A. M. Roy, Supritha Chintamaneni, S. Alaklabi, Hassan Awada, Kristopher Attwood, Shipra Gandhi
Background: Multiple randomized controlled trials (RCTs) have investigated the impact of adding checkpoint inhibitors to neoadjuvant chemotherapy for triple-negative breast cancer (TNBC) patients. However, there is a lack of biomarkers that can help identify patients who would benefit from combination therapy. Our research identifies response predictors and assesses the effectiveness of adding immunotherapy to neoadjuvant chemotherapy for TNBC patients. Methods: We identified eligible RCTs by searching PubMed, Cochrane CENTRAL, Embase, and oncological meetings. For this meta-analysis, we obtained odds ratios using the standard random effects model. To assess the heterogeneity of the study outcomes, the I2 statistic was obtained. Potential bias was assessed using a funnel plot and the corresponding Egger’s test. Results: In total, 1637 patients with TNBC were included from five RCTs. Neoadjuvant chemoimmunotherapy significantly improved pCR when compared to neoadjuvant chemotherapy alone. In the subgroup analysis, neoadjuvant chemoimmunotherapy showed higher pCR rates in both Programmed death-ligand 1 (PD-L1)-positive and PD-L1-negative TNBC patients. An Eastern Cooperative Oncology Group (ECOG) performance score (PS) of 0 correlated with increased pCRs (OR = 1.9, p < 0.001) in neoadjuvant chemoimmunotherapy vs. neoadjuvant chemotherapy, but no benefit was observed for patients with ECOG PS 1. Nodal positivity was significantly associated with pCR (OR = 2.52, p < 0.001), while neoadjuvant chemoimmunotherapy did not benefit patients with negative lymph nodes. Conclusions: Checkpoint inhibition and neoadjuvant chemotherapy significantly increased pCRs in TNBC patients, regardless of their PDL-1 status. Additional checkpoint inhibitors improved pCR rates, mainly for patients with ECOG PS 0 and lymph node-positive disease.
{"title":"Predictors of Complete Pathological Response with Chemoimmunotherapy in Triple-Negative Breast Cancer: A Meta-Analysis","authors":"A. M. Roy, Supritha Chintamaneni, S. Alaklabi, Hassan Awada, Kristopher Attwood, Shipra Gandhi","doi":"10.3390/onco4010001","DOIUrl":"https://doi.org/10.3390/onco4010001","url":null,"abstract":"Background: Multiple randomized controlled trials (RCTs) have investigated the impact of adding checkpoint inhibitors to neoadjuvant chemotherapy for triple-negative breast cancer (TNBC) patients. However, there is a lack of biomarkers that can help identify patients who would benefit from combination therapy. Our research identifies response predictors and assesses the effectiveness of adding immunotherapy to neoadjuvant chemotherapy for TNBC patients. Methods: We identified eligible RCTs by searching PubMed, Cochrane CENTRAL, Embase, and oncological meetings. For this meta-analysis, we obtained odds ratios using the standard random effects model. To assess the heterogeneity of the study outcomes, the I2 statistic was obtained. Potential bias was assessed using a funnel plot and the corresponding Egger’s test. Results: In total, 1637 patients with TNBC were included from five RCTs. Neoadjuvant chemoimmunotherapy significantly improved pCR when compared to neoadjuvant chemotherapy alone. In the subgroup analysis, neoadjuvant chemoimmunotherapy showed higher pCR rates in both Programmed death-ligand 1 (PD-L1)-positive and PD-L1-negative TNBC patients. An Eastern Cooperative Oncology Group (ECOG) performance score (PS) of 0 correlated with increased pCRs (OR = 1.9, p < 0.001) in neoadjuvant chemoimmunotherapy vs. neoadjuvant chemotherapy, but no benefit was observed for patients with ECOG PS 1. Nodal positivity was significantly associated with pCR (OR = 2.52, p < 0.001), while neoadjuvant chemoimmunotherapy did not benefit patients with negative lymph nodes. Conclusions: Checkpoint inhibition and neoadjuvant chemotherapy significantly increased pCRs in TNBC patients, regardless of their PDL-1 status. Additional checkpoint inhibitors improved pCR rates, mainly for patients with ECOG PS 0 and lymph node-positive disease.","PeriodicalId":74339,"journal":{"name":"Onco","volume":"293 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139152604","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pancreatic cancer (PC) is one of the most fatal cancers, and there is an urgent need to develop new anticancer agents with fewer side effects for the treatment of this condition. A patient-derived xenograft (PDX) mouse model transplanted with cancer tissue from patients is widely accepted as the best preclinical model for evaluating the anticancer potential of drug candidates. Fucoxanthin (Fx) is a highly polar carotenoid contained in edible marine