Type Of Primary Cancer Research Articles

A radiomics model based on magnetic resonance imaging to predict cytokeratin 7/19 expression and liver fluke infection of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer. HCC with liver fluke infection could harbor unique biological behaviors. This study was aimed at investigating radiomics features of HCC with liver fluke infection and establishing a model to predict the expression of cytokeratin 7 (CK7) and cytokeratin 19 (CK19) as well as prognosis at the same time. A total of 134 HCC patients were included. Gadoxetic acid-enhanced magnetic resonance imaging (MRI) images of all patients were acquired. Radiomics features of the tumor were extracted and then data dimensionality was reduced. The radiomics model was established to predict liver fluke infection and the radiomics score (Radscore) was calculated. There were 11 features in the four-phase combined model. The efficiency of the combined model increased significantly compared to each single-phase MRI model. Radscore was an independent predictor of liver fluke infection. It was also significantly different between different expression of CK7/ CK19. Meanwhile, liver fluke infection was associated with CK7/CK19 expression. A cut-off value was set up and all patients were divided into high risk and low risk groups of CK7/CK19 positive expression. Radscore was also an independent predictor of these two biomarkers. Overall survival (OS) and recurrence free survival (RFS) of negative liver fluke infection group were significantly better than the positive group. OS and RFS of negative CK7 and CK19 expression were also better, though not significantly. Positive liver fluke infection and CK19 expression prediction groups harbored significantly worse OS and RFS, survival of positive CK7 expression prediction was unsatisfying as well. A radiomics model was established to predict liver fluke infection among HCC patients. This model could also predict CK7 and CK19 expression. OS and RFS could be foreseen by this model at the same time.

The hepatocellular carcinoma (HCC) stage carcinogenesis is associated with genomic instability features

Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer, which accounts for over 80% of liver tumors. In the study, the current objective is investigating the entire mutational background of the HCC tumors in a single study because it is challenging to explore the many genomic disparities. The study collected DNA-dependent gene sets such as epigenetic modifications, DNA repair, DNA damage response, replication stress, and other related signatures from the molecular signatures database. It investigated their expression patterns in genome-wide expression profiles of liver cancer cohorts by Z score-based pathway activation scoring. Furthermore, these gene set features were validated with a pan-cancer atlas profile. Recurrence is the primary concern in tumors that have regeneration features. Hence, these effects are also further reconfirmed at the recurrence level. Based on activation pattern results, most genomic instabilities feature gene sets activated in the HCC stage tumors rather than other stages. Moreover, these genomic instabilities features are further concluded from that i) The signatures of epigenetic modifications, loss of DNA repair activity, dysregulation of DNA damage response, and replication stress are highly elevated in the HCC stage because of mutation and carcinogenic effects, ii) In addition, hyper DNA helicase activity, transcriptional dysregulation, telomere maintenance, and cell division-related gene sets are also highly enhanced due to proliferation and survival properties of the HCC tumors, and iii) This gene sets an activated in genomic instability comprising subtypes (chromosomal instability and microsatellite instability) of pan-cancer tumor cohort, and these results also reconfirm that these gene sets have genomic instability features. This instability and its dysregulation also have similar impacts at the level of recurrence HCC tumor carcinogenesis. Thus, the potential relevance of molecular signatures identified in terms of outcome prediction and research study in this direction would probably produce significant biological information that may aid in classifying the patients more accurately and providing suggestions for appropriate therapy.

Miliary cerebral metastases: prevalence and radiological findings

Aims: Miliary cerebral metastases, also known as carcinomatosis encephalitis, represent an unusual form of metastatic disease in the brain. Due to their rarity, limited literature is available, restricting our understanding of this condition. This study aimed to evaluate the prevalence and imaging characteristics of miliary cerebral metastases in a cohort of metastatic patients.
 Methods: A retrospective review was conducted on approximately 618 contrast-enhanced MRI scans from patients with metastatic disease who had not undergone surgical intervention or received radiotherapy. Cases of miliary cerebral metastases were identified and analyzed. Demographic data, primary cancer types, non-contrast CT and MRI findings of miliary metastasis cases were evaluated.
 Results: Miliary cerebral metastases were identified in 6 out of the 618 metastatic patients included in the study. The radiological features included small, disseminated hyperintense lesions visible on post-contrast T1-weighted images. These lesions were diffusely scattered throughout the brain, predominantly at the grey-white matter junction.
 Conclusion: Our findings highlight the rarity of miliary cerebral metastases, supporting the limited cases reported in the literature. These findings underscore the need for increased clinical awareness and further research into this condition. High-resolution, contrast-enhanced MRI plays a vital role in detecting and characterizing miliary cerebral metastases, aiding in their management.

