Narrow genetic basis for the Australian dingo confirmed through analysis of paternal ancestry

The dingo (Canis lupus dingo) is an iconic animal in the native culture of Australia, but archaeological and molecular records indicate a relatively recent history on the continent. Studies of mitochondrial DNA (mtDNA) imply that the current dingo population was founded by a small population of already tamed dogs from Southeast Asia. However, the maternal genetic data might give a unilateral picture, and the gene pool has yet to be screened for paternal ancestry. We sequenced 14,437 bp of the Y-chromosome (Y-chr) from two dingoes and one New Guinea Singing Dog (NGSD). This positioned dingo and NGSD within the domestic dog Y-chr phylogeny, and produced one haplotype not detected before. With this data, we characterized 47 male dingoes in 30 Y-chr single-nucleotide polymorphism sites using protease-mediated allele-specific extension technology. Only two haplotypes, H3 and H60, were found among the dingoes, at frequencies of 68.1 and 31.9 %, respectively, compared to 27 haplotypes previously established in the domestic dog. While H3 is common among Southeast Asian dogs, H60 was specifically found in dingoes and the NGSD, but was related to Southeast Asian dog Y-chr haplotypes. H3 and H60 were observed exclusively in the western and eastern parts of Australia, respectively, but had a common range in Southeast. Thus, the Y-chr diversity was very low, similar to previous observations for d-loop mtDNA. Overall genetic evidence suggests a very restricted introduction of the first dingoes into Australia, possibly from New Guinea. This study further confirms the dingo as an isolated feral dog. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s10709-012-9658-5) contains supplementary material, which is available to authorized users

Pitfalls in machine learning‐based assessment of tumor‐infiltrating lymphocytes in breast cancer: a report of the international immuno‐oncology biomarker working group

The clinical significance of the tumor-immune interaction in breast cancer (BC) has been well established, and tumor-infiltrating lymphocytes (TILs) have emerged as a predictive and prognostic biomarker for patients with triple-negative (estrogen receptor, progesterone receptor, and HER2 negative) breast cancer (TNBC) and HER2-positive breast cancer. How computational assessment of TILs can complement manual TIL-assessment in trial- and daily practices is currently debated and still unclear. Recent efforts to use machine learning (ML) for the automated evaluation of TILs show promising results. We review state-of-the-art approaches and identify pitfalls and challenges by studying the root cause of ML discordances in comparison to manual TILs quantification. We categorize our findings into four main topics; (i) technical slide issues, (ii) ML and image analysis aspects, (iii) data challenges, and (iv) validation issues. The main reason for discordant assessments is the inclusion of false-positive areas or cells identified by performance on certain tissue patterns, or design choices in the computational implementation. To aid the adoption of ML in TILs assessment, we provide an in-depth discussion of ML and image analysis including validation issues that need to be considered before reliable computational reporting of TILs can be incorporated into the trial- and routine clinical management of patients with TNBC

Image-based multiplex immune profiling of cancer tissues : translational implications. A report of the International Immuno-oncology Biomarker Working Group on Breast Cancer

