All cancers are caused by somatic mutations; however, understanding of the biological processes generating these mutations is limited. The catalogue of somatic mutations from a cancer genome bears the signatures of the mutational processes that have been operative. Here we analysed 4,938,362 mutations from 7,042 cancers and extracted more than 20 distinct mutational signatures. Some are present in many cancer types, notably a signature attributed to the APOBEC family of cytidine deaminases, whereas others are confined to a single cancer class. Certain signatures are associated with age of the patient at cancer diagnosis, known mutagenic exposures or defects in DNA maintenance, but many are of cryptic origin. In addition to these genome-wide mutational signatures, hypermutation localized to small genomic regions, 'kataegis', is found in many cancer types. The results reveal the diversity of mutational processes underlying the development of cancer, with potential implications for understanding of cancer aetiology, prevention and therapy.

/pdf/signatures-of-mutational-processes-in-human-cancer-j3duru54oq.pdf

Signatures of mutational processes in human cancer

BackgroundSomatic mutations have the potential to encode “non-self” immunogenic antigens. We hypothesized that tumors with a large number of somatic mutations due to mismatch-repair defects may be susceptible to immune checkpoint blockade. MethodsWe conducted a phase 2 study to evaluate the clinical activity of pembrolizumab, an anti–programmed death 1 immune checkpoint inhibitor, in 41 patients with progressive metastatic carcinoma with or without mismatch-repair deficiency. Pembrolizumab was administered intravenously at a dose of 10 mg per kilogram of body weight every 14 days in patients with mismatch repair–deficient colorectal cancers, patients with mismatch repair–proficient colorectal cancers, and patients with mismatch repair–deficient cancers that were not colorectal. The coprimary end points were the immune-related objective response rate and the 20-week immune-related progression-free survival rate. ResultsThe immune-related objective response rate and immune-related progression-free survival ...

/pdf/pd-1-blockade-in-tumors-with-mismatch-repair-deficiency-1eb0ztv7j7.pdf

PD-1 Blockade in Tumors with Mismatch-Repair Deficiency

The Cancer Genome Atlas (TCGA) Research Network has profiled and analyzed large numbers of human tumors to discover molecular aberrations at the DNA, RNA, protein and epigenetic levels. The resulting rich data provide a major opportunity to develop an integrated picture of commonalities, differences and emergent themes across tumor lineages. The Pan-Cancer initiative compares the first 12 tumor types profiled by TCGA. Analysis of the molecular aberrations and their functional roles across tumor types will teach us how to extend therapies effective in one cancer type to others with a similar genomic profile.

/pdf/the-cancer-genome-atlas-pan-cancer-analysis-project-gw3srsikvs.pdf

The cancer genome atlas pan-cancer analysis project

Infiltrating stromal and immune cells form the major fraction of normal cells in tumour tissue and not only perturb the tumour signal in molecular studies but also have an important role in cancer biology. Here we describe 'Estimation of STromal and Immune cells in MAlignant Tumours using Expression data' (ESTIMATE)--a method that uses gene expression signatures to infer the fraction of stromal and immune cells in tumour samples. ESTIMATE scores correlate with DNA copy number-based tumour purity across samples from 11 different tumour types, profiled on Agilent, Affymetrix platforms or based on RNA sequencing and available through The Cancer Genome Atlas. The prediction accuracy is further corroborated using 3,809 transcriptional profiles available elsewhere in the public domain. The ESTIMATE method allows consideration of tumour-associated normal cells in genomic and transcriptomic studies. An R-library is available on https://sourceforge.net/projects/estimateproject/.

/pdf/inferring-tumour-purity-and-stromal-and-immune-cell-3qvnp398w9.pdf

Inferring tumour purity and stromal and immune cell admixture from expression data

The Cancer Genome Atlas Pan-Cancer analysis project

Local pain around the ankle joint is a common symptom in patients with chronic ankle instability (CAI). However, whether the local pain would impose any influence on the balance control performance of CAI patients is still unknown.A total of twenty-six subjects were recruited and divided into the following two groups: pain-free CAI (group A) and pain-present CAI (group B). Subjects in both groups received two independent tests: the star excursion balance test and the single-leg stance test, in order to reflect their balance control ability more accurately.Compared with group A, the group B showed significantly more episodes of the history of sprains, decreased ankle maximum plantarflexion angle, and lower Cumberland scores (all p < 0.05). In the star excursion balance test, group B demonstrated a significantly reduced anterior reach distance than group A (p < 0.05). During the single leg stance test, group B showed a significant increase in the magnitude of electromyographic signals both in peroneus longus and soleus muscles than group A (each p < 0.05). Additionally, group B had a significantly more anterolaterally positioned plantar center of pressure than group A (p < 0.05).CAI patients with local pain around the ankle joint had more episodes of sprains and lower functional scores when compared to those without pain. The balance control performance was also worse in the pain-present CAI patients than those without pain. 