B-364 Inhibition of Hypoxia-Inducible Factor-1a (HIF-1 a) Provides a Therapeutic Approach for Hepatocellular Carcinoma (HCC)

Abstract Background The most frequent type of primary liver cancer in adults is hepatocellular carcinoma (HCC) which is the third-highest cause of cancer-related death worldwide. Globally, people die from liver cancer each year, with HCC accounting for around 90% of those deaths, making it a serious public health concern. Cirrhosis, hepatitis B, hepatitis C, and non-alcoholic fatty liver disease are all high-risk factors for HCC development. In addition, HCC is one of the most frequent solid tumors found in humans. Due to insufficient blood supply, these solid tumors usually are devoid of oxygen and nutrients. A reduction in oxygen concentration results in the formation of a hypoxic environment that downregulates the metabolic process and is fatal to cancer cells. To circumvent this barrier to growth, cancer cells produce hypoxia-inducible factor-1 (HIF-1), which alters their metabolic pathways and allows them to survive. HIF-1alpha (HIF-1α), a cytoplasmic subunit of HIF-1 can be overexpressed in hypoxic conditions. HCC cells cannot proliferate under hypoxia without a high level of HIF-1α expression, making it as a potential cancer treatment target. Using the LOPAC (Library of Pharmacologically Active Compounds) drug library, we have identified multiple drug molecules that inhibit the expression of HIF-1α. Methods We constructed specific SK-HEP-1 cells, a human liver cancer cell line, expressing the luciferase reporter gene under the promoter of HIF-1α. By using the cells, we screened the (LOPAC) library. Other bioanalytical methods were used to confirm and analyze identified candidates. Results We successfully identified several compounds that are able to inhibit HIF-1α expression by using luciferase activity assays and Western blot analysis (WB). Further investigation was conducted to determine the molecular mechanism and function for one of the drug candidates, termed as UZ-1, in inhibiting HIF-1α in HCC by using the MTT assay and WB. UZ-1, an antirheumatic agent, showed a strong inhibitory effect on the expression of HIF-1α in SK-HEP-1 cells. In addition, it suppressed the signaling pathways associated with HIF-1α, leading to the apoptosis of HCC cells. Conclusion The UZ-1 molecule inhibits HIF-1α expression, as a result, and displays anticancer function in HCC cells through inducing apoptosis. Our result suggests that UZ-1 may be a potential drug candidate for the treatment of HCC.

Prognostic model of hepatocellular carcinoma based on cancer grade.

Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer. With highly invasive biological characteristics and a lack of obvious clinical manifestations, HCC usually has a poor prognosis and ranks fourth in cancer mortality. The aetiology and exact molecular mechanism of primary HCC are still unclear. To select the characteristic genes that are significantly associated with the prognosis of HCC patients and construct a prognosis model of this malignancy. By comparing the gene expression levels of patients with different cancer grades of HCC, we screened out differentially expressed genes associated with tumour grade. By protein-protein interaction (PPI) network analysis, we obtained the top 2 PPI networks and hub genes from these differentially expressed genes. By using least absolute shrinkage and selection operator Cox regression, 13 prognostic genes were selected for feature extraction, and a prognostic risk model of HCC was established. The model had significant prognostic ability in HCC. We also analysed the biological functions of these prognostic genes. By comparing the gene profiles of patients with different stages of HCC, We have constructed a prognosis model consisting of 13 genes that have important prognostic value. This model has good application value and can be explained clinically.

Circulating Tumor Cells as a Promising Tool for Early Detection of Hepatocellular Carcinoma.

