Genomics-Guided Immunotherapy for Precision Medicine in Cancer

CT Texture Analysis in Breast Cancer Patients Undergoing CT-Guided Bone Biopsy: Correlations With Histopathology

Background

Texture analysis has the potential to deliver quantitative imaging markers. Patients receiving computed tomography (CT)-guided percutaneous bone biopsies could be characterized using texture analysis derived from CT. Especially for breast cancer (BC) patients, it could be crucial to better predict the outcome of the biopsy to better reflect the immunohistochemistry status of the tumor.

Objectives

The present study examined the relationship between texture features and outcomes in patients with BC receiving CT-guided bone biopsies.

Design

This study is based on a retrospective analysis.

Methods

The present study included a total of 66 patients. All patients proceeded to undergo a CT-guided percutaneous bone biopsy, using an 11-gauge coaxial needle. Clinical and imaging characteristics as well as CT texture analysis were included in the analysis. Logistic regression analysis was performed to predict negative biopsy results.

Results

Overall, 33 patients had osteolytic metastases (50%) and 33 had osteoblastic metastases (50%). The overall positivity rate for the biopsy was 75%. The clinical model exhibited a predictive accuracy for a positive biopsy result, as indicated by an area under the curve (AUC) of 0.73 [95% confidence interval (CI) = 0.63-0.83]. Several CT texture features were different between Luminal A and Luminal B cancers; the best discrimination was reached for "WavEnHH_s-3" with a P-value of .002. When comparing triple-negative to non-triple-negative cancers, several CT texture features were different, the best discrimination achieved "S(5,5)SumVarnc" with a P-value of .01. For the Her 2 discrimination, only 3 parameters reached statistical significance, "S(4,-4)SumOfSqs" with a P-value of .01.

Conclusions

The utilization of CT texture features may facilitate a more accurate characterization of bone metastases in patients with BC. There is the potential to predict the immunohistochemical subtype with a high degree of accuracy. The identified parameters may prove useful in clinical decision-making and could help to identify patients at risk of a negative biopsy result.

India's Potential as a Leader in Cancer Care Progress in the Future: A Synthetic Interdisciplinary Perspective

This paper comprehensively analyzes India's potential to become a leader in cancer care in the Global South, particularly in precision population cancer medicine (PPCM). Through an interdisciplinary lens, it examines the current landscape of cancer care in India, highlighting its strengths, weaknesses, opportunities, and threats in this domain. This review explores the concept of knowledge translation and its importance in bridging the gap between knowledge generation and implementation in medical sciences and applies this to the Indian healthcare scenario. The review then delves into India's technological prowess, exemplified by its digital health initiatives such as the CoWIN (winning over COVID-19) app and the Ayushman Bharat Digital Mission, which provide a strong foundation for leveraging advanced technologies in healthcare. The authors discuss India's pharmaceutical industry, often referred to as the "pharmacy of the world," emphasizing its crucial role in global drug manufacturing and distribution. It also examines the country's emerging genomic research landscape, including initiatives such as GenomeIndia and the Indian Cancer Genome Atlas Foundation, which are pivotal for advancing personalized medicine. A significant portion of the review is dedicated to analyzing India's clinical trial ecosystem. It traces the evolution of regulatory frameworks governing clinical research in the country and highlights recent reforms that have made India an increasingly attractive destination for global studies, the potential adoption of innovative trial designs and artificial intelligence (AI)-driven analyses. Crucially, the authors confront the formidable obstacles inherent in India's complex healthcare landscape, illuminating the unique challenges that must be overcome. The review acknowledges India's underrepresentation in global clinical trials despite its large population and significant cancer burden. The issue of financial toxicity in cancer care is discussed, underscoring the need for affordable treatment options. The study also points out the nascent state of India's genomic databases, which account for only a small percentage of global genetic data. Despite these challenges, the authors posit that by effectively leveraging its information technology (IT) infrastructure, robust pharmaceutical sector, and large, diverse population, India has the potential to develop unique, country-specific solutions for cancer care. The study suggests that by fostering genomic research, strategically reforming its clinical trial ecosystem, and harnessing its digital capabilities, India could transform its cancer care landscape and emerge as a model for other developing nations in the Global South. In essence, this paper provides a roadmap for India's journey towards becoming a leader in PPCM, offering valuable insights for policymakers, healthcare professionals, and researchers in the field of oncology and precision medicine. Indeed, by using PPCM as a "pilot project," India can learn to use its new strategies to improve non-cancer care disease prevention, early detection, and improved and more cost-effective management. This approach could revolutionize cancer care in India and serve as a model for other developing nations in the Global South. By leveraging the strategies and technologies developed for PPCM, India could significantly enhance its healthcare system, highlighting the importance and urgency of improving cancer care in the region.

