Multiple Instance Learning for Heterogeneous Images: Training a CNN for Histopathology

Multiple instance (MI) learning with a convolutional neural network enables end-to-end training in the presence of weak image-level labels. We propose a new method for aggregating predictions from smaller regions of the image into an image-level classification by using the quantile function. The quantile function provides a more complete description of the heterogeneity within each image, improving image-level classification. We also adapt image augmentation to the MI framework by randomly selecting cropped regions on which to apply MI aggregation during each epoch of training. This provides a mechanism to study the importance of MI learning. We validate our method on five different classification tasks for breast tumor histology and provide a visualization method for interpreting local image classifications that could lead to future insights into tumor heterogeneity

Challenges in molecular testing in non-small-cell lung cancer patients with advanced disease

Lung cancer diagnostics have progressed greatly in the previous decade. Development of molecular testing to identify an increasing number of potentially clinically actionable genetic variants, using smaller samples obtained via minimally invasive techniques, is a huge challenge. Tumour heterogeneity and cancer evolution in response to therapy means that repeat biopsies or circulating biomarkers are likely to be increasingly useful to adapt treatment as resistance develops. We highlight some of the current challenges faced in clinical practice for molecular testing of EGFR, ALK, and new biomarkers such as PDL1. Implementation of next generation sequencing platforms for molecular diagnostics in non-small-cell lung cancer is increasingly common, allowing testing of multiple genetic variants from a single sample. The use of next generation sequencing to recruit for molecularly stratified clinical trials is discussed in the context of the UK Stratified Medicine Programme and The UK National Lung Matrix Trial

A clonal expression biomarker associates with lung cancer mortality

An aim of molecular biomarkers is to stratify patients with cancer into disease subtypes predictive of outcome, improving diagnostic precision beyond clinical descriptors such as tumor stage1. Transcriptomic intratumor heterogeneity (RNA-ITH) has been shown to confound existing expression-based biomarkers across multiple cancer types2,3,4,5,6. Here, we analyze multi-region whole-exome and RNA sequencing data for 156 tumor regions from 48 patients enrolled in the TRACERx study to explore and control for RNA-ITH in non-small cell lung cancer. We find that chromosomal instability is a major driver of RNA-ITH, and existing prognostic gene expression signatures are vulnerable to tumor sampling bias. To address this, we identify genes expressed homogeneously within individual tumors that encode expression modules of cancer cell proliferation and are often driven by DNA copy-number gains selected early in tumor evolution. Clonal transcriptomic biomarkers overcome tumor sampling bias, associate with survival independent of clinicopathological risk factors, and may provide a general strategy to refine biomarker design across cancer types

The T cell differentiation landscape is shaped by tumour mutations in lung cancer

Tumour mutational burden (TMB) predicts immunotherapy outcome in non-small cell lung cancer (NSCLC), consistent with immune recognition of tumour neoantigens. However, persistent antigen exposure is detrimental for T cell function. How TMB affects CD4 and CD8 T cell differentiation in untreated tumours and whether this affects patient outcomes is unknown. Here, we paired high-dimensional flow cytometry, exome, single-cell and bulk RNA sequencing from patients with resected, untreated NSCLC to examine these relationships. TMB was associated with compartment-wide T cell differentiation skewing, characterized by loss of TCF7-expressing progenitor-like CD4 T cells, and an increased abundance of dysfunctional CD8 and CD4 T cell subsets with strong phenotypic and transcriptional similarity to neoantigen-reactive CD8 T cells. A gene signature of redistribution from progenitor-like to dysfunctional states was associated with poor survival in lung and other cancer cohorts. Single-cell characterization of these populations informs potential strategies for therapeutic manipulation in NSCLC

The need for multidisciplinarity in specialist training to optimize future patient care

Harmonious interactions between radiation, medical, interventional and surgical oncologists, as well as other members of multidisciplinary teams, are essential for the optimization of patient care in oncology. This multidisciplinary approach is particularly important in the current landscape, in which standard-of-care approaches to cancer treatment are evolving towards highly targeted treatments, precise image guidance and personalized cancer therapy. Herein, we highlight the importance of multidisciplinarity and interdisciplinarity at all levels of clinical oncology training. Potential deficits in the current career development pathways and suggested strategies to broaden clinical training and research are presented, with specific emphasis on the merits of trainee involvement in functional multidisciplinary teams. Finally, the importance of training in multidisciplinary research is discussed, with the expectation that this awareness will yield the most fertile ground for future discoveries. Our key message is for cancer professionals to fulfil their duty in ensuring that trainees appreciate the importance of multidisciplinary research and practice

