Partial deletion of chromosome 1 in a case of acute myelocytic leukemia

Identification of hub genes and potential molecular mechanisms related to drug sensitivity in acute myeloid leukemia based on machine learning

Background: Acute myeloid leukemia (AML) is the most common form of leukemia among adults and is characterized by uncontrolled proliferation and clonal expansion of hematopoietic cells. There has been a significant improvement in the treatment of younger patients, however, prognosis in the elderly AML patients remains poor. Methods: We used computational methods and machine learning (ML) techniques to identify and explore the differential high-risk genes (DHRGs) in AML. The DHRGs were explored through multiple in silico approaches including genomic and functional analysis, survival analysis, immune infiltration, miRNA co-expression and stemness features analyses to reveal their prognostic importance in AML. Furthermore, using different ML algorithms, prognostic models were constructed and validated using the DHRGs. At the end molecular docking studies were performed to identify potential drug candidates targeting the selected DHRGs. Results: We identified a total of 80 DHRGs by comparing the differentially expressed genes derived between AML patients and normal controls and high-risk AML genes identified by Cox regression. Genetic and epigenetic alteration analyses of the DHRGs revealed a significant association of their copy number variations and methylation status with overall survival (OS) of AML patients. Out of the 137 models constructed using different ML algorithms, the combination of Ridge and plsRcox maintained the highest mean C-index and was used to build the final model. When AML patients were classified into low- and high-risk groups based on DHRGs, the low-risk group had significantly longer OS in the AML training and validation cohorts. Furthermore, immune infiltration, miRNA coexpression, stemness feature and hallmark pathway analyses revealed significant differences in the prognosis of the low- and high-risk AML groups. Drug sensitivity and molecular docking studies revealed top 5 drugs, including carboplatin and austocystin-D that may significantly affect the DHRGs in AML. Conclusion: The findings from the current study identified a set of high-risk genes that may be used as prognostic and therapeutic markers for AML patients. In addition, significant use of the ML algorithms in constructing and validating the prognostic models in AML was demonstrated. Although our study used extensive bioinformatics and machine learning methods to identify the hub genes in AML, their experimental validations using knock-out/-in methods would strengthen our findings.

Mouse models for radiation-induced cancers

Potential ionising radiation exposure scenarios are varied, but all bring risks beyond the simple issues of short-term survival. Whether accidentally exposed to a single, whole-body dose in an act of terrorism or purposefully exposed to fractionated doses as part of a therapeutic regimen, radiation exposure carries the consequence of elevated cancer risk. The long-term impact of both intentional and unintentional exposure could potentially be mitigated by treatments specifically developed to limit the mutations and precancerous replication that ensue in the wake of irradiation The development of such agents would undoubtedly require a substantial degree of in vitro testing, but in order to accurately recapitulate the complex process of radiation-induced carcinogenesis, well-understood animal models are necessary. Inbred strains of the laboratory mouse, Mus musculus, present the most logical choice due to the high number of molecular and physiological similarities they share with humans. Their small size, high rate of breeding and fully sequenced genome further increase its value for use in cancer research. This chapter will review relevant m. musculus inbred and F1 hybrid animals of radiation-induced myeloid leukemia, thymic lymphoma, breast and lung cancers. Method of cancer induction and associated molecular pathologies will also be described for each model.

Radiation-induced myeloid leukemia in murine models

The use of radiation therapy is a cornerstone of modern cancer treatment. The number of patients that undergo radiation as a part of their therapy regimen is only increasing every year, but this does not come without cost. As this number increases, so too does the incidence of secondary, radiation-induced neoplasias, creating a need for therapeutic agents targeted specifically towards incidence reduction and treatment of these cancers. Development and efficacy testing of these agents requires not only extensive in vitro testing but also a set of reliable animal models to accurately recreate the complex situations of radiation-induced carcinogenesis. As radiation-induced leukemic progression often involves genomic changes such as rearrangements, deletions, and changes in methylation, the laboratory mouse Mus musculus, with its fully sequenced genome, is a powerful tool in cancer research. This fact, combined with the molecular and physiological similarities it shares with man and its small size and high rate of breeding in captivity, makes it the most relevant model to use in radiation-induced leukemia research. In this work, we review relevant M. musculus inbred and F₁ hybrid animal models, as well as methods of induction of radiation-induced myeloid leukemia. Associated molecular pathologies are also included.

