencing data from The Cancer Genome Atlas (TCGA), we aim to explore whether virus-induced tumors exhibit similar immune-associated (IA) dysregulations using a new algorithm we developed that focuses on the most important biological mechanisms involved in virus-induced cancers.

The intratumor microbiome predicts prognosis across gender and subtypes in papillary thyroid carcinoma.

While the intratumor microbiome has become increasingly implicated in cancer development, the microbial landscape of papillary thyroid carcinoma (PTC) is essentially uninvestigated. PTC is characterized by varied prognosis between gender and cancer subtype, but the cause for gender and subtype-based dissimilarities is unclear. Women are more frequently diagnosed with PTC, while men suffer more advanced-staged PTC.

Using machine learning of clinical data to diagnose COVID-19: a systematic review and meta-analysis.

Background: The recent Coronavirus Disease 2019 (COVID-19) pandemic has placed severe stress on healthcare systems worldwide, which is amplified by the critical shortage of COVID-19 tests.

Methods: In this study, we propose to generate a more accurate diagnosis model of COVID-19 based on patient symptoms and routine test results by applying machine learning to reanalyzing COVID-19 data from 151 published studies. We aim to investigate correlations between clinical variables, cluster COVID-19 patients into subtypes, and generate a computational classification model for discriminating between COVID-19 patients and influenza patients based on clinical variables alone.

The Pancreatic Microbiome is Associated with Carcinogenesis and Worse Prognosis in Males and Smokers.

An intra-pancreatic microbiota was recently discovered in several prominent studies. Since pancreatic adenocarcinoma (PAAD) is one of the most lethal cancers worldwide, and the intratumor microbiome was found to be a significant contributor to carcinogenesis in other cancers, this study aims to characterize the PAAD microbiome and elucidate how it may be associated with PAAD prognosis. We further explored the association between the intra-pancreatic microbiome and smoking and gender, which are both risk factors for PAAD.

Influence of Intratumor Microbiome on Clinical Outcome and Immune Processes in Prostate Cancer.

Although 1 in 9 American men will receive a diagnosis of prostate cancer (PC), most men with this diagnosis will not die from it, as most PCs are indolent. However, there is a subset of patients in which the once-indolent PC becomes metastatic and eventually, fatal. In this study, we analyzed microbial compositions of intratumor bacteria in PC to determine the influence of the microbiome on metastatic growth.