brown algae and possesses anticancer activity. However, there is a lack of data on the effects of Fx in PDX models. We investigated the anticancer effects of Fx in PDX mice transplanted with cancer tissues derived from a patient with PC (PC-PDX) using comprehensive protein expression assay. Fx administration (0.3%Fx diet) ad libitum for 27 days significantly abrogated tumor development (0.4-fold) and induced tumor differentiation in PC-PDX mice, as compared to those in the control mice. Fx significantly upregulated the expression of non-glycanated DCN (2.4-fold), tended to increase the expressions of p-p38(Thr180/Tyr182) (1.6-fold) and pJNK(Thr183/Tyr185) (1.8-fold), significantly downregulated IGFBP2 (0.6-fold) and EpCAM (0.7-fold), and tended to decrease LCN2 (0.6-fold) levels in the tumors of the PC-PDX mice, as compared to those in the control mice. Some of the protein expression patterns were consistent with the in vitro experiments. That is, treatment of fucoxanthinol (FxOH), a prime metabolite derived from dietary Fx, enhanced non-glycanated DCN, p-p38(Thr180/Tyr182), and pJNK(Thr183/Tyr185) levels in human PC PANC-1 and BxPC-3 cells.These results suggested that Fx exerts anticancer and differentiation effects in a PC-PDX mice through alterations of some multifunctional molecules.
{"title":"Anticancer Effects of Fucoxanthin in a PDX Model of Advanced Stage Pancreatic Cancer with Alteration of Several Multifunctional Molecules","authors":"Masaru Terasaki, Sally Suzuki, Takuji Tanaka, Hayato Maeda, Masaki Shibata, Kazuo Miyashita, Yasuhiro Kuramitsu, Junichi Hamada, Tohru Ohta, Shigehiro Yagishita, Akinobu Hamada, Yasunari Sakamoto, Susumu Hijioka, Chigusa Morizane, Mami Takahashi","doi":"10.3390/onco3040016","DOIUrl":"https://doi.org/10.3390/onco3040016","url":null,"abstract":"Pancreatic cancer (PC) is one of the most fatal cancers, and there is an urgent need to develop new anticancer agents with fewer side effects for the treatment of this condition. A patient-derived xenograft (PDX) mouse model transplanted with cancer tissue from patients is widely accepted as the best preclinical model for evaluating the anticancer potential of drug candidates. Fucoxanthin (Fx) is a highly polar carotenoid contained in edible marine brown algae and possesses anticancer activity. However, there is a lack of data on the effects of Fx in PDX models. We investigated the anticancer effects of Fx in PDX mice transplanted with cancer tissues derived from a patient with PC (PC-PDX) using comprehensive protein expression assay. Fx administration (0.3%Fx diet) ad libitum for 27 days significantly abrogated tumor development (0.4-fold) and induced tumor differentiation in PC-PDX mice, as compared to those in the control mice. Fx significantly upregulated the expression of non-glycanated DCN (2.4-fold), tended to increase the expressions of p-p38(Thr180/Tyr182) (1.6-fold) and pJNK(Thr183/Tyr185) (1.8-fold), significantly downregulated IGFBP2 (0.6-fold) and EpCAM (0.7-fold), and tended to decrease LCN2 (0.6-fold) levels in the tumors of the PC-PDX mice, as compared to those in the control mice. Some of the protein expression patterns were consistent with the in vitro experiments. That is, treatment of fucoxanthinol (FxOH), a prime metabolite derived from dietary Fx, enhanced non-glycanated DCN, p-p38(Thr180/Tyr182), and pJNK(Thr183/Tyr185) levels in human PC PANC-1 and BxPC-3 cells.These results suggested that Fx exerts anticancer and differentiation effects in a PC-PDX mice through alterations of some multifunctional molecules.","PeriodicalId":74339,"journal":{"name":"Onco","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135925435","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Vasiliki Gkioka, Olga Balaoura, Maria Goulielmaki, Constantin N. Baxevanis
Cancer biobanks have a crucial role in moving forward the field of translational cancer research and, therefore, have been promoted as indispensable tools for advancing basic biomedical research to preclinical and clinical research, ultimately leading to the design of clinical trials. Consequently, they play an essential role in the establishment of personalized oncology by combining biological data with registries of detailed medical records. The availability of complete electronic medical reports from individualized patients has led to personalized approaches for diagnosis, prognosis, and prediction. To this end, identifying risk factors at early time points is important for designing more effective treatments unique for each patient. Under this aspect, biobanking is essential for accomplishing improvements in the field of precision oncology via the discovery of biomarkers related to cellular and molecular pathways regulating