Widespread transcriptomic alterations of transient receptor potential channel genes in cancer

Ion channels, in particular transient-receptor potential (TRP) channels, are essential genes that play important roles in many physiological processes. Emerging evidence has demonstrated that TRP genes are involved in a number of diseases, including various cancer types. However, we still lack knowledge about the expression alterations landscape of TRP genes across cancer types. In this review, we comprehensively reviewed and summarised the transcriptomes from more than 10 000 samples in 33 cancer types. We found that TRP genes were widespreadly transcriptomic dysregulated in cancer, which was associated with clinical survival of cancer patients. Perturbations of TRP genes were associated with a number of cancer pathways across cancer types. Moreover, we reviewed the functions of TRP family gene alterations in a number of diseases reported in recent studies. Taken together, our study comprehensively reviewed TRP genes with extensive transcriptomic alterations and their functions will directly contribute to cancer therapy and precision medicine.

Prospective cohort study assessing patient satisfaction and diagnostic accuracy in channeled endoscope local anesthetic biopsy in the investigation of head and neck cancer

BACKGROUND

There are delays in the head and neck Urgent Suspicion of Cancer (USOC) pathway. Local anesthetic (LA) biopsy with channeled endoscopes in outpatients can reduce time to diagnosis.

METHODS

Questionnaire-based prospective study of LA or general anesthetic (GA) biopsy for investigation of cancer from September 2021 to July 2022.

RESULTS

100% (n = 48) were very satisfied or satisfied with their overall experience. 71% (n = 20) of LA patients reported they would prefer to have a biopsy under LA. LA biopsy was 68% sensitive and 100% specific for cancer diagnosis. 28.6% (8) and 10% (2) of LA and GA patients had palliative MDT outcomes. Median time to diagnosis was 44.5 and 49.0 days for LA and GA biopsy, respectively.

CONCLUSION

LA biopsy had a high satisfaction rate and is sensitive for diagnosing cancer. LA biopsy can expedite treatment pathways. LA biopsy should be considered as an option for first line investigation.

A critical discourse analysis of the influence of organisational structures on inequality in head and neck cancer treatment in Denmark

BACKGROUND

Concern is growing about inequality in cancer treatment, and a call has been made for more knowledge of the underlying causes of this inequality. Studies show that patients with low socioeconomic status in general face a greater risk of inequality than patients with a high socioeconomic status.

AIM

The aim of the present study was to uncover how institutional factors may exacerbate inequality in cancer treatment for patients with low socioeconomic status exemplified by patients with head and neck cancer, most of whom have low socioeconomic status.

METHOD

Inspired by Fairclough, we undertook a critical discourse analysis investigating the treatment pathway of patients with head and neck cancer on the basis of policy papers.

RESULTS

These papers, which we conceived as formative instruments, harboured a discourse of efficiency and a discourse of participation, together carving out an effective cancer treatment pathway provided patients act in line with the recommendations.

DISCUSSION

The discourses of efficiency and participation are not unfamiliar in health care, and prior research shows that they may pose difficulties for patients with low socioeconomic status.

CONCLUSION

The discoursal framing of head and neck cancer treatment may exacerbate inequality because most patients with a low socioeconomic status fail to comprehend and act in accordance with these discourses.

Joint Transcriptome and Metabolome Analysis Prevails the Biological Mechanisms Underlying the Pro-Survival Fight in In Vitro Heat-Stressed Granulosa Cells