Liver cancer is a significant contributor to the cancer burden, and its incidence rates have recently increased in almost all countries. Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer and is the second leading cause of cancer-related deaths worldwide. Because of the late diagnosis and lack of efficient therapeutic modality for advanced stages of HCC, the death rate continues to increase by ~2-3% per year. Circulating tumor cells (CTCs) are promising tools for early diagnosis, precise prognosis, and follow-up of therapeutic responses. They can be considered to be an innovative biomarker for the early detection of tumors and targeted molecular therapy. In this review, we briefly discuss the novel materials and technologies applied for the practical isolation and detection of CTCs in HCC. Also, the clinical value of CTC detection in HCC is highlighted.

Utility of a microRNA panel in diagnosis and prognosis of hepatitis C-associated hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer and the leading cause of cancer mortality. Various studies have linked dysregulated microRNA expression to liver cancers, but those related to viral hepatitis-related HCC are limited. We investigated the diagnostic and prognostic roles of circulating miR-331-3p, miR-23b-3p, and miR-3194-5p in EDTA-treated blood samples of 50 hepatitis C virus (HCV) HCC patients, 50 HCV cirrhotic patients, and 50 healthy controls using quantitative real-time polymerase chain reaction. We found that miR-23b-3p and miR-3194-5p were significantly downregulated, whereas miR-331-3p was upregulated in HCC patients compared with controls. Also, these miRNAs were significantly dysregulated in HCC compared with cirrhotic patients. For the diagnosis of HCC, miR-331-3p and the combined miRNAs panel had the highest area under the curve (AUC), followed by miR-3194-5p. The highest AUC for differentiating metastatic from nonmetastatic patients was shown by miR-331-3p and the combined miRNAs panel, followed by miR-23b-3p. Dysregulation of miRNAs was associated with poor clinicopathological manifestations. Finally, miR-331-3P was found to be an independent risk factor for metastatic lesions in HCC. Overall, the assessed miR-331-3p, miR-23b-3p, and miR-3194-5p were significantly associated with poor clinicopathological features of HCC and could be used to discriminate HCV-related HCC patients from cirrhosis and differentiating metastatic from nonmetastatic patients, primarily miR-331-3p along with combined miRNAs. Moreover, miR-331-3p was found to be an independent factor for metastatic lesions.

Spontaneous Regression of a Poorly Differentiated Hepatocellular Carcinoma: A Case Report

Hepatocellular carcinoma (HCC) is the most common histological type of primary liver cancer, and spontaneous regression of HCC is rare. We report the case of a 76-year-old male diagnosed with poorly differentiated HCC that spontaneously regressed. Although the patient did not undergo any treatment or invasive diagnostic tests, such as angiography, before surgery, the resected tumor showed complete necrosis similar to that seen after transcatheter arterial embolization. The main cause of the necrosis in the present case was thought to be the occlusion of nutrient vessels and tumor hypoxia. Tumor hypoxia and immunological reactions are reported to be the main causes of spontaneous HCC regression, although the underlying mechanisms remain unclear. In this case report, we provide additional insights into this phenomenon.

The disproportionate burden of Alzheimer's disease and related dementias (ADRD) in diverse older adults diagnosed with cancer

IntroductionOlder adults living with Alzheimer's disease and related dementias (ADRD) who are then diagnosed with cancer are an understudied population. While the role of cognitive impairment during and after cancer treatment have been well-studied, less is understood about patients who are living with ADRD and then develop cancer. The purpose of this study is to contribute evidence about our understanding of this vulnerable population. Materials and MethodsThis was a retrospective cohort study of a linked, representative family of databases of cancer registries and Medicare administrative claims that make up the SEER-Medicare database. Older adults ages 68 and older with a first primary cancer type: breast, cervical, colorectal, lung, oral, or prostate were eligible for inclusion (N = 337,932). Prevalence estimates of ADRD across cancer types and a 5% non-cancer comparison sample were compared by patient factors. ResultsThe overall prevalence of patients who had an ADRD diagnosis anytime in the three years prior to their cancer diagnosis was 5.6%. Patients with ADRD were more likely to be female, older (over age 75), a racial/ethnic minority, single, with multiple chronic conditions, and a tumor diagnosed early (stage I) or were unstaged. Black patients with colorectal and oral cancer had the highest and second highest prevalence of ADRD compared to White patients (13.46% vs 7.95% and 12.64% vs 7.82% respectively, p < .0001). We observed the highest prevalence of ADRD among Black patients for breast (11.85%), cervical (11.98%), lung (8.41%), prostate (4.83), and the 5% sample (9.50%, p > .0001). DiscussionThe higher prevalence of ADRD among Black and Latine older adults with cancer not only aligns with the trend observed in our non-cancer comparison sample, but also, these findings demonstrate the compounded risk experienced by minoritized older adults over the life course. The greater than expected prevalence of patients with ADRD who go on to develop cancer demonstrates better assessment of cognition is urgently needed. Accurate identification of these vulnerable populations is critical to improve assessment, care coordination, and address inequities in screening and treatment planning.

