CAR-T cell therapy: Efficacy in management of cancers, adverse effects, dose-limiting toxicities and long-term follow up.

Chimeric Antigen Receptor T-cell (CAR-T) therapy has emerged as a groundbreaking and highly promising approach for the management of cancer. This paper reviews the efficacy of CAR-T therapy in the treatment of various hematological malignancies, also, with a mention of its effect on solid tumors, for which they have not received FDA approval yet. Different common and uncommon side effects are also discussed in this paper, with attention to the effect of each drug separately. By reviewing the recommendations of the FDA for CAR-T therapy research, we have extensively discussed dose-limiting toxicities. This further highlights the need for precise dosing strategies, striking a balance between therapeutic benefits and potential risks. Additionally, we reviewed the long-term follow-up of patients receiving CAR-T therapy to gain valuable insights into response durability and late-onset effects.

The Contemporary Role of Hematopoietic Stem Cell Transplantation in the Management of Chronic Myeloid Leukemia: Is It the Same in All Settings?

Hematopoietic stem cell transplantation (HSCT) for chronic myeloid leukemia (CML) patients has transitioned from the standard of care to a treatment option limited to those with unsatisfactory tyrosine kinase inhibitor (TKI) responses and advanced disease stages. In recent years, the threshold for undergoing HSCT has increased. Most CML patients now have life expectancies comparable to the general population, and therefore, the goal of therapy is shifting toward achieving treatment-free remission (TFR). While TKI discontinuation trials in CML show potential for achieving TFR, relapse risk is high, affirming allogeneic HSCT as the sole curative treatment. HSCT should be incorporated into treatment algorithms from the time of diagnosis and, in some patients, evaluated as soon as possible. In this review, we will look at some of the recent advances in HSCT, as well as its indication in the era of aiming for TFR in the presence of TKIs in CML.

Male Fertility and Fatherhood in Chronic Myeloid Leukemia: Current Understanding and Future Perspectives.

Chronic myeloid leukemia (CML), while traditionally a disease of the elderly, has recently risen in incidence among younger patients. Hence, fertility concerns have emerged considering the disease process and treatments, especially with the current scarce and conflicting recommendations. This review explores the impact of CML treatments including the first-line tyrosine kinase inhibitors (TKIs) and other treatments on male fertility in chronic myeloid leukemia (CML) patients. The aim of this review was to compile the available evidence on male fertility to ultimately tailor treatment plans for male CML patients for whom fertility and future chances for conception pose a concern. The data available on the conventional and newer TKIs to address fertility concerns were reviewed, particularly the potential long- and short-term effects. Also, the possible side effects on subsequent generations were a crucial focus point of this review to reach a more comprehensive CML management approach. We found and compared the evidence on TKIs approved to treat CML. We also reported the effects of hydroxyurea, interferon, and transplantation, which are considered second-line treatments. Our findings suggest that these drugs might have an undiscovered effect on fertility. More research with larger sample sizes and longer follow-up periods is essential to solidify our understanding of these effects.

Emerging roles of activating transcription factor 2 in the development of breast cancer: a comprehensive review.

Activating transcription factor 2 (ATF2) is a member of the leucine zipper family of DNA binding proteins that are responsible for regulating various genes that play an essential role in major biological and cellular functions. Since ATF2 plays a vital role in cellular proliferation and apoptosis, it is believed that it greatly affects the development of breast cancers. However, its exact role in breast cancer is incompletely understood. It remains a subject of debate, ambiguity, and continuous research. Several studies have suggested the role of ATF2 as an oncogene, promoting cellular proliferation and worsening the outcome of cancers. In contrast, other studies have postulated that ATF2 plays a tumor suppressive role in estrogen receptor-positive breast cancer. The ambiguity surrounding its role in breast cancer is the reason why there is an influx of recent studies and research in this area. In this narrative review, we investigate several studies that have been published about the role of ATF2 in breast cancer. We also explore studies that have examined the association between ATF2 and endocrine therapy resistance. ATF2 has been suggested to modulate estrogen receptor (ER) expression and activity, potentially affecting tamoxifen sensitivity in breast cancer cells. Therefore, the role of ATF2 in DNA repair mechanisms and drug resistance has been deeply explored in this review. Additionally, there are numerous ongoing clinical trials exploring the effect of targeting ATF2 pathways and mechanisms on the outcome of breast cancers, some of which we have discussed. The studies and clinical trials that are being conducted to understand the multifaceted role of ATF2 and its signaling pathways may provide valuable insight for developing efficient targeted therapeutic solutions to enhance the outcomes of breast cancer and overcome endocrine resistance. We suggest further research to elucidate the dual roles of ATF2 in breast cancer and potential therapeutic therapies for its treatment.

