Deep Learning for the detection of microsatellite instability from histology images in colorectal cancer: a systematic literature review

Microsatellite instability (MSI) or deficient mismatch repair (dMMR) is a clinically important genetic feature affecting 10-15% of colorectal cancer (CRC) patients. Patients with metastatic MSI/dMMR CRC are eligible for therapy with immune checkpoint inhibitors, making MSI/dMMR the most important immuno-oncological biomarker in CRC. Gold standard tests for detection of MSI/dMMR in CRC are based on wet laboratory tests such as immunohistochemistry (IHC) or DNA extraction with subsequent polymerase chain reaction (PCR). However, since 2019, advances in Deep Learning (DL), an Artificial Intelligence (AI) technology, have enabled the prediction of MSI/dMMR directly from digitized routine haematoxylin and eosin (H&E) histopathology slides with high accuracy. In addition to the initial proof-of-concept publication in 2019, twelve subsequent studies have refined, improved, and further validated this approach. At this moment, MSI/dMMR prediction using Deep Learning has become a widely used benchmark task for academic studies in the field of computational pathology. Beyond academic use, this assay has attracted commercial interest from companies with the possibility of approval as a diagnostic device in the near future. In this review, we summarize and quantitatively compare the existing evidence on Deep-Learning-based detection of MSI/dMMR in CRC and discuss the need for further improvement and potential for integration into routine pathological workflows. Ultimately, this DL-based method could facilitate the identification of patients eligible for treatment with immune checkpoint inhibitors by pre-screening or replacement of current methods

BCR-ABL1 mutation development during first-line treatment with dasatinib or imatinib for chronic myeloid leukemia in chronic phase

BCR-ABL1 mutations are a common, well-characterized mechanism of resistance to imatinib as first-line treatment of chronic myeloid leukemia in chronic phase (CML-CP). Less is known about mutation development during first-line treatment with dasatinib and nilotinib, despite increased use because of higher response rates compared with imatinib. Retrospective analyses were conducted to characterize mutation development in patients with newly diagnosed CML-CP treated with dasatinib (n=259) or imatinib (n=260) in DASISION (Dasatinib versus Imatinib Study in Treatment-Naive CML-CP), with 3-year minimum follow-up. Mutation screening, including patients who discontinued treatment and patients who had a clinically relevant on-treatment event (no confirmed complete cytogenetic response (cCCyR) and no major molecular response (MMR) within 12 months; fivefold increase in BCR-ABL1 with loss of MMR; loss of CCyR), yielded a small number of patients with mutations (dasatinib, n=17; imatinib, n=18). Dasatinib patients had a narrower spectrum of mutations (4 vs 12 sites for dasatinib vs imatinib), fewer phosphate-binding loop mutations (1 vs 9 mutations), fewer multiple mutations (1 vs 6 patients) and greater occurrence of T315I (11 vs 0 patients). This trial was registered at www.clinicaltrials.gov as NCT00481247.T P Hughes, G Saglio, A Quintás-Cardama, M J Mauro, D-W Kim, J H Lipton6, M B Bradley-Garelik, J Ukropec and A Hochhau

Potential climatic transitions with profound impact on Europe

We discuss potential transitions of six climatic subsystems with large-scale impact on Europe, sometimes denoted as tipping elements. These are the ice sheets on Greenland and West Antarctica, the Atlantic thermohaline circulation, Arctic sea ice, Alpine glaciers and northern hemisphere stratospheric ozone. Each system is represented by co-authors actively publishing in the corresponding field. For each subsystem we summarize the mechanism of a potential transition in a warmer climate along with its impact on Europe and assess the likelihood for such a transition based on published scientific literature. As a summary, the ‘tipping’ potential for each system is provided as a function of global mean temperature increase which required some subjective interpretation of scientific facts by the authors and should be considered as a snapshot of our current understanding. <br/

Body Mass Index and Employment-Based Health Insurance

<p>Abstract</p> <p>Background</p> <p>Obese workers incur greater health care costs than normal weight workers. Possibly viewed by employers as an increased financial risk, they may be at a disadvantage in procuring employment that provides health insurance. This study aims to evaluate the association between body mass index [BMI, weight in kilograms divided by the square of height in meters] of employees and their likelihood of holding jobs that include employment-based health insurance [EBHI].</p> <p>Methods</p> <p>We used the 2004 Household Components of the nationally representative Medical Expenditure Panel Survey. We utilized logistic regression models with provision of EBHI as the dependent variable in this descriptive analysis. The key independent variable was BMI, with adjustments for the domains of demographics, social-economic status, workplace/job characteristics, and health behavior/status. BMI was classified as normal weight (18.5–24.9), overweight (25.0–29.9), or obese (≥ 30.0). There were 11,833 eligible respondents in the analysis.</p> <p>Results</p> <p>Among employed adults, obese workers [adjusted probability (AP) = 0.62, (0.60, 0.65)] (<it>P </it>= 0.005) were more likely to be employed in jobs with EBHI than their normal weight counterparts [AP = 0.57, (0.55, 0.60)]. Overweight workers were also more likely to hold jobs with EBHI than normal weight workers, but the difference did not reach statistical significance [AP = 0.61 (0.58, 0.63)] (<it>P </it>= 0.052). There were no interaction effects between BMI and gender or age.</p> <p>Conclusion</p> <p>In this nationally representative sample, we detected an association between workers' increasing BMI and their likelihood of being employed in positions that include EBHI. These findings suggest that obese workers are more likely to have EBHI than other workers.</p

Experimental Incubations Elicit Profound Changes in Community Transcription in OMZ Bacterioplankton

