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Cancer development can be defined as a process of cellular and tissular microevolution ultimately leading to malignancy. Strikingly, though this concept has prevailed in the field for more than a century, the precise mechanisms underlying evolutionary processes occurring within tumours remain largely uncharacterized and rather cryptic. Nevertheless, although our current knowledge is fragmentary, data collected to date suggest that most tumours display features compatible with a diverse array of evolutionary paths, suggesting that most of the existing macro-evolutionary models find their avatar in cancer biology. Herein, we discuss an up-to-date view of the fundamental genetic and non-genetic mechanisms underlying tumour evolution with the aim of concurring into an integrated view of the evolutionary forces at play throughout the emergence and progression of the disease and into the acquisition of resistance to diverse therapeutic paradigms. Our ultimate goal is to delve into the intricacies of genetic and non-genetic networks underlying tumour evolution to build a framework where both core concepts are considered non-negligible and equally fundamental.

Trastuzumab-containing therapy is a standard of care for patients with HER2+ breast cancer. HER2 status is routinely assigned using in situ hybridization to assess HER2 gene amplification, but interpretation of in situ hybridization results may be challenging in tumors with chromosome 17 polysomy or intratumoral genetic heterogeneity. Apparent chromosome 17 polysomy, defined by increased chromosome enumeration probe 17 (CEP17) signal number, is a common genetic aberration in breast cancer and represents an alternative mechanism for increasing HER2 copy number. Some studies have linked elevated CEP17 count (‘polysomy') with adverse clinicopathologic features and HER2 overexpression, although there are numerous discrepancies in the literature. There is evidence that elevated CEP17 (‘polysomy') count might account for trastuzumab response in tumors with normal HER2:CEP17 ratios. Nonetheless, recent studies establish that apparent ‘polysomy' (CEP17 increase) is usually related to focal pericentromeric gains rather than true polysomy. Assigning HER2 status may also be complex where multiple cell subclones with distinct HER2 amplification characteristics coexist within the same tumor. Such genetic heterogeneity affects up to 40% of breast cancers when assessed according to a College of American Pathologists guideline, although other definitions have been proposed. Recent data have associated heterogeneity with unfavorable clinicopathologic variables and poor prognosis. Genetically heterogeneous tumors harboring HER2-amplified subclones have the potential to benefit from trastuzumab, but this has yet to be evaluated in clinical studies. In this review, we discuss the implications of apparent polysomy 17 and genetic heterogeneity for assigning HER2 status in clinical practice. Among our recommendations, we support the use of mean HER2 copy number rather than HER2:CEP17 ratio to define HER2 positivity in cases where coamplification of the centromere might mask HER2 amplification. We also highlight a need to harmonize in situ hybridization scoring methodology to support accurate HER2 status determination, particularly where there is evidence of heterogeneity.

The Bruton tyrosine kinase (BTK) inhibitor ibrutinib provides effective treatment for patients with chronic lymphocytic leukemia (CLL), despite extensive heterogeneity in this disease. To define the underlining regulatory dynamics, we analyze high-resolution time courses of ibrutinib treatment in patients with CLL, combining immune-phenotyping, single-cell transcriptome profiling, and chromatin mapping. We identify a consistent regulatory program starting with a sharp decrease of NF-κB binding in CLL cells, which is followed by reduced activity of lineage-defining transcription factors, erosion of CLL cell identity, and acquisition of a quiescence-like gene signature. We observe patient-to-patient variation in the speed of execution of this program, which we exploit to predict patient-specific dynamics in the response to ibrutinib based on the pre-treatment patient samples. In aggregate, our study describes time-dependent cellular, molecular, and regulatory effects for therapeutic inhibition of B cell receptor signaling in CLL, and it establishes a broadly applicable method for epigenome/transcriptome-based treatment monitoring. Ibrutinib, a Bruton tyrosine kinase inhibitor, provides effective treatment for chronic lymphocytic leukemia (CLL). Here, the authors describe time-dependent molecular changes to malignant cells and to the immune system in patients undergoing ibrutinib therapy, with can be used for therapy monitoring.

