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Cancers rely on multiple, heterogeneous processes at different scales, pertaining to many biomedical fields. Therefore, understanding cancer is necessarily an interdisciplinary task that requires placing specialised experimental and clinical research into a broader conceptual, theoretical, and methodological framework. Without such a framework, oncology will collect piecemeal results, with scant dialogue between the different scientific communities studying cancer. We argue that one important way forward in service of a more successful dialogue is through greater integration of applied sciences (experimental and clinical) with conceptual and theoretical approaches, informed by philosophical methods. By way of illustration, we explore six central themes: (i) the role of mutations in cancer; (ii) the clonal evolution of cancer cells; (iii) the relationship between cancer and multicellularity; (iv) the tumour microenvironment; (v) the immune system; and (vi) stem cells. In each case, we examine open questions in the scientific literature through a philosophical methodology and show the benefit of such a synergy for the scientific and medical understanding of cancer.

Cancers rely on multiple, heterogeneous processes at different scales, pertaining to many biomedical fields. Therefore, understanding cancer is necessarily an interdisciplinary task that requires placing specialised experimental and clinical research into a broader conceptual, theoretical, and methodological framework. Without such a framework, oncology will collect piecemeal results, with scant dialogue between the different scientific communities studying cancer. We argue that one important way forward in service of a more successful dialogue is through greater integration of applied sciences (experimental and clinical) with conceptual and theoretical approaches, informed by philosophical methods. By way of illustration, we explore six central themes: (i) the role of mutations in cancer; (ii) the clonal evolution of cancer cells; (iii) the relationship between cancer and multicellularity; (iv) the tumour microenvironment; (v) the immune system; and (vi) stem cells. In each case, we examine open questions in the scientific literature through a philosophical methodology and show the benefit of such a synergy for the scientific and medical understanding of cancer.

BACKGROUND: We previously reported a familial thyroid follicular cell carcinoma (FCC) in a large number of Dutch German longhaired pointers and identified two deleterious germline mutations in the TPO gene associated with disease predisposition. However, the somatic mutation profile of the FCC in dogs has not been investigated at a genome-wide scale.RESULTS: Herein, we comprehensively investigated the somatic mutations that potentially contribute to the inherited tumor formation and progression using high depth whole-genome sequencing. A GNAS p.A204D missense mutation was identified in 4 out of 7 FCC tumors by whole-genome sequencing and in 20 out of 32 dogs' tumors by targeted sequencing. In contrast to this, in the human TC, mutations in GNAS gene have lower prevalence. Meanwhile, the homologous somatic mutation in humans has not been reported. These findings suggest a difference in the somatic mutation landscape between TC in these dogs and human TC. Moreover, tumors with the GNAS p.A204D mutation had a significantly lower somatic mutation burden in these dogs. Somatic structural variant and copy number alterations were also investigated, but no potential driver event was identified.CONCLUSION: This study provides novel insight in the molecular mechanism of thyroid carcinoma development in dogs. German longhaired pointers carrying GNAS mutations in the tumor may be used as a disease model for the development and testing of novel therapies to kill the tumor with somatic mutations in the GNAS gene.

PurposePatients with non-small cell lung cancer (NSCLC) that harbor driver mutations are associated with a cancer diagnosis at a younger age. While targeted therapies provide deep remissions and durable benefit in a subset of patients, it is unclear whether targeted therapies bridge the gap in years of life lost (YLL) in these younger NSCLC patients with targetable mutations in comparison to generally older NSCLC patients without actionable driver mutations.Materials and methodsRetrospective cross-sectional study using landmark trials leading to the approval of targeted therapies in NSCLC with actionable mutations. We evaluated all targeted therapies as well as chemotherapy and IO regimens for the treatment of NSCLC through FDA Oncology Announcements and NCCN Guidelines for NSCLC (version 4.2021).ResultsWe estimated the YLL for each driver mutation, cumulative median duration of response (DOR) with targeted therapies by mutation type, and percentage of estimated improvement in YLL from NSCLC targeted therapies. The median ages at diagnosis (in years) for patients whose tumors express targetable mutations were: 47.6 (NTRK); 52.0 (ALK); 62.0 (HER2); 57.0 (ROS1); 61.4 (RET); 63.0 (BRAF); 69.0 (EGFR); and 72.0 (MET). For comparison, the median age at diagnosis for patients without driver mutations, regardless of PD-L1 status was 71 years. The median DOR (in years) for patients whose tumors express the same mutations include: 0.9 (NTRK); 3.9 (ALK); 0.6 (HER2); 6.2 (ROS1); 2.2 (RET); 1.5 (BRAF); 3.1 (EGFR); and 2.4 (MET). The median DOR for patients without driver mutations was 1.2 years. The cumulative estimated survival time (years; median age at diagnosis plus the median DOR or OS) for patients whose tumors express targetable mutations were: 48.5 (NTRK); 55.9 (ALK); 62.6 (HER2); 63.2 (ROS1); 63.6 (RET); 64.5 (BRAF); 72.1 (EGFR); and 74.4 (MET). The cumulative estimated survival time for patients without driver mutations, regardless of PD-L1 status, was 72.2&n

