Extended turnaround times and large economic costs hinder the usage of currently applied screening methods for bacterial pathogen identification (ID) and antimicrobial susceptibility testing. This review provides an overview of current detection methods and their usage in a clinical setting. Issues of timeliness and cost could soon be circumvented, however, with the emergence of detection methods involving single molecule sequencing technology. In the context of bringing diagnostics closer to the point of care, we examine the current state of Oxford Nanopore Technologies (ONT) products and their interaction with third-party software/databases to assess their capabilities for ID and antimicrobial resistance (AMR) prediction. We outline and discuss a potential diagnostic workflow, enumerating (1) rapid sample prep kits, (2) ONT hardware/software and (3) third-party software and databases to improve the cost, accuracy and turnaround times for ID and AMR. Multiple studies across a range of infection types support that the speed and accuracy of ONT sequencing is now such that established ID and AMR prediction tools can be used on its outputs, and so it can be harnessed for near real time, close to the point-of-care diagnostics in common clinical circumstances.

Background Baseline cardiovascular disease (CVD) can impact the patterns of treatment and hence the outcomes of patients with lung cancer. This study aimed to characterize treatment trends and survival outcomes of patients with pre-existing CVD prior to their diagnosis of lung cancer. Methods We conducted a retrospective, population-based cohort study of patients with lung cancer diagnosed from 2004 to 2015 in a large Canadian province. Multivariable logistic regression and Cox regression models were constructed to determine the associations between CVD and treatment patterns, and its impact on overall (OS) and cancer-specific survival (CSS), respectively. A competing risk multistate model was developed to determine the excess mortality risk of patients with pre-existing CVD. Results A total of 20,689 patients with lung cancer were eligible for the current analysis. Men comprised 55%, and the median age at diagnosis was 70 years. One-third had at least one CVD, with the most common being congestive heart failure in 15% of patients. Pre-existing CVD was associated with a lower likelihood of receiving chemotherapy (odds ratio [OR], 0.53; 95% confidence interval [CI], 0.48–0.58; P < .0001), radiotherapy (OR, 0.76; 95% CI, 0.7–0.82; P < .0001), and surgery (OR, 0.56; 95% CI, 0.44–0.7; P < .0001). Adjusting for measured confounders, the presence of pre-existing CVD predicted for inferior OS (hazard ratio [HR], 1.1; 95% CI, 1.1–1.2; P < .0001) and CSS (HR, 1.1; 95% CI, 1.1–1.1; P < .0001). However, in the competing risk multistate model that adjusted for baseline characteristics, prior CVD was associated with increased risk of non-cancer related death (HR, 1.48; 95% CI, 1.33–1.64; P < 0.0001) but not cancer related death (HR, 0.98; 95% CI, 0.94–1.03; P = 0.460). Conclusions Patients with lung cancer and pre-existing CVD are less likely to receive any modality of cancer treatment and are at a higher risk of non-cancer related deaths. As effective therapies such as immuno-oncology drugs are introduced, early cardio-oncology consultation may optimize management of lung cancer.

Colon cancer represents one of the most common cancers diagnosed in older adults worldwide. The standard of care in resected stage II and stage III colon cancer continues to evolve. While there is unequivocal evidence to suggest both disease free and overall survival benefits with the use of combination chemotherapy in patients with stage III colon cancer, data regarding its use in patients with stage II colon cancer are less clear. Further, although colon cancer is a disease that affects older adults, there is considerable debate on the value of adjuvant chemotherapy in the aging population. In particular, many older patients are undertreated when compared to their younger counterparts. In this review, we will describe the clinical trials that contributed to the current adjuvant chemotherapy approach in colon cancer, discuss representation of older adults in trials and the specific challenges associated with the management of this sub-population, and highlight the role of comprehensive geriatric assessments. We will also review how real-world evidence complements the data gaps from clinical trials of early stage colon cancer.