Global Prediction of Tissue-Specific Gene Expression and Context-Dependent Gene Networks in Caenorhabditis elegans

Tissue-specific gene expression plays a fundamental role in metazoan biology and is an important aspect of many complex diseases. Nevertheless, an organism-wide map of tissue-specific expression remains elusive due to difficulty in obtaining these data experimentally. Here, we leveraged existing whole-animal Caenorhabditis elegans microarray data representing diverse conditions and developmental stages to generate accurate predictions of tissue-specific gene expression and experimentally validated these predictions. These patterns of tissue-specific expression are more accurate than existing high-throughput experimental studies for nearly all tissues; they also complement existing experiments by addressing tissue-specific expression present at particular developmental stages and in small tissues. We used these predictions to address several experimentally challenging questions, including the identification of tissue-specific transcriptional motifs and the discovery of potential miRNA regulation specific to particular tissues. We also investigate the role of tissue context in gene function through tissue-specific functional interaction networks. To our knowledge, this is the first study producing high-accuracy predictions of tissue-specific expression and interactions for a metazoan organism based on whole-animal data

Acanthus montanus: An experimental evaluation of the antimicrobial, anti-inflammatory and immunological properties of a traditional remedy for furuncles

<p>Abstract</p> <p>Background</p> <p><it>Acanthus montanus </it>(Nees) T. Anderson (Acanthaceae) is a shrub widespread in Africa, the Balkans, Romania, Greece and Eastern Mediterranean. It is used in African traditional medicine for the treatment of urogenital infections, urethral pain, endometritis, urinary disease, cystitis, leucorrhoea, aches and pains. In southeastern Nigeria, the root is popular and acclaimed highly effective in the treatment of furuncles. This study was undertaken to experimentally evaluate the antimicrobial and anti-inflammatory properties of the root extract as well as its effect on phagocytosis and specific cell-mediated immune response which may underlie the usefulness of the roots in treatment of furuncles.</p> <p>Methods</p> <p>The aqueous root extract (obtained by hot water maceration of the root powder) was studied for effects on the growth of clinically isolated strains of <it>Pseudomonas aeruginosa </it>and <it>Staphylococcus aureus</it>. The anti-inflammatory activity was investigated using acute topical edema of the mouse ear induced by xylene, acute paw edema induced by agar in rats, formaldehyde arthritis in rats, vascular permeability induced by acetic acid in mice and heat- and hypotonicity-induced haemolysis of ox red blood cells (RBCs). Also evaluated were the effects on <it>in vivo </it>leukocyte migration induced by agar, phagocytic activity of macrophages on <it>Candida albicans </it>and specific cell-mediated immune responses (delayed type hypersensitivity reaction (DTHR) induced by sheep red blood cell (SRBC)). The acute toxicity and lethality (LD₅₀) in mice and phytochemical constituents of the extract were also determined.</p> <p>Results</p> <p>The extract moderately inhibited the growth of the test organisms and significantly (<it>P </it>< 0.05) inhibited (57%) topical acute edema in the mouse ear. It significantly (<it>P </it>< 0.05) suppressed the development of acute edema of the rat paw in a non-dose-related manner and was not effective in inhibiting the global edematous response to formaldehyde arthritis. It also inhibited vascular permeability induced by acetic acid in mice and the haemolysis of ox RBCs induced by heat- and hypotonicity. The extract increased total leukocyte and neutrophil counts and caused a significant (<it>P </it>< 0.05) dose-related increase in the total number of macrophages at the 800 mg/kg dose. On phagocytic activity, the extract evoked a significant (<it>P </it>< 0.05) increase in the number of macrophages with ingested <it>C. albicans </it>at 800 mg/kg dose, and significantly (<it>P </it>< 0.05) inhibited DTHR in a dose-related manner. Phytochemical tests on the extract revealed an abundant presence of alkaloids and carbohydrates while saponins, glycosides, and terpenoids occurred in trace amounts. Acute toxicity test established an oral and intraperitoneal LD₅₀greater than 5,000 mg/kg.</p> <p>Conclusion</p> <p>The effectiveness of the root of <it>A. montanus </it>in the treatment of furuncles may largely derive from mobilization of leukocytes to the site of the infection and activation of phagocytic activity as well as suppression of exacerbated immune responses by its constituents. Antimicrobial and anti-inflammatory activities are likely contributory mechanisms. Phytochemical constituents such as alkaloids and carbohydrates may be responsible for these pharmacological activities.</p

