Somatic mutations in cancer development

Deep learning in cancer genomics and histopathology

Histopathology and genomic profiling are cornerstones of precision oncology and are routinely obtained for patients with cancer. Traditionally, histopathology slides are manually reviewed by highly trained pathologists. Genomic data, on the other hand, is evaluated by engineered computational pipelines. In both applications, the advent of modern artificial intelligence methods, specifically machine learning (ML) and deep learning (DL), have opened up a fundamentally new way of extracting actionable insights from raw data, which could augment and potentially replace some aspects of traditional evaluation workflows. In this review, we summarize current and emerging applications of DL in histopathology and genomics, including basic diagnostic as well as advanced prognostic tasks. Based on a growing body of evidence, we suggest that DL could be the groundwork for a new kind of workflow in oncology and cancer research. However, we also point out that DL models can have biases and other flaws that users in healthcare and research need to know about, and we propose ways to address them.

A systematic review of computational approaches to understand cancer biology for informed drug repurposing

Cancer is the second leading cause of death globally, trailing only heart disease. In the United States alone, 1.9 million new cancer cases and 609,360 deaths were recorded for 2022. Unfortunately, the success rate for new cancer drug development remains less than 10%, making the disease particularly challenging. This low success rate is largely attributed to the complex and poorly understood nature of cancer etiology. Therefore, it is critical to find alternative approaches to understanding cancer biology and developing effective treatments. One such approach is drug repurposing, which offers a shorter drug development timeline and lower costs while increasing the likelihood of success. In this review, we provide a comprehensive analysis of computational approaches for understanding cancer biology, including systems biology, multi-omics, and pathway analysis. Additionally, we examine the use of these methods for drug repurposing in cancer, including the databases and tools that are used for cancer research. Finally, we present case studies of drug repurposing, discussing their limitations and offering recommendations for future research in this area.

Clonal hematopoiesis, somatic mosaicism, and age-associated disease

Somatic mosaicism, the occurrence of multiple genetically distinct cell clones within the same tissue, is an evitable consequence of human aging. The hematopoietic system is no exception to this, where studies have revealed the presence of expanded blood cell clones carrying mutations in preleukemic driver genes and/or genetic alterations in chromosomes. This phenomenon is referred to as clonal hematopoiesis and is remarkably prevalent in elderly individuals. While clonal hematopoiesis represents an early step toward a hematological malignancy, most individuals will never develop blood cancer. Somewhat unexpectedly, epidemiological studies have found that clonal hematopoiesis is associated with an increase in the risk of all-cause mortality and age-related disease, particularly in the cardiovascular system. Studies using murine models of clonal hematopoiesis have begun to shed light on this relationship, suggesting that driver mutations in mature blood cells can causally contribute to aging and disease by augmenting inflammatory processes. Here we provide an up-to-date review of clonal hematopoiesis within the context of somatic mosaicism and aging and describe recent epidemiological studies that have reported associations with age-related disease. We will also discuss the experimental studies that have provided important mechanistic insight into how driver mutations promote age-related disease and how this knowledge could be leveraged to treat individuals with clonal hematopoiesis.

Head and neck squamous cell carcinoma: a potential therapeutic target for the Wnt signaling pathway

Squamous cell carcinoma (SCC) of the head and neck region accounts for 3% of all tumors worldwide. The incidence is higher in men, with most carcinomas found in the oral cavity. At the point of initial diagnosis, distant metastases are rare. The Wnt signaling pathway is critically involved in cell development and stemness and has been associated with SCC. Understanding precisely how Wnt signaling regulates SCC progression and how it can, therefore, be modulated for the therapeutic benefit has enormous potential in the treatment of head and neck SCC. In this review, we will describe the underlying mechanisms of Wnt signaling and outline how Wnt signaling controls cellular processes both in homeostasis and in the development and progression of SCC.

Level of evidence: Not gradable.

Mucinous adenocarcinoma of the colon and rectum: A genomic analysis

BACKGROUND AND OBJECTIVES

Mucinous adenocarcinoma is a distinct subtype of colorectal cancer (CRC) with a worse prognosis when compared with non-mucinous adenocarcinoma. The aim of this study was to compare somatic mutations and copy number alteration (CNA) between mucinous and non-mucinous CRC.