Artificial intelligence in sickle disease.

Artificial intelligence (AI) is rapidly becoming an established arm in medical sciences and clinical practice in numerous medical fields. Its implications have been rising and are being widely used in research, diagnostics, and treatment options for many pathologies, including sickle cell disease (SCD). AI has started new ways to improve risk stratification and diagnosing SCD complications early, allowing rapid intervention and reallocation of resources to high-risk patients. We reviewed the literature for established and new AI applications that may enhance management of SCD through advancements in diagnosing SCD and its complications, risk stratification, and the effect of AI in establishing an individualized approach in managing SCD patients in the future. Aim: to review the benefits and drawbacks of resources utilizing AI in clinical practice for improving the management for SCD cases.

Applications of Artificial Intelligence in Thalassemia: A Comprehensive Review.

Thalassemia is an autosomal recessive genetic disorder that affects the beta or alpha subunits of the hemoglobin structure. Thalassemia is classified as a hypochromic microcytic anemia and a definitive diagnosis of thalassemia is made by genetic testing of the alpha and beta genes. Thalassemia carries similar features to the other diseases that lead to microcytic hypochromic anemia, particularly iron deficiency anemia (IDA). Therefore, distinguishing between thalassemia and other causes of microcytic anemia is important to help in the treatment of the patients. Different indices and algorithms are used based on the complete blood count (CBC) parameters to diagnose thalassemia. In this article, we review how effective artificial intelligence is in aiding in the diagnosis and classification of thalassemia.

Comparative efficacy and safety of PD-1/PD-L1 inhibitors in triple negative breast cancer: a systematic review and network meta-analysis of randomized controlled trials.

BACKGROUND: Triple-Negative Breast Cancer (TNBC) is a lethal subtype of breast cancer with limited treatment options. The purpose of this Network Meta-Analysis (NMA) is to compare the efficacy and safety of inhibitors of programmed cell death 1 (PD-1) and programmed cell death ligand 1 (PD-L1) in treating TNBC. METHODS: Our search strategy was used in six databases: PubMed, Cochrane Library, Cumulative Index to Nursing and Allied Health Literature database, Embase, Scopus, and Web of Science up to November 2nd, 2022, as well as a thorough search in the most used trial registries. We included phase II and III randomized controlled trials that looked at the efficacy of PD-1/PD-L1 inhibitors in the treatment of TNBC and reported either Overall Survival (OS), Progression-Free Survival (PFS), or pathological Complete Response (pCR). The risk of bias was assessed utilizing Cochrane's risk of bias 2 tool, and the statistical analysis was performed using a frequentist contrast-based method for NMA by employing standard pairwise meta-analysis applying random effects model. RESULTS: 12 trials (5324 patients) were included in our NMA including seven phase III trials. Pembrolizumab in a neoadjuvant setting achieved a pooled OS of 0.82 (95% Confidence Interval (CI) 0.65 to 1.03), a PFS of 0.82 (95% CI 0.71 to 0.94) and a pCR 2.79 (95% CI 1.07 to 7.24) compared to Atezolizumab's OS of 0.92 (95% CI 0.74 to 1.15), PFS of 0.82 (95% CI 0.69 to 0.97), and pCR of 1.94 (95% CI 0.86 to 4.37). Atezolizumab had less grade ≥ 3 adverse events (OR 1.48, 95% CI 0.90 to 2.42) than Pembrolizumab (OR 1.90, 95% CI 1.08 to 3.33) in the neoadjuvant setting. CONCLUSIONS: PD-1/PD-L1 inhibitors exhibited varying efficacy in terms of OS, PFS, and pCR. They were associated with an increase in immune-related adverse effects. When used early in the course of TNBC, PD-1/PD-L1 inhibitors exert their maximum benefit. Durvalumab as a maintenance treatment instead of chemotherapy has shown promising outcomes. Future studies should focus on PD-L1 expression status and TNBC subtypes, since these factors may contribute to the design of individualized TNBC therapy regimens. Systematic review registration PROSPERO Identifier: CRD42022380712.