Recent advances in the field of immuno-oncology have brought transformative changes in the management of cancer patients. The immune profile of tumours has been found to have key value in predicting disease prognosis and treatment response in various cancers. Multiplex immunohistochemistry and immunofluorescence have emerged as potent tools for the simultaneous detection of multiple protein biomarkers in a single tissue section, thereby expanding opportunities for molecular and immune profiling while preserving tissue samples. By establishing the phenotype of individual tumour cells when distributed within a mixed cell population, the identification of clinically relevant biomarkers with high-throughput multiplex immunophenotyping of tumour samples has great potential to guide appropriate treatment choices. Moreover, the emergence of novel multi-marker imaging approaches can now provide unprecedented insights into the tumour microenvironment, including the potential interplay between various cell types. However, there are significant challenges to widespread integration of these technologies in daily research and clinical practice. This review addresses the challenges and potential solutions within a structured framework of action from a regulatory and clinical trial perspective. New developments within the field of immunophenotyping using multiplexed tissue imaging platforms and associated digital pathology are also described, with a specific focus on translational implications across different subtypes of cancer.Gilead Breast Cancer Research Grant; Breast Cancer Research Foundation; Susan G Komen Leadership; Interne Fondsen KU Leuven/Internal Funds KU Leuven; Swedish Society for Medical Research; Swedish Breast Cancer Association; Cancer Research Program; US Department of Defense; Mayo Clinic Breast Cancer; Marie Sklodowska Curie; NHMRC; National Institutes of Health; Cancer Research UK; Japan Society for the Promotion of Science; Horizon 2020 European Union Research and Innovation Programme National Cancer Institute; National Heart, Lung and Blood Institute; National Institute of Biomedical Imaging and Bioengineering; VA Merit Review Award; US Department of Veterans Affairs Biomedical Laboratory Research Breast Cancer Research Program; Prostate Cancer Research Program; Lung Cancer Research Program; Kidney Precision Medicine Project (KPMP) Glue Grant; EPSRC; Melbourne Research Scholarship; Peter MacCallum Cancer Centre; KWF Kankerbestrijding; Dutch Ministry of Health, Welfare and Sport the Breast Cancer Research Foundation; Agence Nationale de la Recherche; Q-Life; National Breast Cancer Foundation of Australia; National Health and Medical Council of Australia; All-Island Cancer Research Institute; Irish Cancer Society; Science Foundation Ireland Investigator Programme; Science Foundation Ireland Strategic Partnership Programme. Open access funding provided by IReL.https://pathsocjournals.onlinelibrary.wiley.com/journal/10969896hj2024ImmunologySDG-03:Good heatlh and well-bein

Image-based multiplex immune profiling of cancer tissues: translational implications. A report of the International Immuno-oncology Biomarker Working Group on Breast Cancer

Recent advances in the field of immuno-oncology have brought transformative changes in the management of cancer patients. The immune profile of tumours has been found to have key value in predicting disease prognosis and treatment response in various cancers. Multiplex immunohistochemistry and immunofluorescence have emerged as potent tools for the simultaneous detection of multiple protein biomarkers in a single tissue section, thereby expanding opportunities for molecular and immune profiling while preserving tissue samples. By establishing the phenotype of individual tumour cells when distributed within a mixed cell population, the identification of clinically relevant biomarkers with high-throughput multiplex immunophenotyping of tumour samples has great potential to guide appropriate treatment choices. Moreover, the emergence of novel multi-marker imaging approaches can now provide unprecedented insights into the tumour microenvironment, including the potential interplay between various cell types. However, there are significant challenges to widespread integration of these technologies in daily research and clinical practice. This review addresses the challenges and potential solutions within a structured framework of action from a regulatory and clinical trial perspective. New developments within the field of immunophenotyping using multiplexed tissue imaging platforms and associated digital pathology are also described, with a specific focus on translational implications across different subtypes of cancer

Spatial analyses of immune cell infiltration in cancer : current methods and future directions. A report of the International Immuno-Oncology Biomarker Working Group on Breast Cancer

Modern histologic imaging platforms coupled with machine learning methods have provided new opportunities to map the spatial distribution of immune cells in the tumor microenvironment. However, there exists no standardized method for describing or analyzing spatial immune cell data, and most reported spatial analyses are rudimentary. In this review, we provide an overview of two approaches for reporting and analyzing spatial data (raster versus vector-based). We then provide a compendium of spatial immune cell metrics that have been reported in the literature, summarizing prognostic associations in the context of a variety of cancers. We conclude by discussing two well-described clinical biomarkers, the breast cancer stromal tumor infiltrating lymphocytes score and the colon cancer Immunoscore, and describe investigative opportunities to improve clinical utility of these spatial biomarkers. © 2023 The Pathological Society of Great Britain and Ireland.http://www.thejournalofpathology.com/hj2024ImmunologySDG-03:Good heatlh and well-bein

Pitfalls in machine learning-based assessment of tumor-infiltrating lymphocytes in breast cancer: A report of the International Immuno-Oncology Biomarker Working Group on Breast Cancer