Impact of quantitative CT texture analysis on the outcome of CT-guided bone biopsy

Texture analysis can provide new imaging-based biomarkers. Texture analysis derived from computed tomography (CT) might be able to better characterize patients undergoing CT-guided percutaneous bone biopsy. The present study evaluated this and correlated texture features with bioptic outcome in patients undergoing CT-guided bone biopsy. Overall, 123 patients (89 female patients, 72.4 %) were included into the present study. All patients underwent CT-guided percutaneous bone biopsy with an 11 Gauge coaxial needle. Clinical parameters and quantitative imaging features were investigated. Random forest classifier was used to predict a positive biopsy result. Overall, 69 patients had osteolytic metastasis (56.1 %) and 54 had osteoblastic metastasis (43.9 %). The overall positive biopsy rate was 72 %. The developed radiomics model demonstrated a prediction accuracy of a positive biopsy result with an AUC of 0.75 [95 %CI 0.65 - 0.85]. In a subgroup of breast cancer patients, the model achieved an AUC of 0.85 [95 %CI 0.73 - 0.96]. In the subgroup of non-breast cancer patients, the signature achieved an AUC of 0.80 [95 %CI 0.60 - 0.99]. Quantitative CT imaging findings comprised of conventional and texture features can aid to predict the bioptic result of CT-guided bone biopsies. The developed radiomics signature aids in clinical decision-making, and could identify patients at risk for a negative biopsy.

Real-world comprehensive genomic and immune profiling reveals distinct age- and sex-based genomic and immune landscapes in tumors of patients with non-small cell lung cancer

Introduction

Younger patients with non-small cell lung cancer (NSCLC) (<50 years) represent a significant patient population with distinct clinicopathological features and enriched targetable genomic alterations compared to older patients. However, previous studies of younger NSCLC suffer from inconsistent findings, few studies have incorporated sex into their analyses, and studies targeting age-related differences in the tumor immune microenvironment are lacking.

Methods

We performed a retrospective analysis of 8,230 patients with NSCLC, comparing genomic alterations and immunogenic markers of younger and older patients while also considering differences between male and female patients. We defined older patients as those ≥65 years and used a 5-year sliding threshold from <45 to <65 years to define various groups of younger patients. Additionally, in an independent cohort of patients with NSCLC, we use our observations to inform testing of the combinatorial effect of age and sex on survival of patients given immunotherapy with or without chemotherapy.

Results

We observed distinct genomic and immune microenvironment profiles for tumors of younger patients compared to tumors of older patients. Younger patient tumors were enriched in clinically relevant genomic alterations and had gene expression patterns indicative of reduced immune system activation, which was most evident when analyzing male patients. Further, we found younger male patients treated with immunotherapy alone had significantly worse survival compared to male patients ≥65 years, while the addition of chemotherapy reduced this disparity. Contrarily, we found younger female patients had significantly better survival compared to female patients ≥65 years when treated with immunotherapy plus chemotherapy, while treatment with immunotherapy alone resulted in similar outcomes.

Discussion

These results show the value of comprehensive genomic and immune profiling (CGIP) for informing clinical treatment of younger patients with NSCLC and provides support for broader coverage of CGIP for younger patients with advanced NSCLC.

Silencing immune-infiltrating biomarker CCDC80 inhibits malignant characterization and tumor formation in gastric cancer

OBJECTIVE

Tumor immune infiltration leads to poor prognosis of gastric cancer patients and seriously affects the life quality of gastric cancer patients. This study was based on bioinformatics to screen prognostic biomarkers in patients with high degree of immune invasion of gastric cancer. Meanwhile, the action of biomarker CCDC80 was explored in gastric cancer by cell and tumorigenesis experiments, to provide reference for the cure of gastric cancer patients.