Previous studies reported the physical, transcriptome, and metabolome changes in in vitro acute heat-stressed (38 °C versus 43 °C for 2 h) bovine granulosa cells. Granulosa cells exhibited transient proliferation senescence, oxidative stress, an increased rate of apoptosis, and a decline in steroidogenic activity. In this study, we performed a joint integration and network analysis of metabolomic and transcriptomic data to further narrow down and elucidate the role of differentially expressed genes, important metabolites, and relevant cellular and metabolic pathways in acute heat-stressed granulosa cells. Among the significant (raw p-value < 0.05) metabolic pathways where metabolites and genes converged, this study found vitamin B6 metabolism, glycine, serine and threonine metabolism, phenylalanine metabolism, arginine biosynthesis, tryptophan metabolism, arginine and proline metabolism, histidine metabolism, and glyoxylate and dicarboxylate metabolism. Important significant convergent biological pathways included ABC transporters and protein digestion and absorption, while functional signaling pathways included cAMP, mTOR, and AMPK signaling pathways together with the ovarian steroidogenesis pathway. Among the cancer pathways, the most important pathway was the central carbon metabolism in cancer. Through multiple analysis queries, progesterone, serotonin, citric acid, pyridoxal, L-lysine, succinic acid, L-glutamine, L-leucine, L-threonine, L-tyrosine, vitamin B6, choline, and CYP1B1, MAOB, VEGFA, WNT11, AOX1, ADCY2, ICAM1, PYGM, SLC2A4, SLC16A3, HSD11B2, and NOS2 appeared to be important enriched metabolites and genes, respectively. These genes, metabolites, and metabolic, cellular, and cell signaling pathways comprehensively elucidate the mechanisms underlying the intricate fight between death and survival in acute heat-stressed bovine granulosa cells and essentially help further our understanding (and will help the future quest) of research in this direction.

In Limbo: Seven Families' Experiences of Encounter with Cancer Care in Norway

INTRODUCTION

Like many other countries, Norway has seen a shift from inpatient to outpatient cancer care, with pathways aimed at improving the integration and coordination of health services. This study explores the perspectives of seven patients and their family members in light of this change. We focus on one particular phase of the pathway: the first encounter. Our interviews were set in the period from referral until the start of treatment.

METHODS

Nineteen individual in-depth interviews were conducted in seven families. Seven patients with cancer and 12 family members were interviewed.

RESULTS

Three categories of experiences stood out in the empirical material: 'Being in between different health professionals', 'Overwhelmed by written and oral information' and 'Lack of involvement'.

CONCLUSION

This study provides insight into families' experiences with cancer care from referral until the start of treatment. Our findings indicate that families often experience cancer care as fragmented and confusing. Although evaluations have shown that the introduction of cancer pathways seems to have a positive effect on waiting times and standardization of examinations across hospitals and regions, there is still potential for improvement in coordination between services, family involvement, and emotional and practical support. We argue that our findings highlight the tension between two ideals of professional care: standardization and patient-centredness. The study illustrates shortcomings in translating the ideal of patient-centredness into professional practice.

Tumorigenic bacteria in colorectal cancer: mechanisms and treatments

Colorectal cancer (CRC) is the third most common and the second most fatal cancer. In recent years, more attention has been directed toward the role of gut microbiota in the initiation and development of CRC. Some bacterial species, such as Fusobacterium nucleatum, Escherichia coli, Bacteroides fragilis, Enterococcus faecalis, and Salmonella sp. have been associated with CRC, based upon sequencing studies in CRC patients and functional studies in cell culture and animal models. These bacteria can cause host DNA damage by genotoxic substances, including colibactin secreted by pks + Escherichia coli, B. fragilis toxin (BFT) produced by Bacteroides fragilis, and typhoid toxin (TT) from Salmonella. These bacteria can also indirectly promote CRC by influencing host-signaling pathways, such as E-cadherin/β-catenin, TLR4/MYD88/NF-κB, and SMO/RAS/p38 MAPK. Moreover, some of these bacteria can contribute to CRC progression by helping tumor cells to evade the immune response by suppressing immune cell function, creating a proinflammatory environment, or influencing the autophagy process. Treatments with the classical antibacterial drugs, metronidazole or erythromycin, the antibacterial active ingredients, M13@ Ag (electrostatically assembled from inorganic silver nanoparticles and the protein capsid of bacteriophage M13), berberine, and zerumbone, were found to inhibit tumorigenic bacteria to different degrees. In this review, we described progress in elucidating the tumorigenic mechanisms of several CRC-associated bacteria, as well as progress in developing effective antibacterial therapies. Specific bacteria have been shown to be active in the oncogenesis and progression of CRC, and some antibacterial compounds have shown therapeutic potential in bacteria-induced CRC. These bacteria may be useful as biomarkers or therapeutic targets for CRC.