Contention exists within the field of oncology with regards to gastroesophageal junction (GEJ) tumors, as in the past, they have been classified as gastric cancer, esophageal cancer, or a combination of both. Misclassifications of GEJ tumors ultimately influence treatment options, which may be rendered ineffective if treating for the wrong cancer attributes. It has been suggested that misclassification rates were as high as 45%, which is greater than reported for junctional cancer occurrences. Here, we aimed to use the methylation profiles of GEJ tumors to improve classifications of GEJ tumors. Four cohorts of DNA methylation profiles, containing ~27,000 (27k) methylation sites per sample, were collected from the Gene Expression Omnibus and The Cancer Genome Atlas. Tumor samples were assigned into discovery (nEC = 185, nGC = 395; EC, esophageal cancer; GC gastric cancer) and validation (nEC = 179, nGC = 369) sets. The optimized Multi-Survival Screening (MSS) algorithm was used to identify methylation biomarkers capable of distinguishing GEJ tumors. Three methylation signatures were identified: They were associated with protein binding, gene expression, and cellular component organization cellular processes, and achieved precision and recall rates of 94.7% and 99.2%, 97.6% and 96.8%, and 96.8% and 97.6%, respectively, in the validation dataset. Interestingly, the methylation sites of the signatures were very close (i.e., 170–270 base pairs) to their downstream transcription start sites (TSSs), suggesting that the methylations near TSSs play much more important roles in tumorigenesis. Here we presented the first set of methylation signatures with a higher predictive power for characterizing gastroesophageal tumors. Thus, they could improve the diagnosis and treatment of gastroesophageal tumors.

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Background: Baseline cardiovascular disease can impact the patterns of treatment and hence the outcomes of patients with lung cancer. This study aimed to characterize treatment trends and survival outcomes of patients with pre-existing cardiovascular disease prior to their diagnosis of lung cancer.Methods: We conducted a retrospective, population-based cohort study of patients with lung cancer diagnosed from 2004 to 2015in a large Canadian province. Multivariable logistic regression and Cox regression models were constructed to determine the associations between cardiovascular disease and treatment patterns, and its impact on overall and cancer-specific survival, respectively.Results: A total of 20,689 patients with lung cancer were eligible for the current analysis. Men comprised 55%, and the median age at diagnosis was 70 years. One-third had at least one cardiovascular disease, with the most common being congestive heart failure in 15% of patients. Pre-existing cardiovascular disease was associated with a lower likelihood of receiving chemotherapy (odds ratio [OR],0.53;95% confidence interval [CI],0.48-0.58;P < .0001), radiotherapy (OR,0.76;95% CI,0.7-0.82;P < .0001), and surgery (OR, 056; 95% CI,0.44-0.7;P < .0001). Adjusting for measured confounders, the presence of pre-existing cardiovascular disease predicted for inferior OS (hazard ratio [HR], 1.1; 95% CI, 1.1-1.2; P < .0001) and CSS (HR,1.1; 95% CI, 1.1-1.1; P < .0001). Conclusions: Patients with lung cancer and pre-existing cardiovascular disease are less likely to receive any modality of cancer treatment and have poor OS and CSS. As effective therapies such as immuno-oncology drugs are introduced, early cardio-oncology consultation may optimize management and outcomes of lung cancer.

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Clinical management of papillary thyroid cancer depends on estimations of prognosis. Standard care, which relies on prognostication based on clinicopathologic features, is inaccurate. We applied a machine learning algorithm (HighLifeR) to 502 cases annotated by The Cancer Genome Atlas Project to derive an accurate molecular prognostic classifier. Unsupervised analysis of the 82 genes that were most closely associated with recurrence after surgery enabled identification of three unique molecular subtypes. One subtype had a high recurrence rate, an immunosuppressed microenvironment, and enrichment of the EZH2-HOTAIR pathway. Two other unique molecular subtypes with a lower rate of recurrence were identified, including one subtype with a paucity of BRAFV600E mutations and a high rate of RAS mutations. The genomic risk classifier, in addition to tumor size and lymph node status, enabled effective prognostication that outperformed the American Thyroid Association clinical risk stratification. The genomic classifier we derived can potentially be applied preoperatively to direct clinical decision-making. Distinct biological features of molecular subtypes also have implications regarding sensitivity to radioactive iodine, EZH2 inhibitors, and immune checkpoint inhibitors.