scholarly journals Comprehensive pan-cancer analysis of somatic mutations in drug transporters to reveal acquired and intrinsic drug resistance in 3149 metastatic cancer patients

2019 ◽  
Vol 30 ◽  
pp. v28-v29
Author(s):  
S. Bins ◽  
W.S. van de Geer ◽  
J. van Riet ◽  
N. Steeghs ◽  
H.M.W. Verheul ◽  
...  
Keyword(s):  
Drug Resistance ◽  
Cancer Patients ◽  
Somatic Mutations ◽  
Metastatic Cancer ◽  
Drug Transporters ◽  
Intrinsic Drug Resistance ◽  
Pan Cancer

scholarly journals PRMT3 promotes tumorigenesis by methylating and stabilizing HIF1α in colorectal cancer

2021 ◽  
Vol 12 (11) ◽  
Author(s):  
Xin Zhang ◽  
Kexin Wang ◽  
Xingbo Feng ◽  
Jian Wang ◽  
Yali Chu ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Drug Resistance ◽  
Cancer Cells ◽  
Cancer Patients ◽  
Signaling Pathway ◽  
Solid Tumors ◽  
Therapeutic Strategy ◽  
Function Analysis ◽  
Metastatic Cancer ◽  
Novel Therapeutic

AbstractAbnormal angiogenesis occurs during the growth of solid tumors resulting in increased vascular permeability to fluids and metastatic cancer cells. Anti-angiogenesis therapy for solid tumors is effective in the treatment of cancer patients. However, the efficacy of anti-angiogenesis therapy is limited by drug resistance. The findings of the current study showed that HIF1α R282 is methylated by PRMT3, which is necessary for its stabilization and oncogene function. Analysis showed that PRMT3-mediated tumorigenesis is HIF1α methylation-dependent. A novel therapeutic molecule (MPG-peptide) was used to inhibit HIF1α expression. These findings provided information on PRMT3 signaling pathway and HIF1/VEGFA signaling pathway and offer a novel therapeutic strategy for colorectal cancer, mainly for treatment of anti-angiogenesis resistance patients.

A DNA-mutational panel for liquid biopsy-based pan-cancer early detection.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e13687-e13687
Author(s):  
Zhao Yi ◽  
Weizhi Chen ◽  
Ji He
Keyword(s):  
Early Detection ◽  
Cancer Patients ◽  
Liquid Biopsy ◽  
Somatic Mutations ◽  
Asian Population ◽  
Plasma Samples ◽  
Sequencing Data ◽  
Cancer Early Detection ◽  
Chinese Cancer Patients ◽  
Pan Cancer

e13687 Background: Early detection through liquid biopsy can significantly increase the successful chances of treatment. The sensitivity and specificity of early detection are limited by lower signal-to-noise ratio. Thus, well design of liquid biopsy panel is important. Methods: We adopted comprehensive data sources for designing the liquid biopsy panel, including databases of TCGA, ICGC, COSMIC, MSK Cancer Hotspots, while the panel of HCCscreen and CancerSeek. We also considered the database of somatic mutations in Chinese cancer patients generated by us (Genecast (Beijing) Biotechnology Co., Ltd.). We first calculated pan-cancer carrier ratio of somatic mutations in each database and constructed the distribution of mutation counts on step-wise increased carrier ratio. Then, we selected the set of somatic mutations with “elbow point” carrier ratio from each database as part of the panel. Finally, we integrated collected hotspots with the panel of HCCscreen and CancerSeek. Results: We selected 408, 521, 214, 146 and 330 hotspots from databases of TCGA, ICGC, COSMIC, MSK Cancer Hotspots and somatic mutations in Chinese cancer patients, respectively. After integration with the panel of HCCscreen and CancerSeek, this designed panel contains 3,334 bases distributed on 23 chromosomes and 915 gene models. Comparison of hotspots collected from different databases showed that few of them shared the same genomic location except for ones from the database of MSK Cancer Hotspots, indicating the well complementarity between them. Especially, there are 186 unique hotspots collected from the database of somatic mutations in Chinese cancer patients, which can improve the sensitivity of early detection for Chinese and Asian population. Next, we evaluated detected sensitivity of the designed panel based on sequencing data of plasma samples from more than 12,000 Chinese cancer patients collected in Genecast. The result showed that the maximum sensitivity is 66.67% for small cell lung cancer and the overall sensitivity is 45.71% for 26 cancer types, in which hotspots uniquely collected from the database of somatic mutations in Chinese cancer patients accounted for 5.11%. Conclusions: We designed a liquid biopsy panel for pan-cancer early detection and evaluated its sensitivity based on sequencing data of plasma samples from more than 12,000 Chinese cancer patients. Satisfactory performance of our designed panel shows its potential application in cancer screening for healthy and highly risky individuals.

