Anders Valind

Bio: Anders Valind is an academic researcher from Lund University. The author has contributed to research in topics: Chromosome instability & Wilms' tumor. The author has an hindex of 8, co-authored 23 publications receiving 267 citations.

Intratumoral genome diversity parallels progression and predicts outcome in pediatric cancer

Abstract: Genetic differences among neoplastic cells within the same tumour have been proposed to drive cancer progression and treatment failure. Whether data on intratumoral diversity can be used to predict clinical outcome remains unclear. We here address this issue by quantifying genetic intratumoral diversity in a set of chemotherapy-treated childhood tumours. By analysis of multiple tumour samples from seven patients we demonstrate intratumoral diversity in all patients analysed after chemotherapy, typically presenting as multiple clones within a single millimetre-sized tumour sample (microdiversity). We show that microdiversity often acts as the foundation for further genome evolution in metastases. In addition, we find that microdiversity predicts poor cancer-specific survival (60%; P=0.009), independent of other risk factors, in a cohort of 44 patients with chemotherapy-treated childhood kidney cancer. Survival was 100% for patients lacking microdiversity. Thus, intratumoral genetic diversity is common in childhood cancers after chemotherapy and may be an important factor behind treatment failure.

Four evolutionary trajectories underlie genetic intratumoral variation in childhood cancer

Abstract: A major challenge to personalized oncology is that driver mutations vary among cancer cells inhabiting the same tumor. Whether this reflects principally disparate patterns of Darwinian evolution in different tumor regions has remained unexplored1–5. We mapped the prevalence of genetically distinct clones over 250 regions in 54 childhood cancers. This showed that primary tumors can simultaneously follow up to four evolutionary trajectories over different anatomic areas. The most common pattern consists of subclones with very few mutations confined to a single tumor region. The second most common is a stable coexistence, over vast areas, of clones characterized by changes in chromosome numbers. This is contrasted by a third, less frequent, pattern where a clone with driver mutations or structural chromosome rearrangements emerges through a clonal sweep to dominate an anatomical region. The fourth and rarest pattern is the local emergence of a myriad of clones with TP53 inactivation. Death from disease was limited to tumors exhibiting the two last, most dynamic patterns.

BCOR internal tandem duplication and YWHAE–NUTM2B/E fusion are mutually exclusive events in clear cell sarcoma of the kidney

Abstract: Clear cell sarcoma of the kidney (CCSK) is the second most common pediatric renal tumor. Two recurrent genetic aberrations have been described in CCSK. One is a fusion of YWHAE and NUTM2B/E, the other is an internal tandem duplication (ITD) in the BCOR gene. Here it is shown that YWHAE-NUTM2B/E fusion and the BCOR ITD are mutually exclusive events and activated different downstream signaling systems. This has important diagnostic implications and opens up for further mechanistic studies of CCSK pathogenesis.

Whole chromosome gain does not in itself confer cancer-like chromosomal instability

Abstract: Constitutional aneuploidy is typically caused by a single-event meiotic or early mitotic error. In contrast, somatic aneuploidy, found mainly in neoplastic tissue, is attributed to continuous chromosomal instability. More debated as a cause of aneuploidy is aneuploidy itself; that is, whether aneuploidy per se causes chromosomal instability, for example, in patients with inborn aneuploidy. We have addressed this issue by quantifying the level of somatic mosaicism, a proxy marker of chromosomal instability, in patients with constitutional aneuploidy by precise background-filtered dual-color FISH. In contrast to previous studies that used less precise methods, we find that constitutional trisomy, even for large chromosomes that are often trisomic in cancer, does not confer a significantly elevated rate of somatic chromosomal mosaicism in individual cases. Constitutional triploidy was associated with an increased level of somatic mosaicism, but this consisted mostly of reversion from trisomy to disomy and did not correspond to a proportionally elevated level of chromosome mis-segregation in triploids, indicating that the observed mosaicism resulted from a specific accumulation of cells with a hypotriploid chromosome number. In no case did the rate of somatic mosaicism in constitutional aneuploidy exceed that of “chromosomally stable” cancer cells. Our findings show that even though constitutional aneuploidy was in some cases associated with low-level somatic mosaicism, it was insufficient to generate the cancer-like levels expected if aneuploidy single-handedly triggered cancer-like chromosomal instability.