METHODS

Data sets and clinical massage on gastric cancer were collected from TCGA database and GEO database. ConsensusClusterPlus was used to cluster gastric cancer patients based on the 28 immune cells infiltration in ssGSEA. R "Limma" package was applied to analyze differential mRNAs between Cluster 1 and Cluster 2. Differential expression genes were screened by single factor analysis. Stemness markers (SERPINF1, DCN, CCDC80, FBLN5, SPARCL1, CCL14, DPYSL3) were identified for differential expression genes. Prognostic value of CCDC80 was evaluated in gastric cancer. Differences in genomic mutation and tumor microenvironment immune infiltration were assessed between high or low CCDC80. Finally, gastric cancer cells (HGC-27 and MKN-45) were selected to evaluate the action of silencing CCDC80 on malignant characterization, macrophage polarization, and tumor formation.

RESULTS

Bioinformatics analysis showed that CCDC80, as a stemness marker, was significantly overexpressed in gastric cancer. CCDC80 was also related to the degree of gastric cancer immune invasion. CCDC80 was up-expressed in cells of gastric cancer. Silencing CCDC80 inhibited malignant characterization and subcutaneous tumor formation of gastric cancer cells. High expression of CCDC80 was positive correspondence with immune invasion. Silencing CCDC80 inhibited M2 polarization and promoted M1 polarization in tumor tissues. In addition, gastric cancer patients were likely to have mutations in CDH1, ACTRT1, GANAB, and CDH10 genes in the High-CCDC80 group.

CONCLUSION

Silencing CCDC80, a prognostic biomarker in patients with immune invasion of gastric cancer, could effectively inhibit the malignant characterization, M2 polarization, and tumor formation of gastric cancer.

Revolutionizing personalized cancer treatment: the synergy of next-generation sequencing and CRISPR/Cas9

In the context of cancer heterogeneity, the synergistic action of next-generation sequencing (NGS) and CRISPR/Cas9 plays a promising role in the personalized treatment of cancer. NGS enables high-throughput genomic profiling of tumors and pinpoints specific mutations that primarily lead to cancer. Oncologists use this information obtained from NGS in the form of DNA profiling or RNA analysis to tailor precision strategies based on an individual's unique molecular signature. Furthermore, the CRISPR technique enables precise editing of cancer-specific mutations, allowing targeted gene modifications. Harnessing the potential insights of NGS and CRISPR/Cas9 heralds a remarkable frontier in cancer therapeutics with unprecedented precision, effectiveness and minimal off-target effects.

Comprehensive pan-cancer analysis: essential role of ABCB family genes in cancer

Background

The adenosine triphosphate-binding-cassette (ABC) transporter orchestrates the transmembrane transport of diverse substrates with the aid of ATP as an energy source. ABC transporter constitutes a widespread superfamily of transporters prominently present on the cellular membrane of organisms. Advancements in understanding have unveiled additional roles beyond mere intracellular or extracellular transport functions for the ABC protein family, encompassing involvement in DNA repair, protein translation, and gene expression regulation. Yet its role in tumors is still unknown.

Methods

This study drew support from multiple databases, including Gene Expression Omnibus (GEO), European Genome-phenome Archive (EGA), The Cancer Genome Atlas (TCGA), and employed multidimensional bioinformatics analyses, incorporating online databases and the R-project. Through a comprehensive analysis, we seek to discern transcriptional-level disparities among genes and their consequential impacts on prognosis, tumor microenvironment (TME), stemness score, immune subtypes, clinical characteristics, and drug sensitivity across human cancers.

Results

ABC transporter subfamily B (ABCB) family genes exhibited heightened expression across diverse tumors, demonstrating a significant correlation with overall prognosis in pan-cancer contexts. Notably, gene expression levels manifested substantial associations with TME, stemness score, immune subtypes, clinical characteristics, and drug sensitivity in specific cancers, including kidney renal papillary cell carcinoma (KIRP), liver hepatocellular carcinoma (LIHC), and pancreatic adenocarcinoma (PAAD). Within this subset, transporter associated with antigen processing 1 (TAP1), TAP2, and ABCB6 emerged as noteworthy oncogenes.

Conclusions

The outcomes of this study contribute to a comprehensive understanding of the implications of ABCB family genes in tumor progression, offering insights into potential therapeutic targets for cancer. Notably, the identification of ABCB6 as a significant oncogene suggests promising avenues for targeted therapies in KIRP, LIHC, and PAAD.