oncogenic signaling. In general terms, biological samples are thought to reflect the patient’s disease biology, but under certain conditions, these may also represent responses to various biological stresses. Divergent collection, handling, and storage methods may significantly change biosamples’ inherent biological properties. The alteration or loss of biological traits post-collection would lead to the discovery of nonreliable biomarkers and, consequently, to irreproducible results, thus constituting a formidable obstacle regarding the successful translation of preclinical research to clinical approaches. Therefore, a necessary prerequisite for successful biobanking is that the stored biological samples retain their biological characteristics unchanged. The application of quality standards for biospecimen collection and storage could be useful for generating encouraging preclinical data leading to the successful translation to clinical treatment approaches. Herein, we aim to comprehensively review the issues linked to biobank implementation for promoting cancer research.
{"title":"The Organization of Contemporary Biobanks for Translational Cancer Research","authors":"Vasiliki Gkioka, Olga Balaoura, Maria Goulielmaki, Constantin N. Baxevanis","doi":"10.3390/onco3040015","DOIUrl":"https://doi.org/10.3390/onco3040015","url":null,"abstract":"Cancer biobanks have a crucial role in moving forward the field of translational cancer research and, therefore, have been promoted as indispensable tools for advancing basic biomedical research to preclinical and clinical research, ultimately leading to the design of clinical trials. Consequently, they play an essential role in the establishment of personalized oncology by combining biological data with registries of detailed medical records. The availability of complete electronic medical reports from individualized patients has led to personalized approaches for diagnosis, prognosis, and prediction. To this end, identifying risk factors at early time points is important for designing more effective treatments unique for each patient. Under this aspect, biobanking is essential for accomplishing improvements in the field of precision oncology via the discovery of biomarkers related to cellular and molecular pathways regulating oncogenic signaling. In general terms, biological samples are thought to reflect the patient’s disease biology, but under certain conditions, these may also represent responses to various biological stresses. Divergent collection, handling, and storage methods may significantly change biosamples’ inherent biological properties. The alteration or loss of biological traits post-collection would lead to the discovery of nonreliable biomarkers and, consequently, to irreproducible results, thus constituting a formidable obstacle regarding the successful translation of preclinical research to clinical approaches. Therefore, a necessary prerequisite for successful biobanking is that the stored biological samples retain their biological characteristics unchanged. The application of quality standards for biospecimen collection and storage could be useful for generating encouraging preclinical data leading to the successful translation to clinical treatment approaches. Herein, we aim to comprehensively review the issues linked to biobank implementation for promoting cancer research.","PeriodicalId":74339,"journal":{"name":"Onco","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136096673","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Non-small-cell lung cancer (NSCLC) is a heterogeneous group of diseases accounting for 80–85% of lung cancers. A molecular subset of NSCLC (1–2.5%) harboring molecular rearrangements of the tyrosine kinase gene ROS1 is defined as ROS1-positive and is almost exclusively diagnosed in patients with lung adenocarcinoma histology, predominantly nonsmokers. ROS1 is constitutively activated by molecular rearrangements and acts as a main driver of lung carcinogenesis. These findings have provided a strong rationale for the clinical use of tyrosine kinase inhibitors that target ROS1; these inhibitors block ROS1-positive NSCLC and provide clinical benefit. Crizotinib was introduced as a first-line treatment for ROS1-positive NSCLCs, with 75–80% of patients responding and a PFS of about 20 months. More recently developed ROS1-TKIs, such as entrectinib, lorlatinib, taletrectinib, repotrectinib and NVL-520, are active against some resistant ROS1 mutants appearing during crizotinib therapy and more active against brain metastases, frequent in ROS1-positive NSCLC. The development of resistance mechanisms represents a great limitation for the targeted treatment of ROS1-positive NSCLCs with TKIs.