Unravelling the Shared Genetic Mechanisms Underlying 18 Autoimmune Diseases Using a Systems Approach

Autoimmune diseases (AiDs) are complex heterogeneous diseases characterized by hyperactive immune responses against self. Genome-wide association studies have identified thousands of single nucleotide polymorphisms (SNPs) associated with several AiDs. While these studies have identified a handful of pleiotropic loci that confer risk to multiple AiDs, they lack the power to detect shared genetic factors residing outside of these loci. Here, we integrated chromatin contact, expression quantitative trait loci and protein-protein interaction (PPI) data to identify genes that are regulated by both pleiotropic and non-pleiotropic SNPs. The PPI analysis revealed complex interactions between the shared and disease-specific genes. Furthermore, pathway enrichment analysis demonstrated that the shared genes co-occur with disease-specific genes within the same biological pathways. In conclusion, our results are consistent with the hypothesis that genetic risk loci associated with multiple AiDs converge on a core set of biological processes that potentially contribute to the emergence of polyautoimmunity.

Molecular Characterization and Clinical Relevance of Lysine Acetylation Regulators in Urological Cancers

Background

Lysine acetylation and deacetylation are posttranslational modifications that are able to link extracellular signals to intracellular responses. However, knowledge regarding the status of lysine regulators in urological cancers is still unknown.

Methods

We first systematically analyzed the genetic and expression alterations of 31 lysine acetylation regulators in urological cancers. The correlation between lysine acetylation regulators and activation of cancer pathways was explored. The clinical relevance of lysine acetylation regulators was further analyzed.

Results

We identified that there are widespread genetic alterations of lysine acetylation regulators, and that their expression levels are significantly associated with the activity of cancer hallmark-related pathways. Moreover, lysine acetylation regulators were found to be potentially useful for prognostic stratification. HDAC11 may act as a potential oncogene in cell cycle and oxidative phosphorylation of urological cancers.

Conclusion

Lysine acetylation regulators are involved in tumorigenesis and progression. Our results provide a valuable resource that will guide both mechanistic and therapeutic analyses of the role of lysine acetylation regulators in urological cancers.

Using a Multi-Level Process Comparison for Process Change Analysis in Cancer Pathways

The area of process change over time is a particular concern in healthcare, where patterns of care emerge and evolve in response to individual patient needs. We propose a structured approach to analyse process change over time that is suitable for the complex domain of healthcare. Our approach applies a qualitative process comparison at three levels of abstraction: a holistic perspective (process model), a middle-level perspective (trace), and a fine-grained detail (activity). Our aim was to detect change points, localise and characterise the change, and unravel/understand the process evolution. We illustrate the approach using a case study of cancer pathways in Leeds where we found evidence of change points identified at multiple levels. In this paper, we extend our study by analysing the miners used in process discovery and providing a deeper analysis of the activity of investigation in trace and activity levels. In the experiment, we show that this qualitative approach provides a useful understanding of process change over time. Examining change at three levels provides confirmatory evidence of process change where perspectives agree, while contradictory evidence can lead to focused discussions with domain experts. This approach should be of interest to others dealing with processes that undergo complex change over time.

Outcomes of the 2019 novel coronavirus in patients with or without a history of cancer: a multi-centre North London experience

Background:

This study aims to compare the outcomes of COVID-19-positive disease in patients with a history of cancer to those without.

Methods:

We retrospectively collected clinical data and outcomes of COVID-19 positive cancer patients treated consecutively in five North London hospitals (cohort A). Outcomes recorded included time interval between most recent anti-cancer treatment and admission, severe outcome [a composite endpoint of intensive care unit (ITU) admission, ventilation and/or death] and mortality. Outcomes were compared with consecutively admitted COVID-19 positive patients, without a history of cancer (cohort B), treated at the primary centre during the same time period (1 March–30 April 2020). Patients were matched for age, gender and comorbidity.