Molecular insights into clinical trials for immune checkpoint inhibitors in colorectal cancer: Unravelling challenges and future directions

Colorectal cancer (CRC) is a complex disease with diverse etiologies and clinical outcomes. Despite considerable progress in development of CRC therapeutics, challenges remain regarding the diagnosis and management of advanced stage metastatic CRC (mCRC). In particular, the five-year survival rate is very low since mCRC is currently rarely curable. Over the past decade, cancer treatment has significantly improved with the introduction of cancer immunotherapies, specifically immune checkpoint inhibitors. Therapies aimed at blocking immune checkpoints such as PD-1, PD-L1, and CTLA-4 target inhibitory pathways of the immune system, and thereby enhance anti-tumor immunity. These therapies thus have shown promising results in many clinical trials alone or in combination. The efficacy and safety of immunotherapy, either alone or in combination with CRC, have been investigated in several clinical trials. Clinical trials, including KEYNOTE-164 and CheckMate 142, have led to Food and Drug Administration approval of the PD-1 inhibitors pembrolizumab and nivolumab, respectively, for the treatment of patients with unresectable or metastatic microsatellite instability-high or deficient mismatch repair CRC. Unfortunately, these drugs benefit only a small percentage of patients, with the benefits of immunotherapy remaining elusive for the vast majority of CRC patients. To this end, primary and secondary resistance to immunotherapy remains a significant issue, and further research is necessary to optimize the use of immunotherapy in CRC and identify biomarkers to predict the response. This review provides a comprehensive overview of the clinical trials involving immune checkpoint inhibitors in CRC. The underlying rationale, challenges faced, and potential future steps to improve the prognosis and enhance the likelihood of successful trials in this field are discussed.

Distinct tumor microenvironment landscapes in gastric cancer classified by cuproptosis-related lncRNAs

Cuproptosis is a newly discovered non-apoptotic form of cell death that may be related to the development of tumors. Nonetheless, the potential role of cuproptosis-related lncRNAs in tumor microenvironment (TME) formation and patient-tailored treatment optimization of gastric cancer (GC) is still unclear. In this study, the six-lncRNA signature was constructed to quantify the molecular patterns of GC using LASSO-Cox regression model. Receiver operating characteristic (ROC) curves, C-index curves, independent prognostic analysis and principal component analysis (PCA) were conducted to verify and evaluate the model. The results showed that this risk model was accurate and reliable in predicting GC patient survival. In addition, two distinct subgroups were identified based on the risk model, which showed significant difference in biological functions of the associated genes, TME scores, characteristics of infiltrating immune cells and immunotherapy responses. We found that the high-risk subgroup was associated with immune activation and tumor-related pathways. Furthermore, compared with the low-risk subgroup, the high-risk subgroup had higher TME scores, richer immune cell infiltration and a better immunotherapy response. To accurately identify immune cold tumors and hot tumors, all samples of GC were divided into four distinct clusters by consensus clustering. Among them, Cluster 3 was identified as an immune hot tumor and was more sensitive to immunotherapy. Overall, this study demonstrates that cuproptosis-related lncRNAs could accurately predict the prognosis of patients with GC, help make a distinction between immune cold tumors and hot tumors and provide a basis for the precision medicine of GC.

Optimising CT-guided biopsies of sclerotic bone lesions in cancer patients

Objectives

Investigate the laboratory, imaging and procedural factors that are associated with a tumour-positive and/or NGS-feasible CT-guided sclerotic bone lesion biopsy result in cancer patients.

Methods

In total, 113 CT-guided bone biopsies performed in cancer patients by an interventional radiologist in one institution were retrospectively reviewed. Sixty-five sclerotic bone biopsies were eventually included and routine blood parameters and tumour marker levels were recorded. Non-contrast (NC) biopsy CTs (65), contrast-enhanced CTs (24), and PET/CTs (22) performed within four weeks of biopsy were reviewed; lesion location, diameter, lesion-to-cortex distance, and NC-CT appearance (dense-sclerosis versus mild-sclerosis) were noted. Mean NC-CT, CE-CT HU, and PET SUVmax were derived from biopsy tract and lesion segmentations. Needle diameter, tract length, and number of samples were noted. Comparisons between tumour-positive/negative and next-generation sequencing (NGS)-feasible/non-feasible biopsies determined significant (p < 0.05) laboratory, imaging, and procedural parameter differences.