{"title":"ROS1-Rearranged Lung Adenocarcinoma: From Molecular Genetics to Target Therapy","authors":"U. Testa, G. Castelli, E. Pelosi","doi":"10.3390/onco3030014","DOIUrl":"https://doi.org/10.3390/onco3030014","url":null,"abstract":"Non-small-cell lung cancer (NSCLC) is a heterogeneous group of diseases accounting for 80–85% of lung cancers. A molecular subset of NSCLC (1–2.5%) harboring molecular rearrangements of the tyrosine kinase gene ROS1 is defined as ROS1-positive and is almost exclusively diagnosed in patients with lung adenocarcinoma histology, predominantly nonsmokers. ROS1 is constitutively activated by molecular rearrangements and acts as a main driver of lung carcinogenesis. These findings have provided a strong rationale for the clinical use of tyrosine kinase inhibitors that target ROS1; these inhibitors block ROS1-positive NSCLC and provide clinical benefit. Crizotinib was introduced as a first-line treatment for ROS1-positive NSCLCs, with 75–80% of patients responding and a PFS of about 20 months. More recently developed ROS1-TKIs, such as entrectinib, lorlatinib, taletrectinib, repotrectinib and NVL-520, are active against some resistant ROS1 mutants appearing during crizotinib therapy and more active against brain metastases, frequent in ROS1-positive NSCLC. The development of resistance mechanisms represents a great limitation for the targeted treatment of ROS1-positive NSCLCs with TKIs.","PeriodicalId":74339,"journal":{"name":"Onco","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46965204","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
E. Vigia, L. Ramalhete, E. Filipe, L. Bicho, A. Nobre, P. Mira, M. Macedo, C. Aguiar, S. Corado, B. Chumbinho, Jorge Balaia, P. Custódio, J. Gonçalves, H. Marques
Pancreatic ductal adenocarcinoma is an invasive tumor with similar incidence and mortality rates. Pancreaticoduodenectomy has morbidity and mortality rates of up to 60% and 5%, respectively. The purpose of our study was to assess preoperative features contributing to unfavorable 1-year survival prognosis. Study Design: Retrospective, single-center study evaluating the impact of preoperative features on short-term survival outcomes in head PDAC patients. Forty-four prior features of 172 patients were tested using different supervised machine learning models. Patient records were randomly divided into training and validation sets (80–20%, respectively), and model performance was assessed by area under curve (AUC) and classification accuracy (CA). Additionally, 33 patients were included as an independent revalidation or holdout dataset group. Results: Eleven relevant features were identified: age, sex, Ca-19-9, jaundice, ERCP with biliary stent, neutrophils, lymphocytes, lymphocyte/neutrophil ratio, neoadjuvant treatment, imaging tumor size, and ASA. Tree regression (tree model) and logistic regression (LR) performed better than the other tested models. The tree model had an AUC = 0.92 and CA = 0.85. LR had an AUC = 0.74 and CA = 0.78, allowing the development of a nomogram based on absolute feature significance. The best performance model was the tree model which allows us to have a decision tree to help clinical decisions. Discussion and conclusions: Based only on preoperative data, it was possible to predict 1-year survival (91.5% vs. 78.1% alive and 70.9% vs. 76.6% deceased for the tree model and LR, respectively). These results contribute to informed decision-making in the selection of which patients with PDAC can benefit from pancreatoduodenectomy. A machine learning algorithm was developed for the recognition of unfavorable 1-year survival prognosis in patients with pancreatic ductal adenocarcinoma. This will contribute to the identification of patients who would benefit from pancreatoduodenectomy. In our cohort, the tree regression model had an AUC = 0.92 and CA = 0.85, whereas the logistic regression had an AUC = 0.74 and CA = 0.78. To further inform decision-making, a decision tree based on tree regression was developed.