METHODS

Data from The Cancer Genome Atlas-colon adenocarcinoma and rectum adenocarcinoma projects were utilized. Mucinous and non-mucinous CRC were compared with regard to microsatellite status, overall mutation rate, the most frequently mutated genes, mutations in genes coding for mismatch repair (MMR) proteins and genes coding for mucin glycoproteins. CNA analysis and pathway analysis was undertaken.

RESULTS

Mucinous CRC was more likely to be microsatellite instability-high (MSI-H) and hypermutated. When corrected for microsatellite status the single-nucleotide variation and insertion-deletion rate was similar between the two cohorts. Mucinous adenocarcinoma was more likely to have mutations in genes coding for MMR proteins and mucin glycoproteins. Pathway analysis revealed further differences between the two histological subtypes in the cell cycle, RTK-RAS, transforming growth factor-β, and TP53 pathways.

CONCLUSIONS

Mucinous CRC has some distinct genomic aberrations when compared with non-mucinous adenocarcinoma, many of which are driven by the increased frequency of MSI-H tumors. These genomic aberrations may play an important part in the difference seen in response to treatment and prognosis in mucinous adenocarcinoma.

Cardiovascular Disease, Aging, and Clonal Hematopoiesis

Traditional risk factors are incompletely predictive of cardiovascular disease development, a leading cause of death in the elderly. Recent epidemiological studies have shown that human aging is associated with an increased frequency of somatic mutations in the hematopoietic system, which provide a competitive advantage to a mutant cell, thus allowing for its clonal expansion, a phenomenon known as clonal hematopoiesis. Unexpectedly, these mutations have been associated with a higher incidence of cardiovascular disease, suggesting a previously unrecognized connection between somatic mutations in hematopoietic cells and cardiovascular disease. Here, we provide an up-to-date review of clonal hematopoiesis and its association with aging and cardiovascular disease. We also give a detailed report of the experimental studies that have been instrumental in understanding the relationship between clonal hematopoiesis and cardiovascular disease and have shed light on the mechanisms by which hematopoietic somatic mutations contribute to disease pathology.

Multivariate association analysis with somatic mutation data

Somatic mutations are the driving forces for tumor development, and recent advances in cancer genome sequencing have made it feasible to evaluate the association between somatic mutations and cancer-related traits in large sample sizes. However, despite increasingly large sample sizes, it remains challenging to conduct statistical analysis for somatic mutations, because the vast majority of somatic mutations occur at very low frequencies. Furthermore, cancer is a complex disease and it is often accompanied by multiple traits that reflect various aspects of cancer; how to combine the information of these traits to identify important somatic mutations poses additional challenges. In this article, we introduce a statistical approach, named as SOMAT, for detecting somatic mutations associated with multiple cancer-related traits. Our approach provides a flexible framework for analyzing continuous, binary, or a mixture of both types of traits, and is statistically powerful and computationally efficient. In addition, we propose a data-adaptive procedure, which is grid-search free, for effectively combining test statistics to enhance statistical power. We conduct an extensive study and show that the proposed approach maintains correct type I error and is more powerful than existing approaches under the scenarios considered. We also apply our approach to an exome-sequencing study of liver tumor for illustration.

[Expression pattern of FAM135B and K (lysine) acetyltransferase 5 in esophageal squamous cell carcinoma in Uygur patients]

OBJECTIVE

To explore the expression of the family with sequence similarity 135 member B (FAM135B) and K(lysine) acetyltransferase 5 (KAT5) in esophageal squamous cell carcinoma (ESCC) in Uygur patients.

METHODS

The expression of FAM135B and KAT5 in ESCC tissues and paired adjacent tissues from 40 Uygur patients were detected using Roche Benchmark XT. The correlation of FAM135B and KAT5 and their correlation with the clinicopathological characteristics of the patients were analyzed.