PTEN regulates expression of its pseudogene in glioblastoma cells in DNA methylation-dependent manner

Glioblastoma (GBM) is the most aggressive and frequent type of primary brain cancer in adult patients. One of the key molecular features associated with GBM pathogenesis is the dysfunction of PTEN oncosuppressor. In addition to PTEN gene, humans and several primates possess processed PTEN pseudogene (PTENP1) that gives rise to long non-coding RNA lncPTENP1-S. Regulation and functions of PTEN and PTENP1 are highly interconnected, however, the exact molecular mechanism of how these two genes affect each other remains unclear. Here, we analyzed the methylation level of the CpG islands (CpGIs) in the promoter regions of PTEN and PTENP1 in patient-derived GBM neurospheres. We found that increased PTEN methylation corelates with decreased PTEN mRNA level. Unexpectedly, we showed the opposite trend for PTENP1. Using targeted methylation and demethylation of PTENP1 CpGI, we demonstrated that DNA methylation increases lncPTENP1-S expression in the presence of wild type PTEN protein but decreases lncPTENP1-S expression if PTEN protein is absent. Further experiments revealed that PTEN protein binds to PTENP1 promoter region and inhibits lncPTENP1-S expression if its CpGI is demethylated. Interestingly, we did not detect any effect of lncPTENP1-S on the level of PTEN mRNA, indicating that in GBM cells PTENP1 is a downstream target of PTEN rather than its upstream regulator. Finally, we studied the functions of lncPTENP1-S and demonstrated that it plays a pro-oncogenic role in GBM cells by upregulating the expression of cancer stem cell markers and decreasing cell adhesion.

Association of first primary cancer with risk of subsequent primary cancer among survivors of adult-onset cancers in Kentucky and Appalachian Kentucky.

Appalachia is a region with significant cancer disparities in incidence and mortality compared to Kentucky and the United States. However, the contribution of these cancer health disparities to subsequent primary cancers (SPCs) among survivors of adult-onset cancers is limited. This study aimed to quantify the overall and cancer type-specific risks of SPCs among adult-onset cancer survivors by first primary cancer (FPC) types, residence and sex. This retrospective cohort study from the Kentucky Cancer Registry included 148,509 individuals aged 20-84 years diagnosed with FPCs from 2000-2014 (followed until December 31, 2019) and survived at least 5 years. Expected numbers of SPC were derived from incidence rates in the Kentucky population; standardized incidence ratio (SIR) compared with those expected in the general Kentucky population. Among 148,509 survivors (50.2% women, 27.9% Appalachian), 17,970 SPC cases occurred during 829,530 person-years of follow-up (mean, 5.6 years). Among men, the overall risk of developing any SPCs was statistically significantly higher for 20 of the 30 FPC types, as compared with risks in the general population. Among women, the overall risk of developing any SPCs was statistically significantly higher for 20 of the 31 FPC types, as compared to the general population. The highest overall SIR were estimated among oral cancer survivors (SIR, 2.14 [95% CI, 1.97-2.33] among men, and among laryngeal cancer survivors (SIR, 3.62 [95% CI, 2.93-4.42], among women. Appalachian survivors had significantly increased risk of overall SPC and different site specific SPC when compared to non-Appalachian survivors. The highest overall SIR were estimated among laryngeal cancer survivors for both Appalachian and non-Appalachian residents (SIR, 2.50: 95%CI, 2.10-2.95; SIR, 2.02: 95% CI, 1.77-2.03, respectively). Among adult-onset cancer survivors in Kentucky, several FPC types were significantly associated with greater risk of developing an SPC, compared with the general population. Risk for Appalachian survivors was even higher when compared to non-Appalachian residents, but was not explained by higher risk of smoking related cancers. Cancers associated with smoking comprised substantial proportions of overall SPC incidence among all survivors and highlight the importance of ongoing surveillance and efforts to prevent new cancers among survivors.