Applications of Machine Learning in Chronic Myeloid Leukemia.

Chronic myeloid leukemia (CML) is a myeloproliferative neoplasm characterized by dysregulated growth and the proliferation of myeloid cells in the bone marrow caused by the BCR-ABL1 fusion gene. Clinically, CML demonstrates an increased production of mature and maturing granulocytes, mainly neutrophils. When a patient is suspected to have CML, peripheral blood smears and bone marrow biopsies may be manually examined by a hematologist. However, confirmatory testing for the BCR-ABL1 gene is still needed to confirm the diagnosis. Despite tyrosine kinase inhibitors (TKIs) being the mainstay of treatment for patients with CML, different agents should be used in different patients given their stage of disease and comorbidities. Moreover, some patients do not respond well to certain agents and some need more aggressive courses of therapy. Given the innovations and development that machine learning (ML) and artificial intelligence (AI) have undergone over the years, multiple models and algorithms have been put forward to help in the assessment and treatment of CML. In this review, we summarize the recent studies utilizing ML algorithms in patients with CML. The search was conducted on the PubMed/Medline and Embase databases and yielded 66 full-text articles and abstracts, out of which 11 studies were included after screening against the inclusion criteria. The studies included show potential for the clinical implementation of ML models in the diagnosis, risk assessment, and treatment processes of patients with CML.

Applications of Artificial Intelligence in Thrombocytopenia.

Thrombocytopenia is a medical condition where blood platelet count drops very low. This drop in platelet count can be attributed to many causes including medication, sepsis, viral infections, and autoimmunity. Clinically, the presence of thrombocytopenia might be very dangerous and is associated with poor outcomes of patients due to excessive bleeding if not addressed quickly enough. Hence, early detection and evaluation of thrombocytopenia is essential for rapid and appropriate intervention for these patients. Since artificial intelligence is able to combine and evaluate many linear and nonlinear variables simultaneously, it has shown great potential in its application in the early diagnosis, assessing the prognosis and predicting the distribution of patients with thrombocytopenia. In this review, we conducted a search across four databases and identified a total of 13 original articles that looked at the use of many machine learning algorithms in the diagnosis, prognosis, and distribution of various types of thrombocytopenia. We summarized the methods and findings of each article in this review. The included studies showed that artificial intelligence can potentially enhance the clinical approaches used in the diagnosis, prognosis, and treatment of thrombocytopenia.

Applications of Artificial Intelligence in Philadelphia-Negative Myeloproliferative Neoplasms.