The clinical significance of the tumor-immune interaction in breast cancer is now established, and tumor-infiltrating lymphocytes (TILs) have emerged as predictive and prognostic biomarkers for patients with triple-negative (estrogen receptor, progesterone receptor, and HER2-negative) breast cancer and HER2-positive breast cancer. How computational assessments of TILs might complement manual TIL assessment in trial and daily practices is currently debated. Recent efforts to use machine learning (ML) to automatically evaluate TILs have shown promising results. We review state-of-the-art approaches and identify pitfalls and challenges of automated TIL evaluation by studying the root cause of ML discordances in comparison to manual TIL quantification. We categorize our findings into four main topics: (1) technical slide issues, (2) ML and image analysis aspects, (3) data challenges, and (4) validation issues. The main reason for discordant assessments is the inclusion of false-positive areas or cells identified by performance on certain tissue patterns or design choices in the computational implementation. To aid the adoption of ML for TIL assessment, we provide an in-depth discussion of ML and image analysis, including validation issues that need to be considered before reliable computational reporting of TILs can be incorporated into the trial and routine clinical management of patients with triple-negative breast cancer

Molecular Profiling of the Population Dynamics : Foundation and Expansion of an Archaic Domesticate

"An ‘exponential growth of science’ throughout modern history has been frequently boasted by numerous narcissistic accounts of ‘modern humanity.’ Nonetheless, ‘modern science’ seems to have overwhelmingly compromised on its original promises by fitting into an ‘industrial scheme.’ With this concern, ‘molecular phylogeographics with conservational ambitions’ would look an intact ground for research efforts in a ‘school of biotechnology.’ The dog (Canis familiaris) as an earliest domestic animal has a history of conflicts over its origins and dispersal. Having those disputes addressed, valuable knowledge could be acquired on the nature and dynamics of domestication, and of human societies particularly of pre-agricultural ages. We employed two most widely-used genealogical markers, the mitochondrial DNA (mtDNA) and the non-recombining portion of the Y-chromosome (NRY), to address dog demography. Through 582 bps of mtDNA Control Region, complemented with whole mitochondrial genomes, it was established that almost all maternal lineages of the domestic dog worldwide coalesce to a population of at least 51 and perhaps many more female wolves in Asia South of Yangtze River (ASY) approximately 16,000 years before present (BP). This was based on the presence of a maximal diversity in this area, a descending gradient of diversity outward it, and a ubiquitous population structure everywhere in the world. A closer examination of this portrait in Southwest Asia (SwAsia) and the Fertile Crescent (FC), a region which has supplied persuasive evidence on early presence of the domestic dog, retrieved the same information, with implications for backbreeding with the local wolf population. Meanwhile, analyses of mtDNA dispersal showed that dogs took the long way via land to Madagascar Island, and not together with humans via sea. By the other approach, the NRY data in 14,437 bps length supplemented the mtDNA in reporting the height of diversity from ASY with a founding population of at least 13 male wolves, but expectably produced lower inter-regional differentiation by diversity. Screening of NRY by a SNP assay in the dingoes of Australia Island as a population of feral dogs revealed restricted and similar dispersal patterns for sires and dams. Prospects of ancient, multilocus and whole genome assays with the emerging high-throughput technologies has still more to promise on finer elaborations of these issues."QC 20120529</p

Effect of ion partitioning on the electrostatics of soft particles with a volumetrically charged core

In most studies of the electrostatics of soft particles, the permittivities of the shell and the electrolyte are assumed to be equal so the ion partitioning effect, arising from the permittivity difference between these two media, can be neglected. On the other hand, recent investigations have revealed that considering the volumetric charge and finite permittivity of the rigid core results in more realistic descriptions of the electrostatics of biological particles. Here, the simultaneous impact of ion partitioning and core volumetric charge on the electrostatics of spherical soft particles is studied using theoretical methods. The equations governing the general case are solved numerically, and analytical expressions are also derived using the Debye–Hückel linearization, which are found to be accurate even in the presence of large core charges. It is observed that, whenever there is a difference between the permittivities of two neighboring media, there is a noticeable change in the slope of the electrostatic potential profile at the interface, with the result that the electrostatic potential distribution of the system deviates from literature predictions. Based on these findings, it is strongly recommended to take the effect of ion partitioning into account when studying the electrostatics of soft particles, especially in the case of low-shell permittivity and concentrated electrolytes. Keywords: Electrostatics, Soft particle, Ion partitioning, Core charge, Analytical expressio