Spatial analysis of recurrent glioblastoma reveals perivascular niche organization.

Tumor evolution is driven by genetic variation; however, it is the tumor microenvironment (TME) that provides the selective pressure contributing to evolution in cancer. Despite high histopathological heterogeneity within glioblastoma (GBM), the most aggressive brain tumor, the interactions between the genetically distinct GBM cells and the surrounding TME are not fully understood. To address this, we analyzed matched primary and recurrent GBM archival tumor tissues with imaging-based techniques aimed to simultaneously evaluate tumor tissues for the presence of hypoxic, angiogenic, and inflammatory niches, extracellular matrix (ECM) organization, TERT promoter mutational status, and several oncogenic amplifications on the same slide and location.

A Phase 1b Adaptive Androgen Deprivation Therapy Trial in Metastatic Castration Sensitive Prostate Cancer.

Background: We hypothesize that cancer survival can be improved through adapting treatment strategies to cancer evolutionary dynamics and conducted a phase 1b study in metastatic castration sensitive prostate cancer (mCSPC). Methods: Men with asymptomatic mCSPC were enrolled and proceeded with a treatment break after achieving > 75% PSA decline with LHRH analog plus an NHA. ADT was restarted at the time of PSA or radiographic progression and held again after achieving >50% PSA decline.

Ovarian cancer immunogenicity is governed by a narrow subset of progenitor tissue-resident memory T cells.

Despite repeated associations between T cell infiltration and outcome, human ovarian cancer remains poorly responsive to immunotherapy. We report that the hallmarks of tumor recognition in ovarian cancer-infiltrating T cells are primarily restricted to tissue-resident memory (TRM) cells. Single-cell RNA/TCR/ATAC sequencing of 83,454 CD3CD8CD103CD69 TRM cells and immunohistochemistry of 122 high-grade serous ovarian cancers shows that only progenitor (TCF1) tissue-resident T cells (TRM cells), but not recirculating TCF1 T cells, predict ovarian cancer outcome.

IgA-Dominated Humoral Immune Responses Govern Patients' Outcome in Endometrial Cancer.

Unlabelled: Recent studies suggest that B cells could play an important role in the tumor microenvironment. However, the role of humoral responses in endometrial cancer remains insufficiently investigated. Using a cohort of 107 patients with different histological subtypes of endometrial carcinoma, we evaluated the role of coordinated humoral and cellular adaptive immune responses in endometrial cancer.

IgA transcytosis and antigen recognition govern ovarian cancer immunity.

Most ovarian cancers are infiltrated by prognostically relevant activated T cells, yet exhibit low response rates to immune checkpoint inhibitors. Memory B cell and plasma cell infiltrates have previously been associated with better outcomes in ovarian cancer, but the nature and functional relevance of these responses are controversial. Here, using 3 independent cohorts that in total comprise 534 patients with high-grade serous ovarian cancer, we show that robust, protective humoral responses are dominated by the production of polyclonal IgA, which binds to polymeric IgA receptors that are universally expressed on ovarian cancer cells.

Molecular Determinants of Thyroid Nodules with Indeterminate Cytology and Mutations.

gene family mutations are the most prevalent in thyroid nodules with indeterminate cytology and are present in a wide spectrum of histological diagnoses. We evaluated differentially expressed genes and signaling pathways across the histological/clinical spectrum of -mutant nodules to determine key molecular determinants associated with a high risk of malignancy. Sixty-one thyroid nodules with mutations were identified.

Multidrug Cancer Therapy in Metastatic Castrate-Resistant Prostate Cancer: An Evolution-Based Strategy.

Purpose: Integration of evolutionary dynamics into systemic therapy for metastatic cancers can prolong tumor control compared with standard maximum tolerated dose (MTD) strategies. Prior investigations have focused on monotherapy, but many clinical cancer treatments combine two or more drugs. Optimizing the evolutionary dynamics in multidrug therapy is challenging because of the complex cellular interactions and the large parameter space of potential variations in drugs, doses, and treatment schedules.

The evolutionary landscape of colorectal tumorigenesis.

The evolutionary events that cause colorectal adenomas (benign) to progress to carcinomas (malignant) remain largely undetermined. Using multi-region genome and exome sequencing of 24 benign and malignant colorectal tumours, we investigate the evolutionary fitness landscape occupied by these neoplasms. Unlike carcinomas, advanced adenomas frequently harbour sub-clonal driver mutations-considered to be functionally important in the carcinogenic process-that have not swept to fixation, and have relatively high genetic heterogeneity.