Characteristics and classification of first primary cancer patients with second primary cancer: a population-based cohort study.

Cancer survivors have an increased risk of developing subsequent primary tumors. However, the characteristics of first primary cancers (FPCs) with various types of second primary cancers (SPCs) are poorly understood, which hinders screening strategies. We analyzed data from 1,893,258 patients from the Surveillance, Epidemiology, and End Results (SEER) database to characterize and classify of FPC patients with subsequent SPCs at the pan-cancer level. In total, 3% of patients had SPC, with varied incidence rates observed depending on the types of FPC. Their onset patterns of SPC and diversity of SPC varied. Based on the diversity of the high-incidence sites of SPC, we classified FPCs into two categories: FPCs that require whole-body screening and those that need screening of particular body parts. Moreover, according to the different timing of high incidence of SPCs, our system classifies FPCs into two subtypes: FPCs that require long-term monitoring for the occurrence of SPCs and those that require screening at specific time points for SPCs. Furthermore, we identified 11 anatomical sites where over half of FPC types are prone to SPC occurrence at these locations. The risk factors for SPC occurrence in different FPC types and prognostic factors were also elucidated. Overall, we characterize and classify of FPC patients with subsequent SPCs at the pan-cancer level, which can guide the development of distinct screening strategies for each FPC type.

Interpretable AI-assisted clinical decision making (CDM) for dose prescription in radiosurgery of brain metastases

PurposeAI modeling physicians’ clinical decision-making (CDM) can improve the efficiency and accuracy of clinical practice or serve as a surrogate to provide initial consultations to patients seeking secondary opinions. In this study, we developed an interpretable AI model that predicts dose fractionation for patients receiving radiation therapy for brain metastases with an interpretation of its decision-making process. Materials/Methods152 patients with brain metastases treated by radiosurgery from 2017 to 2021 were obtained. CT images and target and organ-at-risk (OAR) contours were extracted. Eight non-image clinical parameters were also extracted and digitized, including age, the number of brain metastasis, ECOG performance status, presence of symptoms, sequencing with surgery (pre- or post-operative radiation therapy), de novo vs. re-treatment, primary cancer type, and metastasis to other sites. 3D convolutional neural networks (CNN) architectures with encoding paths were built based on the CT data and clinical parameters to capture three inputs: (1) Tumor size, shape, and location; (2) The spatial relationship between tumors and OARs; (3) The clinical parameters. The models fuse the features extracted from these three inputs at the decision-making level to learn the input independently to predict dose prescription. Models with different independent paths were developed, including models combining two independent paths (IM-2), three independent paths (IM-3), and ten independent paths (IM-10) at the decision-making level. A class activation score and relative weighting were calculated for each input path during the model prediction to represent the role of each input in the decision-making process, providing an interpretation of the model prediction. The actual prescription in the record was used as ground truth for model training. The model performance was assessed by 19-fold cross-validation, with each fold consisting of randomly selected 128 training, 16 validation, and 8 testing subjects. ResultThe dose prescriptions of 152 patient cases included 48 cases with 1 × 24 Gy, 48 cases with 1 × 20–22 Gy, 32 cases with 3 × 9 Gy, and 24 cases with 5 × 6 Gy prescribed by 8 physicians. IM-2 achieved slightly superior performance than IM-3 and IM-10, with 131 (86%) patients classified correctly and 21 (14%) patients misclassified. IM-10 provided the most interpretability with a relative weighting for each input: target (34%), the relationship between target and OAR (35%), ECOG (6%), re-treatment (6%), metastasis to other sites (6%), number of brain metastases (3%), symptomatic (3%), pre/post-surgery (3%), primary cancer type (2%), age (2%), reflecting the importance of the inputs in decision making. The importance ranking of inputs interpreted from the model also matched closely with a physician’s own ranking in the decision process. ConclusionInterpretable CNN models were successfully developed to use CT images and non-image clinical parameters to predict dose prescriptions for brain metastases patients treated by radiosurgery. Models showed high prediction accuracy while providing an interpretation of the decision process, which was validated by the physician. Such interpretability makes the model more transparent, which is crucial for the future clinical adoption of the models in routine practice for CDM assistance.