Integrative Genomics Viewer

Abstract: Rapid improvements in sequencing and array-based platforms are resulting in a flood of diverse genome-wide data, including data from exome and whole-genome sequencing, epigenetic surveys, expression profiling of coding and noncoding RNAs, single nucleotide polymorphism (SNP) and copy number profiling, and functional assays. Analysis of these large, diverse data sets holds the promise of a more comprehensive understanding of the genome and its relation to human disease. Experienced and knowledgeable human review is an essential component of this process, complementing computational approaches. This calls for efficient and intuitive visualization tools able to scale to very large data sets and to flexibly integrate multiple data types, including clinical data. However, the sheer volume and scope of data pose a significant challenge to the development of such tools.

SF-010-4 Distant metastasis occurs late during the genetic evolution of pancreatic cancer

Abstract: Metastasis, the dissemination and growth of neoplastic cells in an organ distinct from that in which they originated, is the most common cause of death in cancer patients. This is particularly true for pancreatic cancers, where most patients are diagnosed with metastatic disease and few show a sustained response to chemotherapy or radiation therapy. Whether the dismal prognosis of patients with pancreatic cancer compared to patients with other types of cancer is a result of late diagnosis or early dissemination of disease to distant organs is not known. Here we rely on data generated by sequencing the genomes of seven pancreatic cancer metastases to evaluate the clonal relationships among primary and metastatic cancers. We find that clonal populations that give rise to distant metastases are represented within the primary carcinoma, but these clones are genetically evolved from the original parental, non-metastatic clone. Thus, genetic heterogeneity of metastases reflects that within the primary carcinoma. A quantitative analysis of the timing of the genetic evolution of pancreatic cancer was performed, indicating at least a decade between the occurrence of the initiating mutation and the birth of the parental, non-metastatic founder cell. At least five more years are required for the acquisition of metastatic ability and patients die an average of two years thereafter. These data provide novel insights into the genetic features underlying pancreatic cancer progression and define a broad time window of opportunity for early detection to prevent deaths from metastatic disease.

Landscape of somatic mutations in 560 breast cancer whole-genome sequences

Abstract: We analysed whole-genome sequences of 560 breast cancers to advance understanding of the driver mutations conferring clonal advantage and the mutational processes generating somatic mutations. We found that 93 protein-coding cancer genes carried probable driver mutations. Some non-coding regions exhibited high mutation frequencies, but most have distinctive structural features probably causing elevated mutation rates and do not contain driver mutations. Mutational signature analysis was extended to genome rearrangements and revealed twelve base substitution and six rearrangement signatures. Three rearrangement signatures, characterized by tandem duplications or deletions, appear associated with defective homologous-recombination-based DNA repair: one with deficient BRCA1 function, another with deficient BRCA1 or BRCA2 function, the cause of the third is unknown. This analysis of all classes of somatic mutation across exons, introns and intergenic regions highlights the repertoire of cancer genes and mutational processes operating, and progresses towards a comprehensive account of the somatic genetic basis of breast cancer.

Precision medicine for cancer with next-generation functional diagnostics

Abstract: Precision medicine is about matching the right drugs to the right patients. Although this approach is technology agnostic, in cancer there is a tendency to make precision medicine synonymous with genomics. However, genome-based cancer therapeutic matching is limited by incomplete biological understanding of the relationship between phenotype and cancer genotype. This limitation can be addressed by functional testing of live patient tumour cells exposed to potential therapies. Recently, several 'next-generation' functional diagnostic technologies have been reported, including novel methods for tumour manipulation, molecularly precise assays of tumour responses and device-based in situ approaches; these address the limitations of the older generation of chemosensitivity tests. The promise of these new technologies suggests a future diagnostic strategy that integrates functional testing with next-generation sequencing and immunoprofiling to precisely match combination therapies to individual cancer patients.

Sensitivity and specificity of information criteria.

Abstract: Choosing a model with too few parameters can involve making unrealistically simple assumptions and lead to high bias, poor prediction, and missed opportunities for insight. Such models are not flexible enough to describe the sample or the population well. A model with too many parameters can fit the observed data very well, but be too closely tailored to it. Such models may generalize poorly. Penalizedlikelihood information criteria, such as Akaike’s Information Criterion (AIC), the Bayesian Information Criterion (BIC), the Consistent AIC, and the Adjusted BIC, are widely used for model selection. However, different criteria sometimes support different models, leading to uncertainty about which criterion is the most trustworthy. In some simple cases the comparison of two models using information criteria can be viewed as equivalent to a likelihood ratio test, with the different models representing different alpha levels (i.e., different emphases on sensitivity or specificity; Lin & Dayton 1997). This perspective may lead to insights about how to interpret the criteria in less simple situations. For example, AIC or BIC could be preferable, depending on sample size and on the relative importance one assigns to sensitivity versus specificity. Understanding the differences among the criteria may make it easier to compare their results and to use them to make informed decisions.