274 High-dose medroxyprogesterone acetate (MPA) in metastatic cancer patients

1983 ◽  
Vol 19 ◽  
pp. 91
Author(s):  
P. Schmidt-Rhode ◽  
G. Sturm ◽  
K.-D. Schulz ◽  
H.J. Künzig ◽  
M. Wunsch
Keyword(s):  
Cancer Patients ◽  
Medroxyprogesterone Acetate ◽  
Metastatic Cancer ◽  
High Dose

Comparing of pan-cancer tumor immune microenvironment.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e15100-e15100
Author(s):  
Jiaan Ye ◽  
Longgang Cui ◽  
Xiaochen Zhao ◽  
Guanghui Lan
Keyword(s):  
Colorectal Cancer ◽  
T Cells ◽  
Natural Killer Cell ◽  
Natural Killer ◽  
Cancer Patients ◽  
Killer Cell ◽  
Immune Microenvironment ◽  
Hepatobiliary Cancer ◽  
Tumor Immune Microenvironment ◽  
Pan Cancer

e15100 Background: Cancer treatment has entered the era of immune checkpoint inhibitors (ICI), but different tumors have different responses to ICI drugs. For example, non-small cell lung cancer and melanoma have higher response rates to ICIs than colorectal cancer and liver cancer patients. Previous studies have shown that tumor immune microenvironment have a great impact on the efficacy of ICI. Methods: This study retrospectively included pan-cancer patient specimens, using multiple fluorescent labeling immunohistochemistry to explore the differences in the immune microenvironment of different tumors. Shapiro-Wilk was used for normality test, and ANOVA or Kruskal Wallis test was used according to the results. Two-sided P < 0.05 was considered a significant difference. Results: The study included 308 patients, including 119 (38.6%) NSCLC patients, 72 (23.4%) Colorectal cancer patients, 51 (16.6%) Hepatobiliary cancer patients and 66 (21.4%) Others types of cancer patients. Among them, there was 192 (62.3%) Male, and 116 (37.7%) Female, and the median age was 57 (50-66). The proportion of CD8+ T cells and natural killer cell in tumor was statistically different. The proportion of CD8+ T cells in NSCLC, Colorectal cancer, Hepatobiliary cancer and others was 2.16%, 1%, 1.77% and 2.63%, p < 0.01; the proportion of natural killer cell was 16.44 %, 4.91%, 5.58% and 3.29%, p < 0.01. Conclusions: Different tumor types have different immune microenvironments. These results may provide valuable clues for future ICI trail design.

Impact of cancer on emergency department outcomes.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e18618-e18618
Author(s):  
Alexander S. Qian ◽  
Edmund M. Qiao ◽  
Vinit Nalawade ◽  
Rohith S. Voora ◽  
Nikhil V. Kotha ◽  
...  
Keyword(s):  
Emergency Department ◽  
Risk Stratification ◽  
Hospital Mortality ◽  
Hospital Admission ◽  
Cancer Patients ◽  
Metastatic Cancer ◽  
Inpatient Admission ◽  
Cancer Site ◽  
Patients With Cancer ◽  
Increased Risk

e18618 Background: Cancer patients frequently utilize the Emergency Department (ED) for a variety of diagnoses, both related and unrelated to their cancer. Patients with cancer have unique risks related to their cancer and treatment which could influence ED-related outcomes. A better understanding of these risks could help improve risk-stratification for these patients and help inform future interventions. This study sought to define the increased risks cancer patients face for inpatient admission and hospital mortality among cancer patients presenting to the ED. Methods: From the National Emergency Department Sample (NEDS) we identified patients with and without a diagnosis of cancer presenting to the ED between 2016 and 2018. We used International Classification of Diseases, version 10 (ICD10-CM) codes to identify patients with cancer, and to identify patient’s presenting diagnosis. Multivariable mixed-effects logistic regression models assessed the influence of cancer diagnoses on two endpoints: hospital admission from the ED, and inpatient hospital mortality. Results: There were 340 million weighted ED visits, of which 8.3 million (2.3%) occurred in patients with a cancer diagnosis. Compared to non-cancer patients, patients with cancer had an increased risk of inpatient admission (64.7% vs. 14.8%; p < 0.0001) and hospital mortality (4.6% vs. 0.5%; p < 0.0001). Factors associated with both an increased risk of hospitalization and death included older age, male gender, lower income level, discharge quarter, and receipt of care in a teaching hospital. We identified the top 15 most common presenting diagnoses among cancer patients, and among each of these diagnoses, cancer patients had increased risks of hospitalization (odds ratio [OR] range 2.0-13.2; all p < 0.05) and death (OR range 2.1-14.4; all p < 0.05) compared to non-cancer patients with the same diagnosis. Within the cancer patient cohort, cancer site was the most robust individual predictor associated with risk of hospitalization or death, with highest risk among patients with metastatic cancer, liver and lung cancers compared to the reference group of prostate cancer patients. Conclusions: Cancer patients presenting to the ED have high risks for hospital admission and death when compared to patients without cancer. Cancer patients represent a distinct population and may benefit from cancer-specific risk stratification or focused interventions tailored to improve outcomes in the ED setting.