Purpose: To establish a clinically applicable genomic clustering system, we investigated the interactive landscape of driver mutations in intrahepatic cholangiocarcinoma (ICC). Methods: The genomic data of 1481 ICCs from diverse populations was analyzed to investigate the pair-wise co-occurrences or mutual exclusivities among recurrent driver mutations. Clinicopathological features and outcomes were compared among different clusters. Gene expression and DNA methylation profiling datasets were analyzed to investigate the molecular distinctions among mutational clusters. ICC cell lines with different gene mutation backgrounds were used to evaluate the cluster specific biological behaviors and drug sensitivities. Results: Statistically significant mutation-pairs were identified across 21 combinations of genes. Seven most recurrent driver mutations (TP53, KRAS, SMAD4, IDH1/2, FGFR2-fus and BAP1) showed pair-wise co-occurrences or mutual exclusivities and could aggregate into three genetic clusters: Cluster1: represented by tripartite interaction of KRAS, TP53 and SMAD4 mutations, exhibited large bile duct histological phenotype with high CA19-9 level and dismal prognosis; Cluster2: co-association of IDH/BAP1 or FGFR2-fus/BAP1 mutation, was characterized by small bile duct phenotype, low CA19-9 level and optimal prognosis; Cluster3: mutation-free ICC cases with intermediate clinicopathological features. These clusters showed distinct molecular traits, biological behaviors and responses to therapeutic drugs. Finally, we identified S100P and KRT17 as “cluster-specific”, “lineage-dictating” and “prognosis-related” biomarkers, which in combination with CA19-9 could well stratify Cluster3 ICCs into two biologically and clinically distinct subtypes. Conclusions: This clinically applicable clustering system can be instructive to ICC prognostic stratification, molecular classification, and therapeutic optimization.

Cancer driver mutations often display mutual exclusion or co-occurrence, underscoring the key role of epistasis in carcinogenesis. However, estimating the magnitude of epistasis and quantifying its effect on tumor evolution remains a challenge. We develop a method (Coselens) to quantify conditional selection on the excess of nonsynonymous substitutions in cancer genes. Coselens infers the number of drivers per gene in different partitions of a cancer genomics dataset using covariance-based mutation models and determines whether coding mutations in a gene affect selection for drivers in any other gene. Using Coselens, we identify 296 conditionally selected gene pairs across 16 cancer types in the TCGA dataset. Conditional selection affects 25%-50% of driver substitutions in tumors with >2 drivers. Conditionally co-selected genes form modular networks, whose structures challenge the traditional interpretation of within-pathway mutual exclusivity and across-pathway synergy, suggesting a more complex scenario where gene-specific across-pathway epistasis shapes differentiated cancer subtypes.

The active layer morphology transition of organic photovoltaics under non-equilibrium conditions are of vital importance in determining the device power conversion efficiency and stability; however, a general and unified picture on this issue has not been well addressed. Using combined in situ and ex situ morphology characterizations, morphological parameters relating to kinetics and thermodynamics of morphology evolution are extracted and studied in model systems under thermal annealing. The coupling and competition of crystallization and demixing are found to be critical in morphology evolution, phase purification and interfacial orientation. A unified model summarizing different phase diagrams and all possible kinetic routes is proposed. The current observations address the fundamental issues underlying the formation of the complex multi-length scale morphology in bulk heterojunction blends and provide useful morphology optimization guidelines for processing devices with higher efficiency and stability. © 2021, The Author(s).

Background: Adrenocortical carcinoma (ACC) is a rare, often-aggressive neoplasm of the adrenal cortex, with a 14–17 month median overall survival. We asked whether tumors from patients with advanced or metastatic ACC would offer clues as to putative genes that might have critical roles in disease progression or in more aggressive disease biology. Methods: We conducted comprehensive genomic and expression analyses of ACCs from 43 patients, 30 female, and 42 from metastatic sites, including deep sequencing, copy number analysis, mRNA expression and microRNA arrays. Results: Copy number gains and losses were similar to that previously reported for ACC. We identified a median mutation rate of 3.38 per megabase (Mb). The mutational signature was characterized by a predominance of C > T, C > A and T > C transitions. Only cancer genes TP53 (26%) and beta-catenin (CTNNB1, 14%) were mutated in more than 10% of samples. The TCGA-identified putative cancer genes MEN1 and PRKAR1A were found in low frequency—4.7 and 2.3%, respectively. The majority of the mutations were in genes not implicated in the etiology or maintenance of cancer. Specifically, amongst the 38 genes that were mutated in more than 9% of samples, only four were represented in Tier 1 of the 576 COSMIC Cancer Gene Census (CCGC). Thus, 82% of genes found to have mutations likely have no role in the etiology or biology of ACC; while the role of the other 18%, if any, remains to be proven. Finally, the transcript length for the 38 most frequently mutated genes in ACC is statistically longer than the average of all coding genes, raising the question of whether transcript length in part determined mutation probability. Conclusions: We conclude that the mutational and expression profiles of advanced and metastatic tumors are very similar to those from newly diagnosed patients—with very little in the way of genomic aberration to explain differences in biology. With relatively low mutation rates, few major on