Philadelphia-negative (Ph-) myeloproliferative neoplasms (MPNs) are a group of hematopoietic malignancies identified by clonal proliferation of blood cell lineages and encompasses polycythemia vera (PV), essential thrombocythemia (ET), and primary myelofibrosis (PMF). The clinical and laboratory features of Philadelphia-negative MPNs are similar, making them difficult to diagnose, especially in the preliminary stages. Because treatment goals and progression risk differ amongst MPNs, accurate classification and prognostication are critical for optimal management. Artificial intelligence (AI) and machine learning (ML) algorithms provide a plethora of possible tools to clinicians in general, and particularly in the field of malignant hematology, to better improve diagnosis, prognosis, therapy planning, and fundamental knowledge. In this review, we summarize the literature discussing the application of AI and ML algorithms in patients with diagnosed or suspected Philadelphia-negative MPNs. A literature search was conducted on PubMed/MEDLINE, Embase, Scopus, and Web of Science databases and yielded 125 studies, out of which 17 studies were included after screening. The included studies demonstrated the potential for the practical use of ML and AI in the diagnosis, prognosis, and genomic landscaping of patients with Philadelphia-negative MPNs.

Proteome changes in autosomal recessive primary microcephaly.

BACKGROUND/AIM: Autosomal recessive primary microcephaly (MCPH) is a rare and genetically heterogeneous group of disorders characterized by intellectual disability and microcephaly at birth, classically without further organ involvement. MCPH3 is caused by biallelic variants in the cyclin-dependent kinase 5 regulatory subunit-associated protein 2 gene CDK5RAP2. In the corresponding Cdk5rap2 mutant or Hertwig's anemia mouse model, congenital microcephaly as well as defects in the hematopoietic system, germ cells and eyes have been reported. The reduction in brain volume, particularly affecting gray matter, has been attributed mainly to disturbances in the proliferation and survival of early neuronal progenitors. In addition, defects in dendritic development and synaptogenesis exist that affect the excitation-inhibition balance. Here, we studied proteomic changes in cerebral cortices of Cdk5rap2 mutant mice. MATERIAL AND METHODS: We used large-gel two-dimensional gel (2-DE) electrophoresis to separate cortical proteins. 2-DE gels were visualized by a trained observer on a light box. Spot changes were considered with respect to presence/absence, quantitative variation and altered mobility. RESULT: We identified a reduction in more than 30 proteins that play a role in processes such as cell cytoskeleton dynamics, cell cycle progression, ciliary functions and apoptosis. These proteome changes in the MCPH3 model can be associated with various functional and morphological alterations of the developing brain. CONCLUSION: Our results shed light on potential protein candidates for the disease-associated phenotype reported in MCPH3.

Clinical Implications of COVID-19 Presence in CSF: Systematic Review of Case Reports.

This systematic review focused on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) patients that had detected SARS-CoV-2 virus in cerebrospinal fluid (CSF). A systematic literature search was carried out in PubMed, Embase, Scopus, Web of Science, Medrxiv, and Biorxiv databases from inception to 19 December 2021. Case reports or case series involving patients with proved SARS-CoV-2 presence in CSF by polymerize chain reaction were included. Our search strategy produced 23 articles documenting a total of 23 patients with positive SARS-CoV-2 in the CSF. Fever (55%) was the most common symptom, followed by headaches (41%), cough (32%), and vomiting/nausea (32%). The majority of the cases included was encephalitis (57%), 8 of which were confirmed by magnetic resonance imaging. The second most prevalent presentation was meningitis. The cerebral spinal fluid analysis found disparities in protein levels and normal glucose levels in most cases. This study demonstrates that SARS-CoV-2 can enter the nervous system via various routes and cause CNS infection symptoms. SARS-CoV-2 has been shown to infect the CNS even when no respiratory symptoms are present and nasopharyngeal swabs are negative. As a result, SARS-CoV-2 should be considered as a possible cause of CNS infection and tested for in the CSF.

Impact of Smoking on COVID-19 Symptoms in Non-Vaccinated Patients: A Matched Observational Study from Qatar.