RESULTS

The positivity rates of FAM135B and KAT5 in ESCC tissues were 92.50% (37/40) and 15.00%(6/40) in these patients, respectively. The ESCC tissues showed a significantly higher rate of strong FAM135B expression than the adjacent tissues [45.00% (18/40) vs 22.50% (9/40); Χ²=4.528, P=0.033], but the rates of negative KAT5 expression was similar between ESCC and adjacent tissues [85.00% (34/40) vs 87.50% (35/40); Χ²=0.105, P=0.745]. Strong expressions of FAM135B in ESCC tissues and the paired adjacent tissues were well correlated (Kendall's coefficient = 0.707, P<0.001). In ESCC tissues, a strong expression of FAM135B showed a significant negative correlation with KAT5 expression (Kendall's coefficient=-0.946, P<0.001). Neither FAM135B nor KAT5 expression was associated with the patients' gender, age, tumor site, tumor differentiation, invasion, lymph node metastasis and clinical stage (all P>0.05).

CONCLUSION

A strong expression of FAM135B may be an important molecular basis for the occurrence of ESCC in Uygur patients and plays its role by negatively regulating the expression of KAT5.

New Insight into microRNA Functions in Cancer: Oncogene-microRNA-Tumor Suppressor Gene Network

Tumorigenesis is a multi-step and complex process with multi-factors involved. Deregulated oncogenes and tumor suppressor genes (TSGs) induced by genetic and epigenetic factors are considered as the driving force in the development and progression of cancer. Besides, microRNAs (miRNAs) act vital roles in tumorigenesis through regulating some oncogenes and TSGs. Interestingly, miRNAs are also regulated by oncogenes and TSGs. Considering the entangled regulation, here we propose a new insight into these regulation relationships in cancer: oncogene–miRNA–TSG network, which further emphasizes roles of miRNA, as well as highlights the network regulation among oncogene, miRNA, and TSG during tumorigenesis. The oncogene–miRNA–TSG network demonstrates that oncogenes and TSGs not only show functional synergy, but also there are regulatory relationships among oncogenes and TSGs during tumorigenesis, which could be mediated by miRNAs. In view of the oncogene–miRNA–TSG network involved in many oncogenes, miRNAs, and TSGs, as well as occurring in various tumor types, the anomaly of this network may be a common event in cancers and participates in tumorigenesis. This hypothesis broadens horizons of molecular mechanisms underlying tumorigenesis, and may provide a new promising venue for the prediction, diagnosis, and even therapy of cancer.

The frequency of granulocytes with spontaneous somatic mutations: a wide distribution in a normal human population

Germ-line mutation rate has been regarded classically as a fundamental biological parameter, as it affects the prevalence of genetic disorders and the rate of evolution. Somatic mutation rate is also an important biological parameter, as it may influence the development and/or the course of acquired diseases, particularly of cancer. Estimates of this parameter have been previously obtained in few instances from dermal fibroblasts and lymphoblastoid cells. However, the methodology required has been laborious and did not lend itself to the analysis of large numbers of samples. We have previously shown that the X-linked gene PIG-A, since its product is required for glycosyl-phosphatidylinositol-anchored proteins to become surface bound, is a good sentinel gene for studying somatic mutations. We now show that by this approach we can accurately measure the proportion of PIG-A mutant peripheral blood granulocytes, which we call mutant frequency, ƒ. We found that the results are reproducible, with a variation coefficient (CV) of 45%. Repeat samples from 32 subjects also had a CV of 44%, indicating that ƒ is a relatively stable individual characteristic. From a study of 142 normal subjects we found that log ƒ is a normally distributed variable; ƒ variability spans a 80-fold range, from less than 1×10⁻⁶ to 37.5×10⁻⁶, with a median of 4.9×10⁻⁶. Unlike other techniques commonly employed in population studies, such as comet assay, this method can detect any kind of mutation, including point mutation, as long as it causes functional inactivation of PIG-A gene. Since the test is rapid and requires only a small sample of peripheral blood, this methodology will lend itself to investigating genetic factors that underlie the variation in the somatic mutation rate, as well as environmental factors that may affect it. It will be also possible to test whether ƒ is a determinant of the risk of cancer.