Results:

The median age in both cohorts was 74 years, with 67% male, and comprised of 30 patients with cancer, and 90 without (1:3 ratio). For cohort B, 579 patients without a history of cancer and consecutively admitted were screened from the primary London hospital, 105 were COVID-19 positive and 90 were matched and included. Excluding cancer, both cohorts had a median of two comorbidities. The odds ratio (OR) for mortality, comparing patients with cancer to those without, was 1.05 [95% confidence interval (CI) 0.4–2.5], and severe outcome (OR 0.89, 95% CI 0.4–2.0) suggesting no increased risk of death or a severe outcome in patients with cancer. Cancer patients who received systemic treatment within 28 days had an OR for mortality of 4.05 (95% CI 0.68–23.95), p = 0.12. On presentation anaemia, hypokalaemia, hypoalbuminaemia and hypoproteinaemia were identified predominantly in cohort A. Median duration of admission was 8 days for cancer patients and 7 days for non-cancer.

Conclusion:

A diagnosis of cancer does not appear to increase the risk of death or a severe outcome in COVID-19 patients with cancer compared with those without cancer. If a second spike of virus strikes, rational decision making is required to ensure optimal cancer care.

Effects of somatic alterations at pathway level are more mechanism-explanatory and clinically applicable to quantity of liver metastases of colorectal cancer

Background

The quantity of metastases lesions is an important reference when it comes to making a more informed treatment decision for patients with colorectal cancer liver metastases. However, the molecular alterations in patients with different numbers of lesions have not been systematically studied.

Methods

We investigated somatic alterations and microsatellite instability (MSI) of liver metastases from patients with single, multiple or diffuse metastasis lesions. A new algorithm “Pathway Damage Score” was developed to comprehensively assess the functional impact of somatic alterations at the pathway level. Pathogenic pathways of different metastasis were identified and their prognosis effects were evaluated. Furthermore, the subnetworks and affected phenotypes of the altered genes in each pathogenic pathway were analyzed.

Results

Somatic alterations and altered genes occurred sporadically as well as in MSI state in different metastasis types, although MSS patients had more metastatic lesions than that of the MSI patients. Every metastasis group has their own pathogenic pathways and damaged “Cargo recognition for clathrin‐mediated endocytosis” is significantly associated with poor prognosis (P < 0.001). Further pathway subnetwork analysis showed that except conventional drivers, other genes could also contribute to metastasis formation.

Conclusions

Progression of liver metastasis could be driven by the coefficient of all altered genes belonging to the pathways. Thus, compared to somatic alterations and genes, pathway level analysis is more reasonable for functional interpretations of molecular alterations in clinical samples.

Computational Methods for Characterizing Cancer Mutational Heterogeneity

Advances in DNA sequencing technologies have allowed the characterization of somatic mutations in a large number of cancer genomes at an unprecedented level of detail, revealing the extreme genetic heterogeneity of cancer at two different levels: inter-tumor, with different patients of the same cancer type presenting different collections of somatic mutations, and intra-tumor, with different clones coexisting within the same tumor. Both inter-tumor and intra-tumor heterogeneity have crucial implications for clinical practices. Here, we review computational methods that use somatic alterations measured through next-generation DNA sequencing technologies for characterizing tumor heterogeneity and its association with clinical variables. We first review computational methods for studying inter-tumor heterogeneity, focusing on methods that attempt to summarize cancer heterogeneity by discovering pathways that are commonly mutated across different patients of the same cancer type. We then review computational methods for characterizing intra-tumor heterogeneity using information from bulk sequencing data or from single cell sequencing data. Finally, we present some of the recent computational methodologies that have been proposed to identify and assess the association between inter- or intra-tumor heterogeneity with clinical variables.