Stochasticity in the Genotype-Phenotype Map: Implications for the Robustness and Persistence of Bet-Hedging.

Nongenetic variation in phenotypes, or bet-hedging, has been observed as a driver of drug resistance in both bacterial infections and cancers. Here, we study how bet-hedging emerges in genotype-phenotype (GP) mapping through a simple interaction model: a molecular switch. We use simple chemical reaction networks to implement stochastic switches that map gene products to phenotypes, and investigate the impact of structurally distinct mappings on the evolution of phenotypic heterogeneity.

Phase i trials in melanoma: A framework to translate preclinical findings to the clinic.

Background: One of major issues in clinical trials in oncology is their high failure rate, despite the fact that the trials were designed based on the data from successful equivalent preclinical studies. This is in part due to the intrinsic homogeneity of preclinical model systems and the contrasting heterogeneity of actual patient responses.

Methods: We present a mathematical model-driven framework, phase i (virtual/imaginary) trials, that integrates the heterogeneity of actual patient responses and preclinical studies through a cohort of virtual patients.

The Cancer Stem Cell Fraction in Hierarchically Organized Tumors Can Be Estimated Using Mathematical Modeling and Patient-Specific Treatment Trajectories.

Many tumors are hierarchically organized and driven by a subpopulation of tumor-initiating cells (TIC), or cancer stem cells. TICs are uniquely capable of recapitulating the tumor and are thought to be highly resistant to radio- and chemotherapy. Macroscopic patterns of tumor expansion before treatment and tumor regression during treatment are tied to the dynamics of TICs.

Spatial Metrics of Tumour Vascular Organisation Predict Radiation Efficacy in a Computational Model.

Intratumoural heterogeneity is known to contribute to poor therapeutic response. Variations in oxygen tension in particular have been correlated with changes in radiation response in vitro and at the clinical scale with overall survival. Heterogeneity at the microscopic scale in tumour blood vessel architecture has been described, and is one source of the underlying variations in oxygen tension.

Steering Evolution with Sequential Therapy to Prevent the Emergence of Bacterial Antibiotic Resistance.

The increasing rate of antibiotic resistance and slowing discovery of novel antibiotic treatments presents a growing threat to public health. Here, we consider a simple model of evolution in asexually reproducing populations which considers adaptation as a biased random walk on a fitness landscape. This model associates the global properties of the fitness landscape with the algebraic properties of a Markov chain transition matrix and allows us to derive general results on the non-commutativity and irreversibility of natural selection as well as antibiotic cycling strategies.

The evolution of carrying capacity in constrained and expanding tumour cell populations.

Cancer cells are known to modify their micro-environment such that it can sustain a larger population, or, in ecological terms, they construct a niche which increases the carrying capacity of the population. It has however been argued that niche construction, which benefits all cells in the tumour, would be selected against since cheaters could reap the benefits without paying the cost. We have investigated the impact of niche specificity on tumour evolution using an individual based model of breast tumour growth, in which the carrying capacity of each cell consists of two components: an intrinsic, subclone-specific part and a contribution from all neighbouring cells.

In silico analysis suggests differential response to bevacizumab and radiation combination therapy in newly diagnosed glioblastoma.

Recently, two phase III studies of bevacizumab, an anti-angiogenic, for newly diagnosed glioblastoma (GBM) patients were released. While they were unable to statistically significantly demonstrate that bevacizumab in combination with other therapies increases the overall survival of GBM patients, there remains a question of potential benefits for subpopulations of patients. We use a mathematical model of GBM growth to investigate differential benefits of combining surgical resection, radiation and bevacizumab across observed tumour growth kinetics.

Impact of metabolic heterogeneity on tumor growth, invasion, and treatment outcomes.

Histopathologic knowledge that extensive heterogeneity exists between and within tumors has been confirmed and deepened recently by molecular studies. However, the impact of tumor heterogeneity on prognosis and treatment remains as poorly understood as ever. Using a hybrid multiscale mathematical model of tumor growth in vascularized tissue, we investigated the selection pressures exerted by spatial and temporal variations in tumor microenvironment and the resulting phenotypic adaptations.