The evolution of lung cancer and impact of subclonal selection in TRACERx

Lung cancer is the leading cause of cancer-associated mortality worldwide1. Here we analysed 1,644 tumour regions sampled at surgery or during follow-up from the first 421 patients with non-small cell lung cancer prospectively enrolled into the TRACERx study. This project aims to decipher lung cancer evolution and address the primary study endpoint: determining the relationship between intratumour heterogeneity and clinical outcome. In lung adenocarcinoma, mutations in 22 out of 40 common cancer genes were under significant subclonal selection, including classical tumour initiators such as TP53 and KRAS. We defined evolutionary dependencies between drivers, mutational processes and whole genome doubling (WGD) events. Despite patients having a history of smoking, 8% of lung adenocarcinomas lacked evidence of tobacco-induced mutagenesis. These tumours also had similar detection rates for EGFR mutations and for RET, ROS1, ALK and MET oncogenic isoforms compared with tumours in never-smokers, which suggests that they have a similar aetiology and pathogenesis. Large subclonal expansions were associated with positive subclonal selection. Patients with tumours harbouring recent subclonal expansions, on the terminus of a phylogenetic branch, had significantly shorter disease-free survival. Subclonal WGD was detected in 19% of tumours, and 10% of tumours harboured multiple subclonal WGDs in parallel. Subclonal, but not truncal, WGD was associated with shorter disease-free survival. Copy number heterogeneity was associated with extrathoracic relapse within 1 year after surgery. These data demonstrate the importance of clonal expansion, WGD and copy number instability in determining the timing and patterns of relapse in non-small cell lung cancer and provide a comprehensive clinical cancer evolutionary data resource

Deep cell phenotyping and spatial analysis of multiplexed imaging with TRACERx-PHLEX.

The growing scale and dimensionality of multiplexed imaging require reproducible and comprehensive yet user-friendly computational pipelines. TRACERx-PHLEX performs deep learning-based cell segmentation (deep-imcyto), automated cell-type annotation (TYPEx) and interpretable spatial analysis (Spatial-PHLEX) as three independent but interoperable modules. PHLEX generates single-cell identities, cell densities within tissue compartments, marker positivity calls and spatial metrics such as cellular barrier scores, along with summary graphs and spatial visualisations. PHLEX was developed using imaging mass cytometry (IMC) in the TRACERx study, validated using published Co-detection by indexing (CODEX), IMC and orthogonal data and benchmarked against state-of-the-art approaches. We evaluated its use on different tissue types, tissue fixation conditions, image sizes and antibody panels. As PHLEX is an automated and containerised Nextflow pipeline, manual assessment, programming skills or pathology expertise are not essential. PHLEX offers an end-to-end solution in a growing field of highly multiplexed data and provides clinically relevant insights

Geospatial immune variability illuminates differential evolution of lung adenocarcinoma.

Remarkable progress in molecular analyses has improved our understanding of the evolution of cancer cells toward immune escape1-5. However, the spatial configurations of immune and stromal cells, which may shed light on the evolution of immune escape across tumor geographical locations, remain unaddressed. We integrated multiregion exome and RNA-sequencing (RNA-seq) data with spatial histology mapped by deep learning in 100 patients with non-small cell lung cancer from the TRACERx cohort6. Cancer subclones derived from immune cold regions were more closely related in mutation space, diversifying more recently than subclones from immune hot regions. In TRACERx and in an independent multisample cohort of 970 patients with lung adenocarcinoma, tumors with more than one immune cold region had a higher risk of relapse, independently of tumor size, stage and number of samples per patient. In lung adenocarcinoma, but not lung squamous cell carcinoma, geometrical irregularity and complexity of the cancer-stromal cell interface significantly increased in tumor regions without disruption of antigen presentation. Decreased lymphocyte accumulation in adjacent stroma was observed in tumors with low clonal neoantigen burden. Collectively, immune geospatial variability elucidates tumor ecological constraints that may shape the emergence of immune-evading subclones and aggressive clinical phenotypes