Neoadjuvant Immunotherapy in Locally Advanced Mismatch Repair-Deficient Colon Cancer.

Background: Mismatch repair-deficient (dMMR) tumors can be found in 10 to 15% of patients with nonmetastatic colon cancer. In these patients, the efficacy of chemotherapy is limited. The use of neoadjuvant immunotherapy has shown promising results, but data from studies of this approach are limited.

Ductal carcinoma in situ develops within clonal fields of mutant cells in morphologically normal ducts.

Mutations are abundantly present in tissues of healthy individuals, including the breast epithelium. Yet it remains unknown whether mutant cells directly induce lesion formation or first spread, leading to a field of mutant cells that is predisposed towards lesion formation. To study the clonal and spatial relationships between morphologically normal breast epithelium adjacent to pre-cancerous lesions, we developed a three-dimensional (3D) imaging pipeline combined with spatially resolved genomics on archival, formalin-fixed breast tissue with the non-obligate breast cancer precursor ductal carcinoma in situ (DCIS).

Ovarian Cancer-Specific -like Copy-Number Aberration Classifiers Detect Mutations Associated with Homologous Recombination Deficiency in the AGO-TR1 Trial.

Purpose: Previously, we developed breast cancer like and -like copy-number profile shrunken centroid classifiers predictive for mutation status and response to therapy, targeting homologous recombination deficiency (HRD). Therefore, we investigated and like classification in ovarian cancer, aiming to acquire classifiers with similar properties as those in breast cancer. We analyzed DNA copy-number profiles of germline - and -mutant ovarian cancers and control tumors and observed that existing breast cancer classifiers did not sufficiently predict mutation status.

In situ CRISPR-Cas9 base editing for the development of genetically engineered mouse models of breast cancer.

Genetically engineered mouse models (GEMMs) of cancer have proven to be of great value for basic and translational research. Although CRISPR-based gene disruption offers a fast-track approach for perturbing gene function and circumvents certain limitations of standard GEMM development, it does not provide a flexible platform for recapitulating clinically relevant missense mutations in vivo. To this end, we generated knock-in mice with Cre-conditional expression of a cytidine base editor and tested their utility for precise somatic engineering of missense mutations in key cancer drivers.

TLE3 loss confers AR inhibitor resistance by facilitating GR-mediated human prostate cancer cell growth.

Androgen receptor (AR) inhibitors represent the mainstay of prostate cancer treatment. In a genome-wide CRISPR-Cas9 screen using LNCaP prostate cancer cells, loss of co-repressor conferred resistance to AR antagonists apalutamide and enzalutamide. Genes differentially expressed upon loss share AR as the top transcriptional regulator, and loss rescued the expression of a subset of androgen-responsive genes upon enzalutamide treatment.

Optimized ChIP-seq method facilitates transcription factor profiling in human tumors.

Chromatin immunoprecipitation (ChIP)-seq analyses of transcription factors in clinical specimens are challenging due to the technical limitations and low quantities of starting material, often resulting in low enrichments and poor signal-to-noise ratio. Here, we present an optimized protocol for transcription factor ChIP-seq analyses in human tissue, yielding an ∼100% success rate for all transcription factors analyzed. As proof of concept and to illustrate general applicability of the approach, human tissue from the breast, prostate, and endometrial cancers were analyzed.

Consensus molecular subtype classification of colorectal adenomas.

Consensus molecular subtyping is an RNA expression-based classification system for colorectal cancer (CRC). Genomic alterations accumulate during CRC pathogenesis, including the premalignant adenoma stage, leading to changes in RNA expression. Only a minority of adenomas progress to malignancies, a transition that is associated with specific DNA copy number aberrations or microsatellite instability (MSI).

Insertional mutagenesis in a HER2-positive breast cancer model reveals ERAS as a driver of cancer and therapy resistance.