Big Bang and context-driven collapse.

Heterogeneity is the single most important factor driving cancer progression and treatment failure, yet little is understood about how and when this heterogeneity arises. A new study shows that colorectal cancers acquire their dominant mutations early in development and that subsequent mutations, even if they confer greater fitness, are unlikely to sweep through the tumor.

A filter-flow perspective of haematogenous metastasis offers a non-genetic paradigm for personalised cancer therapy.

Research into mechanisms of haematogenous metastasis has largely become genetic in focus, attempting to understand the molecular basis of 'seed-soil' relationships. Preceding this biological mechanism is the physical process of dissemination of circulating tumour cells (CTCs) in the circulation. Patterns of metastatic spread have been previously quantified using the metastatic efficiency index, a measure quantifying metastatic incidence for a given primary-target organ pair and the relative blood flow between them.

Bridging scales in cancer progression: mapping genotype to phenotype using neural networks.

In this review we summarise our recent efforts in trying to understand the role of heterogeneity in cancer progression by using neural networks to characterise different aspects of the mapping from a cancer cells genotype and environment to its phenotype. Our central premise is that cancer is an evolving system subject to mutation and selection, and the primary conduit for these processes to occur is the cancer cell whose behaviour is regulated on multiple biological scales. The selection pressure is mainly driven by the microenvironment that the tumour is growing in and this acts directly upon the cell phenotype.

Exploiting ecological principles to better understand cancer progression and treatment.

A small but growing number of people are finding interesting parallels between ecosystems as studied by ecologists (think of a savannah or the Amazon rainforest or a coral reef) and tumours. The idea of viewing cancer from an ecological perspective has many implications but, basically, it means that we should not see cancer just as a group of mutated cells. A more useful definition of cancer is to consider it a disruption in the complex balance of many interacting cellular and microenvironmental elements in a specific organ.

Evolution of intratumoral phenotypic heterogeneity: the role of trait inheritance.

A tumour is a heterogeneous population of cells that competes for limited resources. In the clinic, we typically probe the tumour by biopsy, and then characterize it by the dominant genetic clone. But genotypes are only the first link in the chain of hierarchical events that leads to a specific cell phenotype.

Inhibition of autophagy enhances the effects of the AKT inhibitor MK-2206 when combined with paclitaxel and carboplatin in BRAF wild-type melanoma.

This study investigates the mechanism of action behind the long-term responses (12-16 months) of two BRAF WT melanoma patients to the AKT inhibitor MK-2206 in combination with paclitaxel and carboplatin. Although single agent MK-2206 inhibited phospho-AKT signaling, it did not impact in vitro melanoma growth or survival. The combination of MK-2206 with paclitaxel and carboplatin was cytotoxic in long-term colony formation and 3D spheroid assays, and induced autophagy.

Microenvironmental variables must influence intrinsic phenotypic parameters of cancer stem cells to affect tumourigenicity.

Since the discovery of tumour initiating cells (TICs) in solid tumours, studies focussing on their role in cancer initiation and progression have abounded. The biological interrogation of these cells continues to yield volumes of information on their pro-tumourigenic behaviour, but actionable generalised conclusions have been scarce. Further, new information suggesting a dependence of tumour composition and growth on the microenvironment has yet to be studied theoretically.

Senescent fibroblasts in melanoma initiation and progression: an integrated theoretical, experimental, and clinical approach.

We present an integrated study to understand the key role of senescent fibroblasts in driving melanoma progression. Based on the hybrid cellular automata paradigm, we developed an in silico model of normal skin. The model focuses on key cellular and microenvironmental variables that regulate interactions among keratinocytes, melanocytes, and fibroblasts, key components of the skin.

Modeling Tumor-Associated Edema in Gliomas during Anti-Angiogenic Therapy and Its Impact on Imageable Tumor.

Glioblastoma, the most aggressive form of primary brain tumor, is predominantly assessed with gadolinium-enhanced T1-weighted (T1Gd) and T2-weighted magnetic resonance imaging (MRI). Pixel intensity enhancement on the T1Gd image is understood to correspond to the gadolinium contrast agent leaking from the tumor-induced neovasculature, while hyperintensity on the T2/FLAIR images corresponds with edema and infiltrated tumor cells. None of these modalities directly show tumor cells; rather, they capture abnormalities in the microenvironment caused by the presence of tumor cells.