{"title":"Machine Learning-Based Model Helps to Decide which Patients May Benefit from Pancreatoduodenectomy","authors":"E. Vigia, L. Ramalhete, E. Filipe, L. Bicho, A. Nobre, P. Mira, M. Macedo, C. Aguiar, S. Corado, B. Chumbinho, Jorge Balaia, P. Custódio, J. Gonçalves, H. Marques","doi":"10.3390/onco3030013","DOIUrl":"https://doi.org/10.3390/onco3030013","url":null,"abstract":"Pancreatic ductal adenocarcinoma is an invasive tumor with similar incidence and mortality rates. Pancreaticoduodenectomy has morbidity and mortality rates of up to 60% and 5%, respectively. The purpose of our study was to assess preoperative features contributing to unfavorable 1-year survival prognosis. Study Design: Retrospective, single-center study evaluating the impact of preoperative features on short-term survival outcomes in head PDAC patients. Forty-four prior features of 172 patients were tested using different supervised machine learning models. Patient records were randomly divided into training and validation sets (80–20%, respectively), and model performance was assessed by area under curve (AUC) and classification accuracy (CA). Additionally, 33 patients were included as an independent revalidation or holdout dataset group. Results: Eleven relevant features were identified: age, sex, Ca-19-9, jaundice, ERCP with biliary stent, neutrophils, lymphocytes, lymphocyte/neutrophil ratio, neoadjuvant treatment, imaging tumor size, and ASA. Tree regression (tree model) and logistic regression (LR) performed better than the other tested models. The tree model had an AUC = 0.92 and CA = 0.85. LR had an AUC = 0.74 and CA = 0.78, allowing the development of a nomogram based on absolute feature significance. The best performance model was the tree model which allows us to have a decision tree to help clinical decisions. Discussion and conclusions: Based only on preoperative data, it was possible to predict 1-year survival (91.5% vs. 78.1% alive and 70.9% vs. 76.6% deceased for the tree model and LR, respectively). These results contribute to informed decision-making in the selection of which patients with PDAC can benefit from pancreatoduodenectomy. A machine learning algorithm was developed for the recognition of unfavorable 1-year survival prognosis in patients with pancreatic ductal adenocarcinoma. This will contribute to the identification of patients who would benefit from pancreatoduodenectomy. In our cohort, the tree regression model had an AUC = 0.92 and CA = 0.85, whereas the logistic regression had an AUC = 0.74 and CA = 0.78. To further inform decision-making, a decision tree based on tree regression was developed.","PeriodicalId":74339,"journal":{"name":"Onco","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44888482","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
C. Baxevanis, S. Stokidis, M. Goulielmaki, A. Gritzapis, S. Fortis
Background: Various studies have reported associations between frequencies of total peripheral blood lymphocytes and prostate cancer prognosis, but none so far has addressed the prognostic role of CD8+ T-lymphocyte subsets. Methods: A total of 43 prostate cancer patients with metastatic disease and 81 patients with non-metastatic disease were included in this study. Flow cytometry analyses were employed for determining the frequencies of peripheral CD8+ T-lymphocyte subsets. Results: Statistically significant lower levels of terminally differentiated effector (TEMRA) cells in patients with non-metastatic disease vs. patients with metastatic disease were observed. Central memory (CM) and effector memory (EM) CD8+ subsets, were found to be significantly higher in patients with non-metastatic disease vs. patients with metastatic disease. A similar profile was revealed when these CD8+ subsets were analyzed based on the patients’ Gleason scores, as well as by combined disease stage (i.e., non-metastatic vs. metastatic disease) and Gleason score. Conclusions: Peripheral blood-derived CD8+ T-lymphocyte memory subsets could function as biomarkers for the prognosis of PCa.