Personalized medicine for cancer patients requires a deep understanding of the underlying genetics that drive cancer and the subsequent identification of predictive biomarkers. To discover new genes and pathways contributing to oncogenesis and therapy resistance in HER2+ breast cancer, we performed Mouse Mammary Tumor Virus (MMTV)-induced insertional mutagenesis screens in ErbB2/cNeu-transgenic mouse models. The screens revealed 34 common integration sites (CIS) in mammary tumors of MMTV-infected mice, highlighting loci with multiple independent MMTV integrations in which potential oncogenes are activated, most of which had never been reported as MMTV CIS.

Estrogen receptor α wields treatment-specific enhancers between morphologically similar endometrial tumors.

The DNA-binding sites of estrogen receptor α (ERα) show great plasticity under the control of hormones and endocrine therapy. Tamoxifen is a widely applied therapy in breast cancer that affects ERα interactions with coregulators and shifts the DNA-binding signature of ERα upon prolonged exposure in breast cancer. Although tamoxifen inhibits the progression of breast cancer, it increases the risk of endometrial cancer in postmenopausal women.

A novel independence test for somatic alterations in cancer shows that biology drives mutual exclusivity but chance explains most co-occurrence.

In cancer, mutually exclusive or co-occurring somatic alterations across genes can suggest functional interactions. Existing tests for such patterns make the unrealistic assumption of identical gene alteration probabilities across tumors. We present Discrete Independence Statistic Controlling for Observations with Varying Event Rates (DISCOVER), a novel test that is more sensitive than other methods and controls its false positive rate.

Logic models to predict continuous outputs based on binary inputs with an application to personalized cancer therapy.

Mining large datasets using machine learning approaches often leads to models that are hard to interpret and not amenable to the generation of hypotheses that can be experimentally tested. We present 'Logic Optimization for Binary Input to Continuous Output' (LOBICO), a computational approach that infers small and easily interpretable logic models of binary input features that explain a continuous output variable. Applying LOBICO to a large cancer cell line panel, we find that logic combinations of multiple mutations are more predictive of drug response than single gene predictors.

Loss of ARID1A Activates ANXA1, which Serves as a Predictive Biomarker for Trastuzumab Resistance.

Purpose: Despite the substantial progress in the development of targeted anticancer drugs, treatment failure due to primary or acquired resistance is still a major hurdle in the effective treatment of most advanced human cancers. Understanding these resistance mechanisms will be instrumental to improve personalized cancer treatment.

Experimental Design: Genome-wide loss-of-function genetic screens were performed to identify genes implicated in resistance to HER2/PI3K/mTOR targeting agents in HER2 breast cancer cell lines.

BCM: toolkit for Bayesian analysis of Computational Models using samplers.

Background: Computational models in biology are characterized by a large degree of uncertainty. This uncertainty can be analyzed with Bayesian statistics, however, the sampling algorithms that are frequently used for calculating Bayesian statistical estimates are computationally demanding, and each algorithm has unique advantages and disadvantages. It is typically unclear, before starting an analysis, which algorithm will perform well on a given computational model.

Large variety in a panel of human colon cancer organoids in response to EZH2 inhibition.

EZH2 inhibitors have gained great interest for their use as anti-cancer therapeutics. However, most research has focused on EZH2 mutant cancers and recently adverse effects of EZH2 inactivation have come to light. To determine whether colorectal cancer cells respond to EZH2 inhibition and to explore which factors influence the degree of response, we treated a panel of 20 organoid lines derived from human colon tumors with different concentrations of the EZH2 inhibitor GSK126.

TANDEM: a two-stage approach to maximize interpretability of drug response models based on multiple molecular data types.

Motivation: Clinical response to anti-cancer drugs varies between patients. A large portion of this variation can be explained by differences in molecular features, such as mutation status, copy number alterations, methylation and gene expression profiles. We show that the classic approach for combining these molecular features (Elastic Net regression on all molecular features simultaneously) results in models that are almost exclusively based on gene expression.

RUBIC identifies driver genes by detecting recurrent DNA copy number breaks.

The frequent recurrence of copy number aberrations across tumour samples is a reliable hallmark of certain cancer driver genes. However, state-of-the-art algorithms for detecting recurrent aberrations fail to detect several known drivers. In this study, we propose RUBIC, an approach that detects recurrent copy number breaks, rather than recurrently amplified or deleted regions.