On the Sample Complexity of Cancer Pathways Identification

Advances in DNA sequencing technologies have enabled large cancer sequencing studies, collecting somatic mutation data from a large number of cancer patients. One of the main goals of these studies is the identification of all cancer genes--genes associated with cancer. Its achievement is complicated by the extensive mutational heterogeneity of cancer, due to the fact that important mutations in cancer target combinations of genes (i.e., pathways). Recently, the pattern of mutual exclusivity among mutations in a cancer pathway has been observed, and methods that find significant combinations of cancer genes by detecting mutual exclusivity have been proposed. A key question in the analysis of mutual exclusivity is the computation of the minimum number of samples required to reliably find a meaningful set of mutually exclusive mutations in the data, or conclude that there is no such set. In general, the problem of determining the sample complexity, or the number of samples required to identify significant combinations of features, of genomic problems is largely unexplored. In this work we propose a framework to analyze the sample complexity of problems that arise in the study of genomic datasets. Our framework is based on tools from combinatorial analysis and statistical learning theory that have been used for the analysis of machine learning and probably approximately correct (PAC) learning. We use our framework to analyze the problem of the identification of cancer pathways through mutual exclusivity analysis. We analytically derive matching upper and lower bounds on the sample complexity of the problem, showing that sample sizes much larger than currently available may be required to identify all the cancer genes in a pathway. We also provide two algorithms to find a cancer pathway from a large genomic dataset. On simulated and cancer data, we show that our algorithms can be used to identify cancer pathways from large genomic datasets.

A survey of tandem repeat instabilities and associated gene expression changes in 35 colorectal cancers

BACKGROUND

Colorectal cancer is a major contributor to cancer morbidity and mortality. Tandem repeat instability and its effect on cancer phenotypes remain so far poorly studied on a genome-wide scale.

RESULTS

Here we analyze the genomes of 35 colorectal tumors and their matched normal (healthy) tissues for two types of tandem repeat instability, de-novo repeat gain or loss and repeat copy number variation. Specifically, we study for the first time genome-wide repeat instability in the promoters and exons of 18,439 genes, and examine the association of repeat instability with genome-scale gene expression levels. We find that tumors with a microsatellite instable (MSI) phenotype are enriched in genes with repeat instability, and that tumor genomes have significantly more genes with repeat instability compared to healthy tissues. Genes in tumor genomes with repeat instability in their promoters are significantly less expressed and show slightly higher levels of methylation. Genes in well-studied cancer-associated signaling pathways also contain significantly more unstable repeats in tumor genomes. Genes with such unstable repeats in the tumor-suppressor p53 pathway have lower expression levels, whereas genes with repeat instability in the MAPK and Wnt signaling pathways are expressed at higher levels, consistent with the oncogenic role they play in cancer.

CONCLUSIONS

Our results suggest that repeat instability in gene promoters and associated differential gene expression may play an important role in colorectal tumors, which is a first step towards the development of more effective molecular diagnostic approaches centered on repeat instability.

Gene expression profiling for targeted cancer treatment

INTRODUCTION

There is certain degree of frustration and discontent in the area of microarray gene expression data analysis of cancer datasets. It arises from the mathematical problem called 'curse of dimensionality,' which is due to the small number of samples available in training sets, used for calculating transcriptional signatures from the large number of differentially expressed (DE) genes, measured by microarrays. The new generation of causal reasoning algorithms can provide solutions to the curse of dimensionality by transforming microarray data into activity of a small number of cancer hallmark pathways. This new approach can make feature space dimensionality optimal for mathematical signature calculations.

AREAS COVERED

The author reviews the reasons behind the current frustration with transcriptional signatures derived from DE genes in cancer. He also provides an overview of the novel methods for signature calculations based on differentially variable genes and expression regulators. Furthermore, the authors provide perspectives on causal reasoning algorithms that use prior knowledge about regulatory events described in scientific literature to identify expression regulators responsible for the differential expression observed in cancer samples.

EXPERT OPINION

The author advocates causal reasoning methods to calculate cancer pathway activity signatures. The current challenge for these algorithms is in ensuring quality of the knowledgebase. Indeed, the development of cancer hallmark pathway collections, together with statistical algorithms to transform activity of expression regulators into pathway activity, are necessary for causal reasoning to be used in cancer research.

Identification of novel mutations by exome sequencing in African American colorectal cancer patients

BACKGROUND

The purpose of this study was to identify genome-wide single nucleotide variants and mutations in African American patients with colorectal cancer (CRC). There is a need of such studies in African Americans, because they display a higher incidence of aggressive CRC tumors.