SPCR-07 REDEFINING BOUNDARIES: STEREOTACTIC RADIOSURGERY FOR ENHANCED QUALITY OF LIFE AND SURVIVAL IN PATIENTS WITH 5-20 BRAIN METASTASES

Abstract INTRODUCTION Brain metastases (BMs) occur in 10-30% of adult patients with cancer. The therapeutic approach for BMs depends on several factors including lesion number, location and size, primary cancer type, and the patient’s overall health. ASCO-SNO-ASTRO guidelines conditionally recommend stereotactic radiosurgery (SRS) for 1-10 BMs. The aim of this study was to investigate the outcomes of radiotherapy in patients with 5 or more BMs using SRS. METHODS We implemented the prospective Cohort for patient-reported Outcomes, Imaging and trial inclusion in Metastatic BRAin disease (COIMBRA) to examine all patients with BM(s) who underwent radiotherapy. In this sub-study we investigated overall survival (OS) and health related quality of life (HRQoL) for 47 patients with 5 to 20 BMs. We evaluated patients’ HRQoL using the EQ5D-VAS, at baseline and at 3 monthly intervals after radiotherapy. RESULTS Median OS was 21.3 months for patients with 5-10 BMs (n=38) and 12.5 months for patients with &amp;gt;10 BMs (n=9). Questionnaires at both baseline and 6 months after radiotherapy showed stability or improvement on the EQ5D-VAS after radiotherapy in 58.1%. Additionally, independence in self-care was not limited before or after SRS. Also, the proportion of patients (66.7%) reporting no limitation on their ability to do daily activities remained stable after radiotherapy. Fewer patients reported pain or other discomfort after SRS compared to before (25% vs 40%). CONCLUSION Our findings suggest that radiotherapy may improve QoL in patients with 5-20 BMs. Furthermore, compared to the literature, we observed a prolonged OS in this prospective cohort, suggesting that SRS should be considered as the treatment option for these patients. These results highlight the need for further investigation of the role of SRS instead of Whole Brain Radiotherapy (WBRT) in the management of patients with multiple BMs.

Radiographic Evaluation of Medication-Related Osteonecrosis of the Jaw (MRONJ) With Different Primary Cancers and Medication Therapies.

Medication-related osteonecrosis of the jaw (MRONJ) is a condition that affects the jaws and is characterized by exposed bone in the oral cavity that persists for more than eight weeks despite treatment. Additional criteria include that the patient should have a current or past history of antiresorptive drugsand/or in combination with antiangiogenic drugs, absence of metastasis, and no previous radiotherapy to the affected area. The radiographic features of MRONJ in most instances do not have any specific radiographic features. This is because standard radiographs usually show no stark abnormalities in the early stages of the disease. The study aimed to evaluate if any specific radiographic patterns are associated with primary cancers and between medications. The study is an observational case series. A total of 50 cases of possible osteonecrosisfrom June 2010 to June 2013 archives of the Department of Oral and Maxillofacial Radiology were assessed. Based on the history, 12 cases that had a history of medication use that could lead to medication-related osteonecrosis of the jaw (MRONJ) were selected. Cone beam computed tomography (CBCT) scans of these 12 cases were evaluated using the CBCT reconstruction program InVivo Dental version 6 (Anatomage Inc., San Jose, CA, USA). The number of areas showing sequestration, the pattern of osteonecrosis, and the extent were assessed. Primary cancer and the type of medication were also assessed to identify if certain cancers or drugs showed any distinctive pattern of osteonecrosis. Reconstructed panoramic images and true three-dimensional (3D) multi-planar images were assessed to study the condition. An oral and maxillofacial radiology resident in training and a board-certified oral and maxillofacial radiologist assessed the images. Radiographic findings varied among the 12 cases and included generalized sclerosis, osteosclerosis with widened periodontal ligament (PDL) space, bony sequestra, and bony necrosis. However, no specific or distinctive radiographic patterns were observed in any of the cases, regardless of the type of primary cancer or medication used. It is challenging to radiographically distinguish between MRONJ cases with different primary cancer and/or medication. Future studies should include evaluating larger samples with varying primary cancers and medications and combination drug therapies. Cases in an advanced stage of MRONJ do not have distinctive features due to extensive destruction and superimposed infection;it may be valuable to evaluate patients in the early stages of MRONJ to better understand distinguishing radiographic patterns specific to certain primary cancers or medications.