Results

Seventy-four percent of biopsies were tumour-positive. NGS was feasible in 22/30 prostate cancer patients (73%). Neither laboratory blood parameters, PET/CT availability, size, nor lesion-to-cortex distance affected diagnostic yield or NGS feasibility (p > 0.298). Eighty-seven percent of mildly sclerotic bone (mean 244 HU) biopsies were positive compared with 56% in dense sclerosis (622 HU, p = 0.005) and NC-CT lesion HU was significantly lower in positive biopsies (p = 0.003). A 610 HU threshold yielded 89% PPV for tumour-positive biopsies and a 370 HU threshold 94% PPV for NGS-feasible biopsies. FDG-PET and procedural parameters were non-significant factors (each p > 0.055).

Conclusion

In cancer patients with sclerotic bone disease, targeting areas of predominantly mild sclerosis in lower CT-attenuation lesions can improve tumour tissue yield and NGS feasibility.

Key Points

• Areas of predominantly mild sclerosis should be preferred to areas of predominantly dense sclerosis for CT-guided bone biopsies in cancer patients.

• Among sclerotic bone lesions in prostate cancer patients, lesions with a mean HU below 370 should be preferred as biopsy targets to improve NGS feasibility.

• Laboratory parameters and procedure related factors may have little implications for CT-guided sclerotic bone biopsy success.

Immune Cell Networks Uncover Candidate Biomarkers of Melanoma Immunotherapy Response

The therapeutic activation of antitumour immunity by immune checkpoint inhibitors (ICIs) is a significant advance in cancer medicine, not least due to the prospect of long-term remission. However, many patients are unresponsive to ICI therapy and may experience serious side effects; companion biomarkers are urgently needed to help inform ICI prescribing decisions. We present the IMMUNETS networks of gene coregulation in five key immune cell types and their application to interrogate control of nivolumab response in advanced melanoma cohorts. The results evidence a role for each of the IMMUNETS cell types in ICI response and in driving tumour clearance with independent cohorts from TCGA. As expected, ‘immune hot’ status, including T cell proliferation, correlates with response to first-line ICI therapy. Genes regulated in NK, dendritic, and B cells are the most prominent discriminators of nivolumab response in patients that had previously progressed on another ICI. Multivariate analysis controlling for tumour stage and age highlights CIITA and IKZF3 as candidate prognostic biomarkers. IMMUNETS provide a resource for network biology, enabling context-specific analysis of immune components in orthogonal datasets. Overall, our results illuminate the relationship between the tumour microenvironment and clinical trajectories, with potential implications for precision medicine.

CRISPR/Cas9 and next generation sequencing in the personalized treatment of Cancer

BACKGROUND

Cancer is caused by a combination of genetic and epigenetic abnormalities. Current cancer therapies are limited due to the complexity of their mechanism, underlining the need for alternative therapeutic approaches. Interestingly, combining the Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR/Cas9) system with next-generation sequencing (NGS) has the potential to speed up the identification, validation, and targeting of high-value targets.

MAIN TEXT

Personalized or precision medicine combines genetic information with phenotypic and environmental characteristics to produce healthcare tailored to the individual and eliminates the constraints of "one-size-fits-all" therapy. Precision medicine is now possible thanks to cancer genome sequencing. Having advantages over limited sample requirements and the recent development of biomarkers have made the use of NGS a major leap in personalized medicine. Tumor and cell-free DNA profiling using NGS, proteome and RNA analyses, and a better understanding of immunological systems, are all helping to improve cancer treatment choices. Finally, direct targeting of tumor genes in cancer cells with CRISPR/Cas9 may be achievable, allowing for eliminating genetic changes that lead to tumor growth and metastatic capability.

CONCLUSION

With NGS and CRISPR/Cas9, the goal is no longer to match the treatment for the diagnosed tumor but rather to build a treatment method that fits the tumor exactly. Hence, in this review, we have discussed the potential role of CRISPR/Cas9 and NGS in advancing personalized medicine.

Locational effects on oral microbiota among long-term care patients

Background

Dysbiosis of oral microbiota is the cause of many diseases related to oral and general health. However, few Asia-based studies have evaluated the role of oral microbiota in patients receiving long-term care. Thus, new indications are needed for early prevention and risk management based on information derived from the oral microbiota.