METHODS

We performed whole exome sequencing (WES) on DNA from 12 normal/tumor pairs of African American CRC patient tissues. Data analysis was performed using the software package GATK (Genome Analysis Tool Kit). Normative population databases (eg, 1000 Genomes SNP database, dbSNP, and HapMap) were used for comparison. Variants were annotated using analysis of variance and were validated via Sanger sequencing.

RESULTS

We identified somatic mutations in genes that are known targets in CRC such as APC, BRAF, KRAS, and PIK3CA. We detected novel alterations in the Wnt pathway gene, APC, within its exon 15, of which mutations are highly associated with CRC.

CONCLUSIONS

This WES study in African American patients with CRC provides insight into the identification of novel somatic mutations in APC. Our data suggest an association between specific mutations in the Wnt signaling pathway and an increased risk of CRC. The analysis of the pathogenicity of these novel variants may shed light on the aggressive nature of CRC in African Americans.

Efficient computation of minimal perturbation sets in gene regulatory networks

In the last few decades, technological and experimental advancements have enabled a more precise understanding of the mode of action of drugs with respect to human cell signaling pathways and have positively influenced the design of new drug compounds. However, as the design of compounds has become increasingly target-specific, the overall effects of a drug on adjacent cellular signaling pathways remain difficult to predict because of the complexity of the interactions involved. Off-target effects of drugs are known to influence their efficacy and safety. Similarly, drugs which are more target-specific also suffer from lack of efficacy because their scope might be too limited in the context of cellular signaling. Even in situations where the signaling pathways targeted by a drug are known, the presence of point mutations in some of the components of the pathways can render a therapy ineffective in a considerable target subpopulation. Some of these issues can be addressed by predicting Minimal Intervention Sets (MIS) of elements of the signaling pathways that when perturbed give rise to a pre-defined cellular phenotype. These minimal gene perturbation sets can then be further used to screen a library of drug compounds in order to discover effective drug therapies. This manuscript describes algorithms that can be used to discover MIS in a gene regulatory network that can lead to a defined cellular phenotype. Algorithms are implemented in our Boolean modeling toolbox, GenYsis. The software binaries of GenYsis are available for download from http://www.vital-it.ch/software/genYsis/.

Gastrointestinal stromal tumor mesenchymal neoplasms: the offspring that choose the wrong path

Gastrointestinal stromal tumors (GISTs) are relatively rare neoplasms of the gastrointestinal tract originating from the pluripotential mesenchymal stem cells, which differentiate into interstitial Cajal cells. They are usually located in the upper gastrointestinal track. These tumors are typically defined by the expression of c-KIT (CD117) and CD34 proteins in the tumor cells. A small percentage of these tumors is negative for c-KIT. The neoplasms are positive for platelet-derived growth factor α (PDGFα) mutations. In addition to PDGFRα mutations, wild-type c-KIT mutations can also be present. The therapeutic approach to locally developed gastrointestinal stromal tumors is surgical resection, either with open or laparoscopic surgery. In case of systemic disease, molecular pharmacologic agents such as imatinib and sunitinib are used for treatment. These agents block the signaling pathways of neoplastic-cell tyrosine kinases, interfering in their proliferation and causing apoptosis.

Hypoxia-inducible factors in stem cells and cancer

Cellular properties are influenced by complex factors inherent to their microenvironments. While oxygen deprivation (hypoxia) occurs in tumours because of rapid cell proliferation and aberrant blood vessel formation, embryonic cells develop in a naturally occurring hypoxic environment. Cells respond to hypoxia by stabilizing hypoxia-inducible factors (HIFs), which are traditionally viewed to function by altering cellular metabolism and blood vessel architecture. Recently, HIFs have been shown to modulate specific stem cell effectors, such as Notch, Wnt and Oct4 that control stem cell proliferation, differentiation and pluripotency. Direct molecular links have also been established between HIFs and critical cell signalling pathways such as cMyc and p53. These novel links suggest a new role for HIFs in stem cell and tumour regulation.