Cell‐to‐cell variability in gene expression is important for many processes in biology, including embryonic development and stem cell homeostasis. While heterogeneity of gene expression levels has been extensively studied, less attention has been paid to mRNA polyadenylation isoform choice. 3′ untranslated regions regulate mRNA fate, and their choice is tightly controlled during development, but how 3′ isoform usage varies within genetically and developmentally homogeneous cell populations has not been explored. Here, we perform genome‐wide quantification of polyadenylation site usage in single mouse embryonic and neural stem cells using a novel single‐cell transcriptomic method, BATSeq. By applying BATBayes, a statistical framework for analyzing single‐cell isoform data, we find that while the developmental state of the cell globally determines isoform usage, single cells from the same state differ in the choice of isoforms. Notably this variation exceeds random selection with equal preference in all cells, a finding that was confirmed by RNA FISH data. Variability in 3′ isoform choice has potential implications on functional cell‐to‐cell heterogeneity as well as utility in resolving cell populations. Synopsis BATSeq, the first transcriptomic method to quantify polyadenylation site use in single cells, reveals that stem cells from homogeneous populations differ in their preference for 3′ mRNA isoforms. We introduce BATBayes, a Bayesian framework that accounts for technical and biological sources of noise to quantify underlying variability in isoform preference 3′ isoform usage is sufficient to distinguish between cells from different stem cell populations Within homogeneous cell populations, cells differ in their use of isoforms more than expected from random choice An intrinsic mechanism acting at the level of individual genes is likely to contribute to isoform choice variability Graphical Abstract BATSeq, the first transcriptomic method to quantify polyadenylation site use in single cells, reveals that stem cells from homogeneous populations differ in their preference for 3′ mRNA isoforms.

Purpose Intra-tumor heterogeneity (ITH) plays a pivotal role in driving breast cancer progression and therapeutic resistance. We used a mutant-allele tumor heterogeneity (MATH) algorithm to measure ITH and explored its correlation with clinical parameters and multi-omics data. Methods We assessed 916 female breast cancer patients from The Cancer Genome Atlas. We calculated the MATH values from whole-exome sequencing data and further investigated their correlation with clinical characteristics, somatic mutations, somatic copy number alterations (SCNAs), and gene enrichment. Results The patients were divided into low, intermediate, and high MATH groups. High T stage, African American race, and triple-negative or basal-like subtype were associated with a higher MATH level (all P  < 0.001). In hormone receptor-positive and human epidermal growth factor receptor-negative patients, the high MATH group showed a tendency toward a worse overall survival ( P  = 0.052); Furthermore, the TP53 mutation rate increased as MATH was elevated ( P  < 0.001), whereas CDH1 mutations were correlated with a lower level of MATH ( P  = 0.002). Several focal and arm-level SCNA events were more common in the high MATH group ( P  < 0.05), including Chr8q24 with only the MYC gene in the “peak” region. Similarly, high MATH was associated with gene set enrichment related to the MYC pathway and proliferation. Conclusion Our integrative analysis reveals the clinical and genetic relevance of ITH in breast cancer. These results also suggest the origin and natural history of clonal evolution and intra-tumor genetic heterogeneity, which warrant further investigation.

Background Single-cell micro-metastases of solid tumors often occur in the bone marrow. These disseminated tumor cells (DTCs) may resist therapy and lay dormant or progress to cause overt bone and visceral metastases. The molecular nature of DTCs remains elusive, as well as when and from where in the tumor they originate. Here, we apply single-cell sequencing to identify and trace the origin of DTCs in breast cancer. Results We sequence the genomes of 63 single cells isolated from six non-metastatic breast cancer patients. By comparing the cells’ DNA copy number aberration (CNA) landscapes with those of the primary tumors and lymph node metastasis, we establish that 53% of the single cells morphologically classified as tumor cells are DTCs disseminating from the observed tumor. The remaining cells represent either non-aberrant “normal” cells or “aberrant cells of unknown origin” that have CNA landscapes discordant from the tumor. Further analyses suggest that the prevalence of aberrant cells of unknown origin is age-dependent and that at least a subset is hematopoietic in origin. Evolutionary reconstruction analysis of bulk tumor and DTC genomes enables ordering of CNA events in molecular pseudo-time and traced the origin of the DTCs to either the main tumor clone, primary tumor subclones, or subclones in an axillary lymph node metastasis. Conclusions Single-cell sequencing of bone marrow epithelial-like cells, in parallel with intra-tumor genetic heterogeneity profiling from bulk DNA, is a powerful approach to identify and study DTCs, yielding insight into metastatic processes. A heterogeneous population of CNA-positive cells is present in the bone marrow of non-metastatic breast cancer patients, only part of which are derived from the observed tumor lineages.