Disparities in pan-cancer patients undergoing germline cancer risk assessment by self-reported race/ethnicity and ancestry.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 10508-10508
Author(s):  
Ying L Liu ◽  
Anna Maio ◽  
Yelena Kemel ◽  
Erin E. Salo-Mullen ◽  
Margaret Sheehan ◽  
...  
Keyword(s):  
Cancer Risk ◽  
Cancer Patients ◽  
Cancer Genetics ◽  
Statistical Tests ◽  
Cancer Risk Assessment ◽  
Clinical Genetics ◽  
Multiple Tumor ◽  
Race Ethnicity ◽  
Pan Cancer

10508 Background: Disparities in access to germline testing for cancer patients (pts) have been demonstrated; however, disparities in post-testing care are unknown. We sought to evaluate germline findings and subsequent genetic counseling/care in cancer pts undergoing tumor-germline sequencing to explore differences by self-reported ancestry. Methods: Pan-cancer pts were prospectively consented to tumor-normal sequencing via a custom NGS panel (MSK-IMPACT) from 1/2015-12/2019 inclusive of germline analysis up to 88 genes. Germline analysis was performed as a research non-billable test in 97.5% of cases. Referral to clinical genetics service (CGS) was recommended for all pts with a new positive (likely pathogenic/pathogenic) germline variant (PV). Ancestry was defined using self-reported Federal definitions of race/ethnicity and designations of Ashkenazi Jewish (AJ) ancestry. Pts were categorized into mutually exclusive groups: AJ, White, Non-White (Asian, Black/African American, Hispanic, Other), and unknown. All pts self-identifying as Hispanic were classified as such, regardless of race. Abstracted data on germline findings and downstream CGS follow-up were compared across groups using non-parametric statistical tests. Results: Among the 15,775 pts in this cohort (59.6% White, 15.7% AJ, 20.5% Non-White [6.9% Asian, 6.8% Black, 6.7% Hispanic, 0.1% Other], and 4.2% unknown), 2663 (17%) had a PV. AJ pts had the highest rates of PV (n = 683, 27.6%), and Non-White pts had a lower proportion of PV (n = 433, 13.6%) compared to Whites (n = 1451, 15.5%), p < 0.01, with differences mostly due to increased prevalence of moderate/low penetrance variants in White and AJ pts . These findings were consistent across multiple tumor types. Prior knowledge of the PV (424/2663, 16%) was more common in Non-White (19.9%) and AJ (19.2%) than White pts (13.4%), p < 0.01. Among 2239 pts with new PV, all were referred to CGS, and 1652 (73.8%) pts were seen. Non-White pts had lower rates of completing visits (67.7%) than White (73.7%) and AJ pts (78.8%), p < 0.01, with the lowest rates occurring in Black (63%) and Hispanic (68.1%) pts. All pts without a visit (n = 587) received a close out letter including 139 pts (6.2% of pts with new PV) who had no documentation of receipt of results in the medical record. Higher rates of non-disclosure were observed in Non-White (6.7%) compared to White (5.4%) and AJ (3.4%) pts with new PV, p = 0.032; non-disclosure did not vary by gene penetrance. There was a non-significant trend towards lower rates of cascade testing at CGS in Asian and Black pts with ongoing analysis. Conclusions: Even when traditional barriers to genetic testing were minimized, Non-White pts were less likely to receive recommended cancer genetics follow-up for subsequent cancer risk counseling, with potential implications for oncological care, cancer risk reduction, and at-risk family members.

