Identifying important microbial and genomic biomarkers for differentiating right- versus left-sided colorectal cancer using random forest models.

BACKGROUND: Colorectal cancer (CRC) is a heterogeneous disease, with subtypes that have different clinical behaviours and subsequent prognoses. There is a growing body of evidence suggesting that right-sided colorectal cancer (RCC) and left-sided colorectal cancer (LCC) also differ in treatment success and patient outcomes. Biomarkers that differentiate between RCC and LCC are not well-established. Here, we apply random forest (RF) machine learning methods to identify genomic or microbial biomarkers that differentiate RCC and LCC. METHODS: RNA-seq expression data for 58,677 coding and non-coding human genes and count data for 28,557 human unmapped reads were obtained from 308 patient CRC tumour samples. We created three RF models for datasets of human genes-only, microbes-only, and genes-and-microbes combined. We used a permutation test to identify features of significant importance. Finally, we used differential expression (DE) and paired Wilcoxon-rank sum tests to associate features with a particular side. RESULTS: RF model accuracy scores were 90%, 70%, and 87% with area under curve (AUC) of 0.9, 0.76, and 0.89 for the human genomic, microbial, and combined feature sets, respectively. 15 features were identified as significant in the model of genes-only, 54 microbes in the model of microbes-only, and 28 genes and 18 microbes in the model with genes-and-microbes combined. PRAC1 expression was the most important feature for differentiating RCC and LCC in the genes-only model, with HOXB13, SPAG16, HOXC4, and RNLS also playing a role. Ruminococcus gnavus and Clostridium acetireducens were the most important in the microbial-only model. MYOM3, HOXC4, Coprococcus eutactus, PRAC1, lncRNA AC012531.25, Ruminococcus gnavus, RNLS, HOXC6, SPAG16 and Fusobacterium nucleatum were most important in the combined model. CONCLUSIONS: Many of the identified genes and microbes among all models have previously established associations with CRC. However, the ability of RF models to account for inter-feature relationships within the underlying decision trees may yield a more sensitive and biologically interconnected set of genomic and microbial biomarkers.

Human gene and microbial analyses in rectal cancer complete responses to radiotherapy.

BACKGROUND: The gold standard treatment for locally advanced rectal cancer is total mesorectal excision after preoperative chemoradiotherapy. Response to chemoradiotherapy varies, with some patients completely responding to the treatment and some failing to respond at all. Identifying biomarkers of response to chemoradiotherapy could allow patients to avoid unnecessary treatment-associated morbidity rate. While previous studies have attempted to identify such biomarkers, none have reached clinical utility, which may be due to heterogeneity of the cancer. In this study, potential human gene and microbial biomarkers were explored in a cohort of rectal cancer patients who underwent chemoradiotherapy. METHODS: RNA sequencing was carried out on matched tumour and adjacent normal rectum biopsies from patients with rectal cancer with varying chemoradiotherapy responses treated between 2016 and 2019 at two institutions. Enriched genes and microbes from tumours of complete responders were compared with those from tumours of others with lesser response. RESULTS: In 39 patients analysed, enriched gene sets in complete responders indicate involvement of immune responses, including immunoglobulin production, B cell activation and response to bacteria (adjusted P values <0.050). Bacteria such as Ruminococcaceae bacterium and Bacteroides thetaiotaomicron were documented to be abundant in tumours of complete responders compared with all other patients (adjusted P value <0.100). CONCLUSION: These results identify potential genetic and microbial biomarkers of response to chemoradiotherapy in rectal cancer, as well as suggesting a potential mechanism of complete response to chemoradiotherapy that may benefit further testing in the laboratory.

Emergence of Klebsiella pneumoniae ST273 Carrying blaNDM-7 and ST656 Carrying blaNDM-1 in Manila, Philippines.

We sought to determine the epidemiology of carbapenem-resistant Enterobacteriaceae and to investigate the emergence of carbapenem-resistant Klebsiella pneumoniae in two teaching hospitals in Manila, Philippines. We screened 364 Enterobacteriaceae for carbapenem resistance between 2012 and 2013 and detected four carbapenem-resistant K. pneumoniae isolates from three different patients. We used whole genome sequencing to determine the antibiotic resistance profiles and confirmed the presence of carbapenemase genes by multiplex PCR. We used multilocus sequence typing and PCR-based replicon typing to genetically characterize the carbapenem-resistant isolates. The carbapenemase gene blaNDM was detected in K. pneumoniae isolates from two patients. The first patient had ventilator-associated pneumonia and lumbar shunt infection from K. pneumoniae ST273 carrying blaNDM-7. The second patient had asymptomatic genitourinary colonization with K. pneumoniae ST656 carrying blaNDM-1. The third patient had a gluteal abscess with K. pneumoniae ST1 that did not carry a carbapenemase gene, but did carry blaDHA-1, blaOXA-1, and blaSHV-1. In this study, we report the first cases of blaNDM-carrying pathogens in the Philippines and add to the growing evidence of the worldwide spread of ST273 and NDM-7, a more efficient carbapenem hydrolyzer than NDM-1.