Mouse models of radiation-induced cancers

Radiation-induced (RI) secondary cancers were not a major clinical concern even as little as 15 years ago. However, advances in cancer diagnostics, therapy, and supportive care have saved numerous lives and many former cancer patients are now living for 5, 10, 20, and more years beyond their initial diagnosis. The majority of these patients have received radiotherapy as a part of their treatment regimen and are now beginning to develop secondary cancers arising from normal tissue exposure to damaging effects of ionizing radiation. Because historically patients rarely survived past the extended latency periods inherent to these RI cancers, very little effort was channeled towards the research leading to the development of therapeutic agents intended to prevent or ameliorate oncogenic effects of normal tissue exposure to radiation. The number of RI cancers is expected to increase very rapidly in the near future, but the field of cancer biology might not be prepared to address important issues related to this phenomena. One such issue is the ability to accurately differentiate between primary tumors and de novo arising secondary tumors in the same patient. Another issue is the lack of therapeutic agents intended to reduce such cancers in the future. To address these issues, large-scale epidemiological studies must be supplemented with appropriate animal modeling studies. This work reviews relevant mouse (Mus musculus) models of inbred and F1 animals and methodologies of induction of most relevant radiation-associated cancers: leukemia, lymphoma, and lung and breast cancers. Where available, underlying molecular pathologies are included.

Mouse models for efficacy testing of agents against radiation carcinogenesis—a literature review

As the number of cancer survivors treated with radiation as a part of their therapy regimen is constantly increasing, so is concern about radiation-induced cancers. This increases the need for therapeutic and mitigating agents against secondary neoplasias. Development and efficacy testing of these agents requires not only extensive in vitro assessment, but also a set of reliable animal models of radiation-induced carcinogenesis. The laboratory mouse (Mus musculus) remains one of the best animal model systems for cancer research due to its molecular and physiological similarities to man, small size, ease of breeding in captivity and a fully sequenced genome. This work reviews relevant M. musculus inbred and F₁ hybrid animal models and methodologies of induction of radiation-induced leukemia, thymic lymphoma, breast, and lung cancer in these models. Where available, the associated molecular pathologies are also included.

Partial trisomy 1p due to paternal t(1;9) translocation in a family with recurrent miscarriages

OBJECTIVE

To report a new case with partial trisomy 1p due to paternal t(1;9) translocation in a family with recurrent miscarriages.

DESIGN

Case report.

SETTING

Faculty of Medicine, Cukurova University.

PATIENT(S)

A couple with recurrent miscarriages, an abnormal fetus, a newborn infant, paternal grandfather and grandmother.

INTERVENTION(S)

Chorionic villi sampling (CVS), amniocentesis, lymphocytic karyotype, and genetic counseling.

MAIN OUTCOME MEASURE(S)

Chromosomal analysis of CVS, amniotic cells, and peripheral blood lymphocytes were performed according to standard cytogenetic methods using G-banding technique.

RESULT(S)

We determined the reproductive risk in a couple who carried a balance and an unbalanced rearrangement of chromosomes 1 and 9 in two generations of a normal father with derivative 9 karyotype. The prenatal and postnatal karyotypes of the newborn infant were the same as the father [46,XY,der(9)t(1:9)(p34.2;q34.3)]. He was also phenotypically normal. The abnormal fetus that was miscarried also had a derivative 9 [46,XY,der(9)t(1:9)(p34.2;q34.3)fat]. The der(9) contained the partial short arm of chromosome 1. Both chromosome 1 showed normal. Trisomy 1p in the fetus was the result of familial derivative 9.

CONCLUSION(S)

Partial trisomy is associated with fetal wastage, and may play a role in the etiology of the other miscarriages in certain families. The apparent lack of increased reproductive failure may result from the selective disadvantage of aneusomic gamets at fertilization or very early spontaneous abortions of unbalanced conceptuses. The detection of couples with chromosomal anomalies can undoubtedly help prevent the births of malformed infants. These findings would be used widely in clinical genetics and as an effective tool for genetic counseling and reproductive guidance.