Methods

We used next-generation sequencing (NGS) to identify the oral bacterial composition and abundance in patients receiving long-term care: 20 from the outpatient department (OPD) and 20 home-care patients. Their microbial compositions, taxonomy, and alpha/beta diversity were characterized.

Results

Microbiota from the two groups showed different diversity and homogeneity, as well as distinct bacterial species. A more diverse and stable microbial population was observed among OPD patients. Our findings indicated that home-care patients had a higher risk of oral diseases due to the existence of dominant species and a less stable microbial community.

Conclusion

This work was the first in Taiwan to use NGS to investigate the oral microbiota of long-term care patients. Our study demonstrated the potential use of dominant bacterial species as biomarkers for the risk management of posttreatment complications.

Immune gene network of neurological diseases: Multiple sclerosis (MS), Alzheimer's disease (AD), Parkinson's disease (PD) and Huntington's disease (HD)

Neurological diseases, such as MS, AD, PD and HD, are a major health concern of the elderly population, but still therapeutic options are limited. Recent advances in genomic sequencing and bioinformatics, present an opportunity to understand mechanisms of these diseases for identification of therapeutic targets. Several studies have shown association of immune dysfunction with immune system mediated neurological disease, MS, as well as neurodegenerative diseases (AD, PD and HD). However, similarities and differences in role of the immune system, immune pathways and immune cell types in these diseases remains unknown. In this study, immune cell type signature genes in gene networks associated with neurological diseases, MS, AD, PD and HD was investigated using meta-analysis and bioinformatics methods. Application of Weighted Gene Co-expression Network Analysis (WGCNA) on publicly available gene expression datasets (microarray and RNA-seq) revealed a ModArray_04 module (microarray) or ModRNAseq_06 module (RNA-seq), significantly associated with MS, AD, PD and HD. Hypergeometric enrichment test revealed significant enrichment of immune cell type genes in these neurological disease modules. This study demonstrates that immune system mediated neurological disease, MS and neurodegenerative diseases (AD, PD and HD), share a common gene network characterized by immune cell type signature genes (microglia, monocytes and macrophages) and are probable targets for therapeutic intervention. In summary, this work shows a connection between MS, a disease where the role of the immune system and inflammation is established, and neurodegenerative diseases (AD, PD and HD) where the role of inflammation is still a hypothesis.

Gene expression changes with tumor disease and leech parasitism in the juvenile green sea turtle skin transcriptome

Emerging infectious diseases are a major threat to biodiversity in the 21st century. Fibropapillomatosis (FP) is an epithelial tumor disease that affects immature and adult marine turtles worldwide, particularly green turtles (Chelonia mydas). We know little about the host factors contributing to FP susceptibility, in part because transcriptomic studies that compare transcript expression in turtles with and without FP are lacking. Here, we performed RNA-Seq on healthy skin tissue from immature C. mydas in the Indian River Lagoon, Florida, USA, comparing turtles (1) with and without FP and (2) with and without leech parasites, a putative vector of FP. We assembled a de novo C. mydas skin transcriptome to identify transcripts with significant differential expression (DE) across FP and leech categories. Significant DE transcripts were found across FP and leech comparisons, including 10 of the same transcripts with DE across both comparisons. Leech-positive individuals significantly upregulated different immune and viral interaction transcripts than did leech-negative individuals, including viral interaction transcripts associated with herpesvirus interactions. This finding strengthens the role of marine leeches as mechanical vectors of Chelonid herpesvirus 5 (ChHV5) which has been implicated as a causative agent of FP. FP-positive turtles upregulated several tumor progression and suppression transcripts relative to FP-negative turtles, which had no significant DE tumor progression transcripts. FP-positive turtles also upregulated significantly more protein interaction transcripts than FP-negative turtles. DE transcripts across leech comparisons showed no functional enrichment, whereas DE transcripts across FP comparisons showed some GO terms were enriched in FP-positive and FP negative turtles. Notably, only FP-negative turtles were enriched for GO terms involved in acquired and inflammatory immune gene regulation. Overall, our DE transcripts included several candidate genes that may play important roles in C. mydas resistance to or recovery from FP, highlighting that transcriptomics provides a promising venue to understand this impactful disease. Continued investigation of C. mydas responses to FP and leech affliction is imperative for species persistence and the conservation of marine ecosystems worldwide due to the essential role of sea turtles in ecosystem function and stability.

