Clonal cytopenias of undetermined significance: potential predictor of myeloid malignancies?

The recent identification of the potential for clonal replication in patients with unexplained cytopenias, resulting in myelodysplastic syndrome (MDS) or myeloid malignancies, has opened the way to identifying a new precursor entity: clonal cytopenia of undetermined significance (CCUS). CCUS has come into the spotlight in recent years with the detection of molecular abnormalities in cytogenetic studies, fluorescence in situ hybridization, and next-generation sequencing. Several clinical trials and retrospective studies are underway to examine further the associated mutation profiles, study the progression of CCUS to MDS or myeloid neoplasm, and investigate potential treatment options. In this review, we discuss CCUS-related mutations in genes such as DNMT3A, TET2, IDH1/2, ASXL1, KDM6A, PHF6, SF3B1, SRSF2, U2AF1, ZRSR2, RUNX1, BCOR, NRAS, KRAS, KIT, PTEN, CBL, TP53, and ATM. We highlight the most common mutations in CCUS, including those in DNMT3A, TET2, ASXL1, SRSF2, and SF3B1, and high-risk mutations, including those in U2AF1, ZRSR2, SRSF2, JAK2, RUNX1, and TP53. Cognizance of these mutations can guide surveillance and heighten awareness of the need to screen patients with unexplained cytopenia as a means of primary prevention in the realm of MDS and AML. Knowledge of mutation profiles, prognostic risk factors, treatment, and follow-up strategies is evolving, and prospective studies are warranted.

Advancements in Oncology with Artificial Intelligence-A Review Article.

Well-trained machine learning (ML) and artificial intelligence (AI) systems can provide clinicians with therapeutic assistance, potentially increasing efficiency and improving efficacy. ML has demonstrated high accuracy in oncology-related diagnostic imaging, including screening mammography interpretation, colon polyp detection, glioma classification, and grading. By utilizing ML techniques, the manual steps of detecting and segmenting lesions are greatly reduced. ML-based tumor imaging analysis is independent of the experience level of evaluating physicians, and the results are expected to be more standardized and accurate. One of the biggest challenges is its generalizability worldwide. The current detection and screening methods for colon polyps and breast cancer have a vast amount of data, so they are ideal areas for studying the global standardization of artificial intelligence. Central nervous system cancers are rare and have poor prognoses based on current management standards. ML offers the prospect of unraveling undiscovered features from routinely acquired neuroimaging for improving treatment planning, prognostication, monitoring, and response assessment of CNS tumors such as gliomas. By studying AI in such rare cancer types, standard management methods may be improved by augmenting personalized/precision medicine. This review aims to provide clinicians and medical researchers with a basic understanding of how ML works and its role in oncology, especially in breast cancer, colorectal cancer, and primary and metastatic brain cancer. Understanding AI basics, current achievements, and future challenges are crucial in advancing the use of AI in oncology.

Sideroblastic anaemia in a patient with sickle cell disease.

Sideroblastic anaemia is a rare condition. We report a unique case of concomitant sideroblastic anaemia in a patient with sickle cell disease with long-standing blood transfusion history. Due to a low prevalence of sideroblastic anaemia, the diagnosis of sideroblastic anaemia is often difficult, especially when coexisting with common types of anaemia, including sickle cell disease. This case highlights the detrimental effects of anchoring bias. Rare causes of refractory anaemia should be considered in patients with haemoglobin disorders as the therapeutic approaches for these conditions are different. High suspicion on the part of the clinician and low threshold for workup of anaemia often aids in the diagnosis of coexisting conditions such as sideroblastic anaemia. Early diagnosis and treatment of sideroblastic anaemia improves patient outcomes and prevents long-term complications.

Iron-Storage Disorder Presenting as Chronic Diarrhea.

The involvement of the endocrine pancreas leading to bronze diabetes is well studied. However, little is known about the pathophysiology of iron dysregulation involving the exocrine pancreas. We present a unique association between the exocrine pancreas and iron dysregulation. A 45-year-old female presented with chronic diarrhea and low fecal elastase indicative of pancreatic exocrine dysfunction. MRI of the abdomen/pelvis showed iron deposition in the pancreas, suggesting an associated iron-storage disorder without features suggesting chronic pancreatitis. Association of an iron-storage disorder with pancreatic exocrine dysfunction has been reported only in one other case report. Pancreatic exocrine dysfunction can be directly associated with an iron-storage disorder that involves the pancreas. This should be included in the differential and diagnostic work-up of chronic diarrhea of unclear etiology. Based on the literature, we have highlighted the potential pathophysiology relevant to the case.