Sequencing of microbial community RNA (metatranscriptome) is a useful approach for assessing gene expression in microorganisms from the natural environment. This method has revealed transcriptional patterns in situ, but can also be used to detect transcriptional cascades in microcosms following experimental perturbation. Unambiguously identifying differential transcription between control and experimental treatments requires constraining effects that are simply due to sampling and bottle enclosure. These effects remain largely uncharacterized for “challenging” microbial samples, such as those from anoxic regions that require special handling to maintain in situ conditions. Here, we demonstrate substantial changes in microbial transcription induced by sample collection and incubation in experimental bioreactors. Microbial communities were sampled from the water column of a marine oxygen minimum zone by a pump system that introduced minimal oxygen contamination and subsequently incubated in bioreactors under near in situ oxygen and temperature conditions. Relative to the source water, experimental samples became dominated by transcripts suggestive of cell stress, including chaperone, protease, and RNA degradation genes from diverse taxa, with strong representation from SAR11-like alphaproteobacteria. In tandem, transcripts matching facultative anaerobic gammaproteobacteria of the Alteromonadales (e.g., Colwellia) increased 4–13 fold up to 43% of coding transcripts, and encoded a diverse gene set suggestive of protein synthesis and cell growth. We interpret these patterns as taxon-specific responses to combined environmental changes in the bioreactors, including shifts in substrate or oxygen availability, and minor temperature and pressure changes during sampling with the pump system. Whether such changes confound analysis of transcriptional patterns may vary based on the design of the experiment, the taxonomic composition of the source community, and on the metabolic linkages between community members. These data highlight the impressive capacity for transcriptional changes within complex microbial communities, underscoring the need for caution when inferring in situ metabolism based on transcript abundances in experimental incubations

Host Genetic Background Strongly Influences the Response to Influenza A Virus Infections

The genetic make-up of the host has a major influence on its response to combat pathogens. For influenza A virus, several single gene mutations have been described which contribute to survival, the immune response and clearance of the pathogen by the host organism. Here, we have studied the influence of the genetic background to influenza A H1N1 (PR8) and H7N7 (SC35M) viruses. The seven inbred laboratory strains of mice analyzed exhibited different weight loss kinetics and survival rates after infection with PR8. Two strains in particular, DBA/2J and A/J, showed very high susceptibility to viral infections compared to all other strains. The LD50 to the influenza virus PR8 in DBA/2J mice was more than 1000-fold lower than in C57BL/6J mice. High susceptibility in DBA/2J mice was also observed after infection with influenza strain SC35M. In addition, infected DBA/2J mice showed a higher viral load in their lungs, elevated expression of cytokines and chemokines, and a more severe and extended lung pathology compared to infected C57BL/6J mice. These findings indicate a major contribution of the genetic background of the host to influenza A virus infections. The overall response in highly susceptible DBA/2J mice resembled the pathology described for infections with the highly virulent influenza H1N1-1918 and newly emerged H5N1 viruses

Exon-Level Transcriptome Profiling in Murine Breast Cancer Reveals Splicing Changes Specific to Tumors with Different Metastatic Abilities

In breast cancer patients, tumor metastases at distant sites are the main cause of death. However, the molecular mechanisms of metastasis of breast cancer remain unclear. It is thought that changes occurring at the level of RNA processing contribute to cancer. Alternative splicing (AS) of pre-mRNA, a key post-transcriptional mechanism allowing for the production of distinct proteins from a single gene, affects over 90% of human genes. Such splicing events are responsible for generating mRNAs that encode protein isoforms that can have very different biological properties and functions. A well-studied example is the BCL-X gene, whose two major transcript isoforms produce two proteins having antagonistic functions: the short form (BCL-XS) promotes apoptosis while the long form (BCL-XL) is anti-apoptotic. Moreover, overexpression of BCL-XL has been reported to enhance the metastatic potential of breast tumor cells in patients

Genomic Sequence around Butterfly Wing Development Genes: Annotation and Comparative Analysis

, where a whole-genome BAC library allows targeted access to large genomic regions. genes. Comparative analysis with orthologous regions of the lepidopteran reference genome allowed assessment of conservation of fine-scale synteny (with detection of new inversions and translocations) and of DNA sequence (with detection of high levels of conservation of non-coding regions around some, but not all, developmental genes)., both involved in multiple developmental processes including wing pattern formation

Uncovering the Molecular Machinery of the Human Spindle—An Integration of Wet and Dry Systems Biology

The mitotic spindle is an essential molecular machine involved in cell division, whose composition has been studied extensively by detailed cellular biology, high-throughput proteomics, and RNA interference experiments. However, because of its dynamic organization and complex regulation it is difficult to obtain a complete description of its molecular composition. We have implemented an integrated computational approach to characterize novel human spindle components and have analysed in detail the individual candidates predicted to be spindle proteins, as well as the network of predicted relations connecting known and putative spindle proteins. The subsequent experimental validation of a number of predicted novel proteins confirmed not only their association with the spindle apparatus but also their role in mitosis. We found that 75% of our tested proteins are localizing to the spindle apparatus compared to a success rate of 35% when expert knowledge alone was used. We compare our results to the previously published MitoCheck study and see that our approach does validate some findings by this consortium. Further, we predict so-called “hidden spindle hub”, proteins whose network of interactions is still poorly characterised by experimental means and which are thought to influence the functionality of the mitotic spindle on a large scale. Our analyses suggest that we are still far from knowing the complete repertoire of functionally important components of the human spindle network. Combining integrated bio-computational approaches and single gene experimental follow-ups could be key to exploring the still hidden regions of the human spindle system