The next generation sequencing (NGS) applied to liquid biopsy is useful to determine the biomolecular identity of the prevalent neoplastic cell population. The sensitivity of ALK detection in liquid biopsy is comparable to that showed by the gold standard tissue biopsy and its usefulness is demonstrated in clinical practice by the similar efficacy of ALK TKIs to obtain prolonged disease control. ALK ve+ lung cancer today presents a large number of therapeutic opportunities leading to a long/term survival. Correct evaluation of ALK translocation is a paramount in order to guide the correct therapeutic strategy as illustrated in the present clinical case.

Enormous amounts of childhood thyroid cancers, mostly childhood papillary thyroid carcinomas (PTCs), after the Chernobyl nuclear power plant accident have revealed a mutual relationship between the radiation exposure and thyroid cancer development. While the internal exposure to radioactive 131I is involved in the childhood thyroid cancers after the Chernobyl accident,people exposed to the external radiation, such as atomic-bomb (A-bomb) survivors, and the patients who received radiation therapy, have also been epidemiologically demonstrated to develop thyroid cancers. In order to elucidate the mechanisms of radiation-induced carcinogenesis, studies have aimed at defining the molecular changes associated with the thyroid cancer development. Here,we overview the literatures towards the identification of oncogenic alterations, particularly gene rearrangements, and discuss the existence of radiation signatures associated with radiation-induced thyroid cancers., Cancers, 11(9), art.no.1290; 2019

Hippo signaling has been recognized as a key tumor suppressor pathway. Here, we perform a comprehensive molecular characterization of 19 Hippo core genes in 9,125 tumor samples across 33 cancer types using multidimensional "omic" data from The Cancer Genome Atlas. We identify somatic drivers among Hippo genes and the related microRNA (miRNA) regulators, and using functional genomic approaches, we experimentally characterize YAP and TAZ mutation effects and miR-590 and miR-200a regulation for TAZ. Hippo pathway activity is best characterized by a YAP/TAZ transcriptional target signature of 22 genes, which shows robust prognostic power across cancer types. Our elastic-net integrated modeling further reveals cancer-type-specific pathway regulators and associated cancer drivers. Our results highlight the importance of Hippo signaling in squamous cell cancers, characterized by frequent amplification of YAP/TAZ, high expression heterogeneity, and significant prognostic patterns. This study represents a systems-biology approach to characterizing key cancer signaling pathways in the post-genomic era.

The evolutionary features of clear-cell renal cell carcinoma (ccRCC) have not been systematically studied to date. We analyzed 1,206 primary tumor regions from 101 patients recruited into the multi-center prospective study, TRACERx Renal. We observe up to 30 driver events per tumor and show that subclonal diversification is associated with known prognostic parameters. By resolving the patterns of driver event ordering, co-occurrence, and mutual exclusivity at clone level, we show the deterministic nature of clonal evolution. ccRCC can be grouped into seven evolutionary subtypes, ranging from tumors characterized by early fixation of multiple mutational and copy number drivers and rapid metastases to highly branched tumors with > 10 subclonal drivers and extensive parallel evolution associated with attenuated progression. We identify genetic diversity and chromosomal complexity as determinants of patient outcome. Our insights reconcile the variable clinical behavior of ccRCC and suggest evolutionary potential as a biomarker for both intervention and surveillance.

Genetic instability is an important characteristic of cancer. While most cancers develop genetic instability at some stage of their progression, sometimes a temporary rise of instability is followed by the return to a relatively stable genome. Neither the reasons for these dynamics, nor, more generally, the role of instability in tumor progression, are well understood. In this paper we develop a class of mathematical models to study the evolutionary competition dynamics among different sub-populations in a heterogeneous tumor. We observe that despite the complexity of this multi-component and multi-process system, there is only a small number of scenarios expected in the context of the evolution of instability. If the penalty incurred by unstable cells (the decrease in the growth due to deleterious mutations) is high compared with the gain (the production rate of advantageous mutations), then instability does not evolve. In the opposite case, instability evolves and comes to dominate the system. In the intermediate parameter regime, instability is generated but later gives way to stable clones. Moreover, the model also informs us of the patterns of instability for cancer lineages corresponding to different stages of progression. It is predicted that mutations causing instability are merely "passengers" in tumors that have undergone only a small number of malignant mutations. Further down the path of carcinogenesis, however, unstable cells are more likely to give rise to the winning clonal wave that takes over the tumor and carries the evolution forward, thus conferring a causal role of the instability in such cases. Further, each individual clonal wave (i.e. cells harboring a fixed number of malignant driver mutations) experiences its own evolutionary history. It can fall under one of three types of temporal behavior: stable throughout, unstable to stable, or unstable throughout. Which scenario is realized depends on the subtle (but predictable) interplay among muta