Machine learning for genetics-based classification and treatment response prediction in cancer of unknown primary.

Cancer of unknown primary (CUP) is a type of cancer that cannot be traced back to its primary site and accounts for 3-5% of all cancers. Established targeted therapies are lacking for CUP, leading to generally poor outcomes. We developed OncoNPC, a machine-learning classifier trained on targeted next-generation sequencing (NGS) data from 36,445 tumors across 22 cancer types from three institutions. Oncology NGS-based primary cancer-type classifier (OncoNPC) achieved a weighted F1 score of 0.942 for high confidence predictions ([Formula: see text]) on held-out tumor samples, which made up 65.2% of all the held-out samples. When applied to 971 CUP tumors collected at the Dana-Farber Cancer Institute, OncoNPC predicted primary cancer types with high confidence in 41.2% of the tumors. OncoNPC also identified CUP subgroups with significantly higher polygenic germline risk for the predicted cancer types and with significantly different survival outcomes. Notably, patients with CUP who received first palliative intent treatments concordant with their OncoNPC-predicted cancers had significantly better outcomes (hazard ratio (HR) = 0.348; 95% confidence interval (CI) = 0.210-0.570; P = [Formula: see text]). Furthermore, OncoNPC enabled a 2.2-fold increase in patients with CUP who could have received genomically guided therapies. OncoNPC thus provides evidence of distinct CUP subgroups and offers the potential for clinical decision support for managing patients with CUP.

NAFLD-Related HCC: Focus on the Latest Relevant Preclinical Models.

Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer and one of the deadliest cancers worldwide. Despite extensive research, the biological mechanisms underlying HCC's development and progression remain only partially understood. Chronic overeating and/or sedentary-lifestyle-associated obesity, which promote Non-Alcoholic Fatty Liver Disease (NAFLD), have recently emerged as worrying risk factors for HCC. NAFLD is characterized by excessive hepatocellular lipid accumulation (steatosis) and affects one quarter of the world's population. Steatosis progresses in the more severe inflammatory form, Non-Alcoholic Steatohepatitis (NASH), potentially leading to HCC. The incidence of NASH is expected to increase by up to 56% over the next 10 years. Better diagnoses and the establishment of effective treatments for NAFLD and HCC will require improvements in our understanding of the fundamental mechanisms of the disease's development. This review describes the pathogenesis of NAFLD and the mechanisms underlying the transition from NAFL/NASH to HCC. We also discuss a selection of appropriate preclinical models of NAFLD for research, from cellular models such as liver-on-a-chip models to in vivo models, focusing particularly on mouse models of dietary NAFLD-HCC.

Circulating RNA ZFR promotes hepatocellular carcinoma cell proliferation and epithelial-mesenchymal transition process through miR-624–3p/WEE1 axis