{"title":"Peripheral Blood CD8+ T-Lymphocyte Subsets Are Associated with Prognosis in Prostate Cancer Patients","authors":"C. Baxevanis, S. Stokidis, M. Goulielmaki, A. Gritzapis, S. Fortis","doi":"10.3390/onco3030012","DOIUrl":"https://doi.org/10.3390/onco3030012","url":null,"abstract":"Background: Various studies have reported associations between frequencies of total peripheral blood lymphocytes and prostate cancer prognosis, but none so far has addressed the prognostic role of CD8+ T-lymphocyte subsets. Methods: A total of 43 prostate cancer patients with metastatic disease and 81 patients with non-metastatic disease were included in this study. Flow cytometry analyses were employed for determining the frequencies of peripheral CD8+ T-lymphocyte subsets. Results: Statistically significant lower levels of terminally differentiated effector (TEMRA) cells in patients with non-metastatic disease vs. patients with metastatic disease were observed. Central memory (CM) and effector memory (EM) CD8+ subsets, were found to be significantly higher in patients with non-metastatic disease vs. patients with metastatic disease. A similar profile was revealed when these CD8+ subsets were analyzed based on the patients’ Gleason scores, as well as by combined disease stage (i.e., non-metastatic vs. metastatic disease) and Gleason score. Conclusions: Peripheral blood-derived CD8+ T-lymphocyte memory subsets could function as biomarkers for the prognosis of PCa.","PeriodicalId":74339,"journal":{"name":"Onco","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49316209","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
NUP98 fusions constitute a small subgroup of AML patients and remain a high-risk AML subtype. There are approximately 30 types of NUP98 fusions identified in AML patients. These patients show resistance to currently available therapies and poor clinical outcomes. NUP98 fusions with different fusion partners have oncogenic transformation potential. This review describes how the NUP98 gene acquires oncogenic properties after rearrangement with multiple partners. In the mechanistic part, the formation of nuclear bodies and dysregulation of the HoxA/Meis1 pathway are highlighted. This review also discusses mutational signatures among NUP98 fusions and their significance in leukemogenesis. It also discusses the clinical implications of NUP98 fusions and their associated mutations in AML patients. Furthermore, it highlights therapeutic vulnerabilities in these leukemias that can be exploited as therapeutic strategies. Lastly, this review discusses the gaps in our knowledge regarding NUP98 fusions in AML, as well as future research opportunities.
{"title":"NUP98 Rearrangements in AML: Molecular Mechanisms and Clinical Implications","authors":"Sagarajit Mohanty","doi":"10.3390/onco3030011","DOIUrl":"https://doi.org/10.3390/onco3030011","url":null,"abstract":"NUP98 fusions constitute a small subgroup of AML patients and remain a high-risk AML subtype. There are approximately 30 types of NUP98 fusions identified in AML patients. These patients show resistance to currently available therapies and poor clinical outcomes. NUP98 fusions with different fusion partners have oncogenic transformation potential. This review describes how the NUP98 gene acquires oncogenic properties after rearrangement with multiple partners. In the mechanistic part, the formation of nuclear bodies and dysregulation of the HoxA/Meis1 pathway are highlighted. This review also discusses mutational signatures among NUP98 fusions and their significance in leukemogenesis. It also discusses the clinical implications of NUP98 fusions and their associated mutations in AML patients. Furthermore, it highlights therapeutic vulnerabilities in these leukemias that can be exploited as therapeutic strategies. Lastly, this review discusses the gaps in our knowledge regarding NUP98 fusions in AML, as well as future research opportunities.","PeriodicalId":74339,"journal":{"name":"Onco","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42661333","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Esophageal cancer is a formidable challenge in the realm of cancer treatment. Conventional methods such as surgery, chemotherapy, and immunotherapy have demonstrated limited success rates in managing this disease. In response, targeted drug therapies have emerged as a promising strategy to improve outcomes for patients. These therapies aim to disrupt specific pathways involved in the growth and development of esophageal cancer cells. This review explores various drugs used to target specific pathways, including cetuximab and monoclonal antibodies (gefitinib) that target the epidermal growth factor receptor (EGFR), trastuzumab that targets human epidermal growth factor receptor 2 (HER-2), drugs targeting the vascular endothelial growth factor receptor (VEGFR), mTOR inhibitors, and cMET inhibitors. Additionally, the article discusses the impact of drug resistance on the effectiveness of these therapies, highlighting factors such as cancer stem cells, cancer-associated fibroblasts, immune-inflammatory cells, cytokines, hypoxia, and growth factors. While drug targeting approaches do not provide a complete cure for esophageal cancer due to drug resistance and associated side effects, they offer potential for improving patient survival rates.