Manipur, one of the northeastern states of India, lies on the ancient silk route and serves as a meeting point between Southeast Asia and South Asia. The origin and migration histories of Naga and Kuki tribal populations are not clearly understood. Moreover, Kukis have been traced to two different ancestries, which has created confusion among the people. The present study examined genomic affinities and differentiation of the Naga and Kuki tribal populations of Manipur, Northeast India. Twenty autosomal markers (8 Alu insertion-deletions, 12 restriction-fragment-length polymorphisms) were analyzed. Findings show genetic differences between Naga and Kuki tribal populations with respect to the allele distribution pattern, which was substantiated by genetic differentiation (GST = 5.2%) and molecular variance (AMOVA), where the highest percentage of among-group variances was observed between Naga and Kuki tribal groups (7.09%). However, genetic similarities with respect to allele distribution patterns in most of the loci were seen among their respective groups (Rongmei and Inpui, Thadou and Vaiphei). Rongmei and Inpui tribal populations (Naga group) belong to the Naga-Bodo linguistic group, and Thadou and Vaiphei (Kuki group) belong to the Northern Kuki-Chin linguistic group, suggesting that genetic similarities may not be independent of linguistic affinities. Despite differential genetic affinities, both Naga and Kuki tribal populations in Manipur show more proximity with Southeast Asian populations and Northeast Indian populations than with other Indian populations and global populations taken for comparison.

Metabolic engineering-driven microbial cell factories have made great progress in the efficient bioproduction of biochemical and recombinant proteins. However, the low efficiency and robustness of microbial cell factories limit their industrial applications. Harnessing microbial heterogeneity contributes to solving this. In this review, the origins of microbial heterogeneity and its effects on biosynthesis are first summarized. Synthetic biology-driven tools and strategies that can be used to improve biosynthesis by increasing and reducing microbial heterogeneity are then systematically summarized. Next, novel single-cell technologies available for unraveling microbial heterogeneity and facilitating heterogeneity regulation are discussed. Furthermore, a combined workflow of increasing genetic heterogeneity in the strain-building step to help in screening highly productive strains - reducing heterogeneity in the production process to obtain highly robust strains (IHP-RHR) facilitated by single-cell technologies was proposed to obtain highly productive and robust strains by harnessing microbial heterogeneity. Finally, the prospects and future challenges are discussed. [Display omitted] •Systematical discussion on tools and strategies to harness microbial heterogeneity.•Novel single-cell technologies for exploring microbial heterogeneity were summarized.•A workflow IHP-RHR was proposed to obtain highly productive and robust strains.•Prospects and future challenges of harnessing microbial heterogeneity were proposed.

Conflicting theories of epithelial carcinogenesis disagree on the clonal composition of primary tumors and on the time at which metastases occur. In order to study the spatial distribution of disparate clonal populations within breast carcinomas and the extent of the genetic relationship between primary tumors and regional metastases, we have analyzed by comparative genomic hybridization 122 tissue samples from altogether 60 breast cancer patients, including 34 tumor samples obtained from different quadrants of 9 breast carcinomas, as well as paired primary-metastatic samples from 12 patients. The median intratumor genetic heterogeneity score (HS) was 17.4% and unsupervised hierarchical clustering analysis comparing the genetic features to those of an independent series of 41 breast carcinomas confirmed intratumor clonal divergence in a high proportion of cases. The median HS between paired primary breast tumors and lymph node metastases was 33.3%, but the number of genomic imbalances did not differ significantly. Clustering analysis confirmed extensive clonal divergence between primary carcinomas and lymph node metastases in several cases. In the independent series of 41 breast carcinomas, the number of genomic imbalances in primary tumors was significantly higher in patients presenting lymph node metastases (median = 15.5) than in the group with no evidence of disease spreading at diagnosis (median = 5.0). We conclude that primary breast carcinomas may be composed of several genetically heterogeneous and spatially separated cell populations and that paired primary breast tumors and lymph node metastases often present divergent clonal evolution, indicating that metastases may occur relatively early during breast carcinogenesis.