Deletion of Polycomb Repressive Complex 2 From Mouse Intestine Causes Loss of Stem Cells.

Background & Aims: The polycomb repressive complex 2 (PRC2) regulates differentiation by contributing to repression of gene expression and thereby stabilizing the fate of stem cells and their progeny. PRC2 helps to maintain adult stem cell populations, but little is known about its functions in intestinal stem cells. We studied phenotypes of mice with intestine-specific deletion of the PRC2 proteins embryonic ectoderm development (EED) (a subunit required for PRC2 function) and enhancer of zeste homolog 2 (EZH2) (a histone methyltransferase).

OncoScape: Exploring the cancer aberration landscape by genomic data fusion.

Although large-scale efforts for molecular profiling of cancer samples provide multiple data types for many samples, most approaches for finding candidate cancer genes rely on somatic mutations and DNA copy number only. We present a new method, OncoScape, which exploits five complementary data types across 11 cancer types to identify new candidate cancer genes. We find many rarely mutated genes that are strongly affected by other aberrations.

Defining chromosomal translocation risks in cancer.

Chromosomal translocations are a hallmark of cancer. Unraveling the molecular mechanism of these rare genetic events requires a clear distinction between correlative and causative risk-determinants, where technical and analytical issues can be excluded. To meet this goal, we performed in-depth analyses of publicly available genome-wide datasets.

Sensitizing Triple-Negative Breast Cancer to PI3K Inhibition by Cotargeting IGF1R.

Targeted therapies have proven invaluable in the treatment of breast cancer, as exemplified by tamoxifen treatment for hormone receptor-positive tumors and trastuzumab treatment for HER2-positive tumors. In contrast, a subset of breast cancer negative for these markers, triple-negative breast cancer (TNBC), has met limited success with pathway-targeted therapies. A large fraction of TNBCs depend on the PI3K pathway for proliferation and survival, but inhibition of PI3K alone generally has limited clinical benefit.

Multilevel models improve precision and speed of IC50 estimates.

Aim: Experimental variation in dose-response data of drugs tested on cell lines result in inaccuracies in the estimate of a key drug sensitivity characteristic: the IC50. We aim to improve the precision of the half-limiting dose (IC50) estimates by simultaneously employing all dose-responses across all cell lines and drugs, rather than using a single drug-cell line response.

Materials & Methods: We propose a multilevel mixed effects model that takes advantage of all available dose-response data.

Androgen receptor DNA binding and chromatin accessibility profiling in prostate cancer.

Prostate cancer (PCa) is the second most common cancer in men. The Androgen Receptor (AR) is the major driver of PCa and the main target of therapy in the advanced setting. AR is a nuclear receptor that binds the chromatin and regulates transcription of genes involved in cancer cell proliferation and survival.

Integration of genomic, transcriptomic and proteomic data identifies two biologically distinct subtypes of invasive lobular breast cancer.

Invasive lobular carcinoma (ILC) is the second most frequently occurring histological breast cancer subtype after invasive ductal carcinoma (IDC), accounting for around 10% of all breast cancers. The molecular processes that drive the development of ILC are still largely unknown. We have performed a comprehensive genomic, transcriptomic and proteomic analysis of a large ILC patient cohort and present here an integrated molecular portrait of ILC.

Subunit composition of VRAC channels determines substrate specificity and cellular resistance to Pt-based anti-cancer drugs.

Although platinum-based drugs are widely used chemotherapeutics for cancer treatment, the determinants of tumor cell responsiveness remain poorly understood. We show that the loss of subunits LRRC8A and LRRC8D of the heteromeric LRRC8 volume-regulated anion channels (VRACs) increased resistance to clinically relevant cisplatin/carboplatin concentrations. Under isotonic conditions, about 50% of cisplatin uptake depended on LRRC8A and LRRC8D, but neither on LRRC8C nor on LRRC8E.

Applications of DNA integrating elements: Facing the bias bully.

Retroviruses and DNA transposons are an important part of molecular biologists' toolbox. The applications of these elements range from functional genomics to oncogene discovery and gene therapy. However, these elements do not integrate uniformly across the genome, which is an important limitation to their use.