BackgroundHepatocellular carcinoma (HCC), the most common type of primary liver cancer, is the fourth leading cause of cancer-related deaths worldwide. Previous evidence shows that the expression of circulating RNA ZFR (circZFR) is upregulated in HCC tissues. However, the molecular mechanism of circZFR in HCC is unclear. MethodsQuantitative reverse transcriptase polymerase chain reaction (qRT-PCR) was employed to detect the expression of circZFR, microRNA-624–3p (miR-624–3p) and WEE1 in HCC tissues and cells. RNase R assay and actinomycin D treatment assay were used to analyze the characteristics of circZFR. For functional analysis, the capacities of colony formation, cell proliferation, cell apoptosis, migration and invasion were assessed by colony formation assay, 5-ethynyl-2′-deoxyuridine (EdU) assay, flow cytometry assay and transwell assay. Western blot was used to examine the protein levels of WEE1 and epithelial-mesenchymal transition (EMT)-related proteins. The interactions between miR-624–3p and circZFR or WEE1 were validated by dual-luciferase reporter assay and RNA immunoprecipitation (RIP) assay. Xenograft models were established to determine the role of circZFR in vivo. ResultscircZFR and WEE1 were upregulated, while miR-624–3p expression was reduced in HCC tissues and cells. circZFR could sponge miR-624–3p, and WEE1 was a downstream gene of miR-624–3p. Knockdown of circZFR significantly reduced the malignant behaviors of HCC and that co-transfection with miR-624–3p inhibitor restored this change. Overexpression of WEE1 abolished the inhibitory effect of miR-624–3p mimic on HCC cells. Mechanistically, circZFR acted as a competitive endogenous RNA (ceRNA) to regulate WEE1 expression by targeting miR-624–3p. Furthermore, in vivo studies have illustrated that circZFR knockdown inhibited tumor growth. ConclusionscircZFR knockdown reduced HCC cell proliferation, migration and invasion and promoted apoptosis by regulating the miR-624–3p/WEE1 axis, suggesting that the circZFR/miR-624–3p/WEE1 axis might be a potential target for HCC treatment.

Association between serum alpha-fetoproteinlevel and liver function parameters in hepatocellular carcinoma patients: A case-control study

: Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer occurs in people with liver diseases like chronic hepatitis B and hepatitis C virus. Early diagnosis and monitoring of HCC is possible with the help of tumor marker AFP. The aim of the study was to assess whether AFP level is associated with selected liver function tests in hepatocellular carcinoma patients.: Total 90 individuals are selected, 50 HCC patients with AFP &amp;#62;20ng/ml and 40 subjects (normal LFT and AFP value &amp;#60;10ng/ml) with an age between 40-70. Serum is used for analysis of AFP, SGOT, SGPT, ALP by Maglumi 1000 and Siemen biochemistry analyzer (using principle Chemiluminescence immunoassay) respectively. Unpaired T test (IBM SPSS 22.0) were used. Elevated levels of AFP (p value &amp;#60;0.05), SGOT (p value &amp;#60; 0.001), SGPT (p value &amp;#60; 0.001), ALP (p value &amp;#60; 0.001) shows statistical significance within study population and also indicated the risk of developing HCC with respect to AFP level in liver disease patients with elevated LFT parameters.: From the study, it is concluded that LFT and AFP are comparatively elevated in HCC. Treatment is usually not possible with advanced HCC due to failure of not doing proper screening at appropriate time. Early diagnosis and monitoring of HCC are possible with the help of tumor marker AFP.

Postoperative survival after lumbar instrumented surgery for metastatic spinal tumors: a nationwide population-based cohort analysis.

It is difficult to predict the expected survival after lumbar instrumented surgery for metastases owing to the difference among different cancer origins and the relatively short survival after surgery. The aim of this study is to analyze the postoperative survival period of lumbar spinal metastasis patients who underwent lumbar instrumented surgery. Data were collected from the Korean National Health Insurance Review and Assessment Service database. Patients who underwent lumbar spinal surgery with instrumentation between January 2011 and December 2015 for metastatic lumbar diseases were reviewed. The mean postoperative survival period of patients with metastatic lumbar cancer according to each primary cancer type was evaluated. A total of 628 patients were enrolled and categorized according to primary cancer type. The overall median survival rate was 1.11±1.30 years. The three most prevalent primary cancer groups were lung, hepatobiliary, and colorectal cancers, presenting relatively short postoperative survival rates (0.93±1.25, 0.74±0.75 and 0.74±0.88 years, respectively). The best postoperative survival period was observed in breast cancer (2.23±1.83 years), while urinary tract cancer showed the shortest postoperative survival period (0.59±0.69 years). The postoperative survival period of patients with lumbar metastatic spinal tumors according to different primary cancers after instrumented fusion was ˃1 year overall, with differences according to different primary origins. This result may provide information regarding the expected postoperative survival after instrumented surgery for lumbar spinal metastases.