How to design a national genomic project-a systematic review of active projects

An increasing number of countries are investing efforts to exploit the human genome, in order to improve genetic diagnostics and to pave the way for the integration of precision medicine into health systems. The expected benefits include improved understanding of normal and pathological genomic variation, shorter time-to-diagnosis, cost-effective diagnostics, targeted prevention and treatment, and research advances.We review the 41 currently active individual national projects concerning their aims and scope, the number and age structure of included subjects, funding, data sharing goals and methods, and linkage with biobanks, medical data, and non-medical data (exposome). The main aims of ongoing projects were to determine normal genomic variation (90%), determine pathological genomic variation (rare disease, complex diseases, cancer, etc.) (71%), improve infrastructure (59%), and enable personalized medicine (37%). Numbers of subjects to be sequenced ranges substantially, from a hundred to over a million, representing in some cases a significant portion of the population. Approximately half of the projects report public funding, with the rest having various mixed or private funding arrangements. 90% of projects report data sharing (public, academic, and/or commercial with various levels of access) and plan on linking genomic data and medical data (78%), existing biobanks (44%), and/or non-medical data (24%) as the basis for enabling personal/precision medicine in the future.Our results show substantial diversity in the analysed categories of 41 ongoing national projects. The overview of current designs will hopefully inform national initiatives in designing new genomic projects and contribute to standardisation and international collaboration.

Approaching precision medicine by tailoring the microbiota

Accumulating evidence has revealed the link between the microbiota and various human diseases. Advances in high-throughput sequencing technologies have identified some consistent disease-associated microbial features, leading to the emerging concept of microbiome-based therapeutics. However, it is also becoming clear that there are considerable variations in the microbiota among patients with the same disease. Variations in the microbial composition and function contribute to substantial differences in metabolic status of the host via production of a myriad of biochemically and functionally different microbial metabolites. Indeed, compelling evidence indicates that individuality of the microbiome may result in individualized responses to microbiome-based therapeutics and other interventions. Mechanistic understanding of the role of the microbiota in diseases and drug metabolism would help us to identify causal relationships and thus guide the development of microbiome-based precision or personalized medicine. In this review, we provide an overview of current efforts to use microbiome-based interventions for the treatment of diseases such as cancer, neurological disorders, and diabetes to approach precision medicine.

Artificial intelligence and pathology: From principles to practice and future applications in histomorphology and molecular profiling

The complexity of diagnostic (surgical) pathology has increased substantially over the last decades with respect to histomorphological and molecular profiling. Pathology has steadily expanded its role in tumor diagnostics and beyond from disease entity identification via prognosis estimation to precision therapy prediction. It is therefore not surprising that pathology is among the disciplines in medicine with high expectations in the application of artificial intelligence (AI) or machine learning approaches given their capabilities to analyze complex data in a quantitative and standardized manner to further enhance scope and precision of diagnostics. While an obvious application is the analysis of histological images, recent applications for the analysis of molecular profiling data from different sources and clinical data support the notion that AI will enhance both histopathology and molecular pathology in the future. At the same time, current literature should not be misunderstood in a way that pathologists will likely be replaced by AI applications in the foreseeable future. Although AI will transform pathology in the coming years, recent studies reporting AI algorithms to diagnose cancer or predict certain molecular properties deal with relatively simple diagnostic problems that fall short of the diagnostic complexity pathologists face in clinical routine. Here, we review the pertinent literature of AI methods and their applications to pathology, and put the current achievements and what can be expected in the future in the context of the requirements for research and routine diagnostics.

The insurability of innovative pharmaceutical cancer technologies

The scientific literature, including several papers published in the IJHPR, has raised the issue of the spiraling cost of cancer treatment, including that of cancer drugs and other technologies such as gene and cell therapies. In this perspective, we review three criteria for insurability and show that they may not be met.