Purpose: Predisposition to acute illness from COVID-19 is suggested to correlate with cigarette smoking as it augments the risk of developing cardiovascular and respiratory illnesses, including infections. However, the effects of smoking on COVID-19 symptoms are not well described and controversial. In this study, we aim to explore the associations between smoking and COVID-19 symptoms. Subjects and Methods: A cross-sectional study using the Ministry of Public Health (MoPH), Qatar database was administered to a Qatari population with confirmed COVID-19 disease who filled in pre-defined phone-call questionnaire between 27th February 2020 and 31st December 2020. We analyzed 11,701 non-vaccinated COVID-19 individuals (2952 smokers and 8749 non-smokers) with confirmed RT-PCR test results. The association of smoking and the presence of symptoms as well as patient characteristics was calculated using Pearson's Chi-square and Fisher's exact tests, adjusting for potential covariates. Results: Compared with the non-smokers, symptomatic COVID-19 infection is significantly higher in smokers. In addition, we found fever as the most common symptom developed in COVID-19 patients followed by cough, headache, muscle ache, and sore throat. As compared to other symptoms, association of smoking with chills and abdominal pain was less evident (P < 0.05 and P < 0.001, respectively). However, both groups showed similar rates of developing cough. Conclusion: In conclusion, smoking is associated with COVID-19 symptoms frequency in non-vaccinated patients; nevertheless, further investigations are necessary to understand the mechanism of this association which could generate new targets for the management of COVID-19 in smoker patients.

HPV and Recurrent Respiratory Papillomatosis: A Brief Review.

Recurrent Respiratory Papillomatosis (RRP) is a rare but severe manifestation of human papillomavirus (HPV). As our knowledge about HPV infections has expanded, it has become possible to understand the course of RRP disease and unravel plausible efficient methods to manage the disease. However, the surge in reports on HPV has not been accompanied by a similar increase in research about RRP specifically. In this paper, we review the clinical manifestation and typical presentation of the illness. In addition, the pathogenesis and progression of the disease are described. On the other hand, we discuss the types of treatments currently available and future treatment strategies. The role of vaccination in both the prevention and treatment of RRP will also be reviewed. We believe this review is essential to update the general knowledge on RRP with the latest information available to date to enhance our understanding of RRP and its management.

Predictors of long-term survival after pancreaticoduodenectomy for peri-ampullary adenocarcinoma: A retrospective study of 5-year survivors.

BACKGROUND: Pancreaticoduodenectomy (PD) is the standard curative treatment for periampullary tumors. The aim of this study is to report the incidence and predictors of long-term survival (≥ 5 years) after PD. METHODS: This study included patients who underwent PD for pathologically proven periampullary adenocarcinomas. Patients were divided into 2 groups: group (I) patients who survived less than 5 years and group (II) patients who survived ≥ 5 years. RESULTS: There were 47 (20.6%) long-term survivors (≥ 5 years) among 228 patients underwent PD for periampullary adenocarcinoma. Patients with ampullary adenocarcinoma represented 31 (66.0%) of the long-term survivors. Primary analysis showed that favourable factors for long-term survival include age < 60 years old, serum CEA < 5 ng/mL, serum CA 19-9 < 37 U/mL, non-cirrhotic liver, tumor size < 2 cm, site of primary tumor, postoperative pancreatic fistula, R0 resection, postoperative chemotherapy, and no recurrence. Multivariate analysis demonstrated that CA 19-9 < 37 U/mL [OR (95% CI) = 1.712 (1.248-2.348), P = 0.001], smaller tumor size [OR (95% CI )= 1.335 (1.032-1.726), P = 0.028] and Ro resection [OR (95% CI) = 3.098 (2.095-4.582), P < 0.001] were independent factors for survival ≥ 5 years. The prognosis was best for ampullary adenocarcinoma, for which the median survival was 54 months and 5-year survival rate was 39.0%, and the poorest was pancreatic head adenocarcinoma, for which the median survival was 27 months and 5-year survival rate was 7%. CONCLUSIONS: The majority of long-term survivors after PD for periampullary adenocarcinoma are patients with ampullary tumor. CA 19-9 < 37 U/mL, smaller tumor size, and R0 resection were found to be independent factors for long-term survival ≥ 5 years.