/pdf/the-influence-of-local-pain-on-balance-control-in-patients-8p94dgf9.pdf

The influence of local pain on balance control in patients with chronic ankle instability

Functional effects of arthroscopic modified Broström procedure on lateral ankle instability: A pilot study.

Recently, a class of small RNA molecules, microRNAs or miRNAs, has attracted interest from researchers for their unique role in post-transcriptional regulation. Due to their distinct cell-type/tissue-specific expression patterns, it is of high importance to identify conditionspecific miRNA-gene modules for a complete depiction of gene regulatory networks. In this paper, we propose a novel method to integrate miRNA and mRNA data to identify condition-specific miRNA-gene modules. Specifically, a Consistency-based Masking Nonnegative Matrix Factorization (CMNMF) method is developed to incorporate existing biological constraints (like the repression of miRNAs on potential target genes) with simultaneous miRNA and mRNA profiling data for an improved performance in module identification. The experimental results on simulation data show that the condition-specific modeling framework improves the performance in predicting miRNA-gene relationships. More importantly, application of CMNMF to human colon cancer data revealed a biologically significant miRNA-gene module, which contains four up-regulated miRNAs (miR-182, miR-183, miR-221 and miR-222) and six down-regulated target genes annotated as cytotoxity mediated by nature killer cells. The proposed method can also be applied to various biological conditions, even with limited number of samples, to elucidate miRNAinvolved gene networks.

Inferring condition-specific miRNA-Gene modules from miRNA and mRNA profiling data

Background: Only a few studies have analyzed functional predictive factors for inferior outcomes after modified Broström procedure (MBP). The aim of the current study is to identify the influence of the preoperative dynamic reach deficit on the surgical outcomes of MBP. Methods: Sixty-one patients with lateral ankle instability who underwent MBP were included in the current study and followed up for a median of 24 months. The Karlsson scores and the reaches of the Star Excursion Balance Test (SEBT) were evaluated before surgery and during the last follow-up. A total of 19 prognostic factors were analyzed. The relationship between the variables and inferior outcomes (Karlsson score < 90) in the bivariate analysis was tested through the Mann-Whitney U test or the Fisher exact test. A multivariate logistic regression model was developed to investigate the influence of the selected factors on inferior outcomes. Results: Thirty-two of the patients had superior outcomes, and the rest had inferior outcomes. The age, gender, and body mass index of the groups with superior and inferior outcomes did not differ. Preoperative dynamic reach deficit (P = .032), osteochondral lesion of the talus (P = .004), and decreased preoperative Karlsson score (P = .004) were independent predictors of inferior outcomes. Conclusion: Patients with preoperative dynamic reach deficit, osteochondral lesion of the talus, or decreased preoperative Karlsson score have inferior outcomes after MBP. Level of Evidence: Level III, case-control study.

Dynamic Reach Deficit Is a Predictive Factor of Inferior Outcomes After Modified Broström Procedure for Lateral Ankle Instability

Cancer is responsible for millions of deaths worldwide every year. Although significant progress has been achieved in cancer medicine, many issues remain to be addressed for improving cancer therapy. Appropriate cancer patient stratification is the prerequisite for selecting appropriate treatment plan, as cancer patients are of known heterogeneous genetic make-ups and phenotypic differences. In this study, built upon deep phenotypic characterizations extractable from Mayo Clinic electronic health records (EHRs) and genetic test reports for a collection of cancer patients, we developed a system leveraging a joint of phenotypic and genetic features for cancer patient subgrouping. 
The workflow is roughly divided into three parts: feature preprocessing, cancer patient classification, and cancer patient clustering based. In feature preprocessing step, we performed filtering, retaining the most relevant features. In cancer patient classification, we utilized joint categorical features to build a patient-feature matrix and applied nine different machine learning models, Random Forests (RF), Decision Tree (DT), Support Vector Machine (SVM), Naive Bayes (NB), Logistic Regression (LR), Multilayer Perceptron (MLP), Gradient Boosting (GB), Convolutional Neural Network (CNN), and Feedforward Neural Network (FNN), for classification purposes. Finally, in the cancer patient clustering step, we leveraged joint embeddings features and patient-feature associations to build an undirected feature graph and then trained the cancer feature node embeddings.

Chen Wang

Papers

The influence of local pain on balance control in patients with chronic ankle instability

Functional effects of arthroscopic modified Broström procedure on lateral ankle instability: A pilot study.

Inferring condition-specific miRNA-Gene modules from miRNA and mRNA profiling data

Dynamic Reach Deficit Is a Predictive Factor of Inferior Outcomes After Modified Broström Procedure for Lateral Ankle Instability

Leveraging a Joint of Phenotypic and Genetic Features on Cancer Patient Subgrouping.