First, the uncertain trends in the cost of innovative pharmaceutical and other cancer technologies make the maximum possible loss per event very difficult to predict and to manage in terms of insurer solvency. Second, the uncertainty of the price, the period that a drug or other cancer care technology will be administered and the number of individuals that will need the technology makes it difficult to predict future insurance premiums and whether they will be affordable to the target population. Third, public coverage needs to be consistent with societal values. However, pressure to limit public coverage will gradually increase as the possibilities of innovative pharmaceutical cancer technologies expand, thus transferring the burden onto commercial insurance. This is a phenomenon that is virtually impossible to predict accurately, but which will certainly undermine the status of health as a social good.

We conclude that the financial risk arising from the use of innovative pharmaceutical cancer technologies fails to meet the aforementioned criteria, thus raising questions as to the sustainability of commercial insurance for cancer treatment and suggesting the need for the state to take greater responsibility for covering this financial risk in the future.

Quiescent stem cell marker genes in glioma gene networks are sufficient to distinguish between normal and glioblastoma (GBM) samples

Grade 4 glioma or GBM has poor prognosis and is the most aggressive grade of glioma. Accurate diagnosis and classification of tumor grade is a critical determinant for development of treatment pathway. Extensive genomic sequencing of gliomas, different cell types, brain tissue regions and advances in bioinformatics algorithms, have presented an opportunity to identify molecular markers that can complement existing histology and imaging methods used to diagnose and classify gliomas. ‘Cancer stem cell theory’ purports that a minor population of stem cells among the heterogeneous population of different cell types in the tumor, drive tumor growth and resistance to therapies. However, characterization of stem cell states in GBM and ability of stem cell state signature genes to serve as diagnostic or prognostic molecular markers are unknown. In this work, two different network construction algorithms, Weighted correlation network analysis (WGCNA) and Multiscale Clustering of Geometric Network (MEGENA), were applied on publicly available glioma, control brain and stem cell gene expression RNA-seq datasets, to identify gene network regulatory modules associated with GBM. Both gene network algorithms identified consensus or equivalent modules, HuAgeGBsplit_18 (WGCNA) and c1_HuAgeGBsplit_32/193 (MEGENA), significantly associated with GBM. Characterization of HuAgeGBsplit_18 (WGCNA) and c1_HuAgeGBsplit_32/193 (MEGENA) modules showed significant enrichment of rodent quiescent stem cell marker genes (GSE70696_QNPbyTAP). A logistic regression model built with eight of these quiescent stem cell marker genes (GSE70696_QNPbyTAP) was sufficient to distinguish between control and GBM samples. This study demonstrates that GBM associated gene regulatory modules are characterized by diagnostic quiescent stem cell marker genes, which may potentially be used clinically as diagnostic markers and therapeutic targets in GBM.

Talkin' Toxins: From Coley's to Modern Cancer Immunotherapy

The ability of the immune system to precisely target and eliminate aberrant or infected cells has long been studied in the field of infectious diseases. Attempts to define and exploit these potent immunological processes in the fight against cancer has been a longstanding effort dating back over 100 years to when Dr. William Coley purposefully infected cancer patients with a cocktail of heat-killed bacteria to stimulate anti-cancer immune processes. Although the field of cancer immunotherapy has been dotted with skepticism at times, the success of immune checkpoint inhibitors and recent FDA approvals of autologous cell therapies have pivoted immunotherapy to center stage as one of the most promising strategies to treat cancer. This review aims to summarize historic milestones throughout the field of cancer immunotherapy as well as highlight current and promising immunotherapies in development.

Benefits of Nanomedicine for Therapeutic Intervention in Malignant Diseases

Cancer remains one of the most difficult to manage healthcare problems. The last two decades have been considered the golden age of cancer research, with major breakthroughs being announced on a regular basis. However, the major problem regarding cancer treatment is the incapability to selectively target cancer cells, with certain populations of tumors still remaining alive after treatment. The main focus of researchers is to develop treatments that are both effective and selective in targeting malignant cells. In this regard, bioavailability can be increased by overcoming the biological barriers encountered in the active agent’s pathway, creating carrier vehicles that have the ability to target malignant cells and effectively release the active agent. Since its appearance, nanomedicine has provided many answers to these challenges, but still, some expectations were not satisfied. In this review, we focused on the most recent developments in targeted drug delivery. Furthermore, a summary of different types of nanoparticles used to deliver active therapeutic agents in oncology is presented, along with details on the nanodrugs that were clinically approved by the Food and Drug Administration (FDA), until April 2019.