{"title":"Precision Medicine Revolutionizing Esophageal Cancer Treatment: Surmounting Hurdles and Enhancing Therapeutic Efficacy through Targeted Drug Therapies","authors":"Poojarani Panda, H. Verma, L. Bhaskar","doi":"10.3390/onco3030010","DOIUrl":"https://doi.org/10.3390/onco3030010","url":null,"abstract":"Esophageal cancer is a formidable challenge in the realm of cancer treatment. Conventional methods such as surgery, chemotherapy, and immunotherapy have demonstrated limited success rates in managing this disease. In response, targeted drug therapies have emerged as a promising strategy to improve outcomes for patients. These therapies aim to disrupt specific pathways involved in the growth and development of esophageal cancer cells. This review explores various drugs used to target specific pathways, including cetuximab and monoclonal antibodies (gefitinib) that target the epidermal growth factor receptor (EGFR), trastuzumab that targets human epidermal growth factor receptor 2 (HER-2), drugs targeting the vascular endothelial growth factor receptor (VEGFR), mTOR inhibitors, and cMET inhibitors. Additionally, the article discusses the impact of drug resistance on the effectiveness of these therapies, highlighting factors such as cancer stem cells, cancer-associated fibroblasts, immune-inflammatory cells, cytokines, hypoxia, and growth factors. While drug targeting approaches do not provide a complete cure for esophageal cancer due to drug resistance and associated side effects, they offer potential for improving patient survival rates.","PeriodicalId":74339,"journal":{"name":"Onco","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42093667","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
As the new Editor-in-Chief of the journal, I believe that I must continue the efforts of my predecessor even more actively and with greater enthusiasm and dedication so that the journal becomes a pole of attraction for the publication of excellent studies of basic, translational and clinical research for the treatment of cancer [...]
{"title":"Onco: A Promising Player Amidst Oncology Journals","authors":"C. Baxevanis","doi":"10.3390/onco3020009","DOIUrl":"https://doi.org/10.3390/onco3020009","url":null,"abstract":"As the new Editor-in-Chief of the journal, I believe that I must continue the efforts of my predecessor even more actively and with greater enthusiasm and dedication so that the journal becomes a pole of attraction for the publication of excellent studies of basic, translational and clinical research for the treatment of cancer [...]","PeriodicalId":74339,"journal":{"name":"Onco","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47571990","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-01Epub Date: 2023-04-10DOI: 10.3390/onco3020007
Lawrence P McKinney, Rajesh Singh, I King Jordan, Sooryanarayana Varambally, Eric B Dammer, James W Lillard
Prostate cancer (PCa) is the second most common cause of cancer death in American men. Metastatic castration-resistant prostate cancer (mCRPC) is the most lethal form of PCa and preferentially metastasizes to the bones through incompletely understood molecular mechanisms. Herein, we processed RNA sequencing data from patients with mCRPC (n = 60) and identified 14 gene clusters (modules) highly correlated with mCRPC bone metastasis. We used a novel combination of weighted gene co-expression network analysis (WGCNA) and upstream regulator and gene ontology analyses of clinically annotated transcriptomes to identify the genes. The cyan module (M14) had the strongest positive correlation (0.81, p = 4 × 10-15) with mCRPC bone metastasis. It was associated with two significant biological pathways through KEGG enrichment analysis (parathyroid hormone synthesis, secretion, and action and protein digestion and absorption). In particular, we identified 10 hub genes (ALPL, PHEX, RUNX2, ENPP1, PHOSPHO1, PTH1R, COL11A1, COL24A1, COL22A1, and COL13A1) using cytoHubba of Cytoscape. We also found high gene expression for collagen formation, degradation, absorption, cell-signaling peptides, and bone regulation processes through Gene Ontology (GO) enrichment analysis.
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