Exploration of the MSI landscape in Chinese pan-cancer patient by Next-Generation Sequencing.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e14576-e14576
Author(s):  
Xinlu Liu ◽  
Jiasheng Xu ◽  
Jian Sun ◽  
Deng Wei ◽  
Xinsheng Zhang ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Correlation Analysis ◽  
Cancer Patients ◽  
Cancer Type ◽  
Multiple Tumor ◽  
Treatment Plans ◽  
Cancer Types ◽  
Chinese Cancer Patients ◽  
Colorectal Cancer Patients ◽  
Pan Cancer

e14576 Background: Clinically, MSI had been used as an important molecular marker for the prognosis of colorectal cancer and other solid tumors and the formulation of adjuvant treatment plans, and it had been used to assist in the screening of Lynch syndrome. However, there were currently few reports on the incidence of MSI-H in Chinese pan-cancer patients. This study described the occurrence of MSI in a large multi-center pan-cancer cohort in China, and explored the correlation between MSI and patients' TMB, age, PD-L1 expression and other indicators. Methods: The study included 8361 patients with 8 cancer types from multiple tumor centers. Use immunohistochemistry to detect the expression of MMR protein (MLH1, MSH2, MSH6 and PMS2) in patients with various cancer types to determine the MSI status and detect the expression of PD-L1 in patients. Through NGS technology, 831 genes of 8361 Chinese cancer patients were sequenced and the tumor mutation load of the patients was calculated. The MSI mutations of patients in 8 cancer types were analyzed and the correlation between MSI mutations of patients and the patient's age, TMB and PD-L1 expression was analyzed. Results: The test results showed that MSI patients accounted for 1.66% of pan-cancers. Among them, MSI-H patients accounted for the highest proportion in intestinal cancer, reaching 7.2%. The correlation analysis between MSI and TMB was performed on patients of various cancer types. The results showed that: in each cancer type, MSI-H patients had TMB greater than 10, and 26.83% of MSI-H patients had TMB greater than 100 in colorectal cancer patients. The result of correlation analysis showed that there was no significant correlation between the patient's age and the risk of MSI mutation ( P> 0.05). In addition to PAAD and LUAD, the expression of PD-L1 in MSI-H patients was higher than that in MSS patients in other cancer types( P< 0.05). The correlation analysis between PD-L1 expression and TMB in patients found that in colorectal cancer, the higher the expression of PD-L1, the higher the patient's TMB ( P< 0.05). Conclusions: In this study, we explored the incidence of MSI-H in pan-cancer patients in China and found that the TMB was greater than 10 in patients with MSI-H. Compared with MSS patients, MSI-H patients have higher PD-L1 expression, and the higher the PD-L1 expression in colorectal cancer, the higher the TMB value of patients.

An ultrasensitive method for noninvasive pan-cancer early detection based on targeted methylation sequencing of cell-free DNA.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 10544-10544
Author(s):  
Tiancheng Han ◽  
Yuanyuan Hong ◽  
Pei Zhihua ◽  
Song Xiaofeng ◽  
Jianing Yu ◽  
...  
Keyword(s):  
Cancer Patients ◽  
Cancer Detection ◽  
Real World ◽  
Early Stage ◽  
Validation Dataset ◽  
Cpg Sites ◽  
Free Dna ◽  
Cancer Types ◽  
Discovery Dataset ◽  
Pan Cancer

10544 Background: Screening the biomarkers from the cell-free DNA (cfDNA) of peripheral blood is a non-invasive and promising method for cancer diagnosis. Among diverse types of biomarkers, epigenetic biomarkers have been reported to be one of the most promising ones. Epigenetic modifications are widespread on the human genome and generally have strong signals due to the similar methylation patterns shared by adjacent CpG sites. Although some epigenetic diagnostic methods have been developed based on cfDNAs, few of them could be applied to pan-cancer and their sensitivities are barely satisfactory for early cancer detection. Methods: Targeted methylation sequencing was performed using our in-house-designed panel targeting regions with abundant cancer-specific methylation CpGs. The cfDNA samples from 80 healthy individuals and 549 cancer patients of 14 cancer types were separately sequenced. The dataset was randomly split into one discovery dataset and one validation dataset. Moreover, cfDNA samples from four cancer patients were diluted with the healthy cfDNAs to generate 12 in vitro simulated samples with low circulating tumor DNA (ctDNA) fraction. Additionally, DNAs extracted from 130 unmatched tumor formalin fixation and paraffin embedding (FFPE) samples of 10 cancer types were sequenced to screen the diagnostic biomarkers. Adjacent CpG sites were first merged into methylation-correlated blocks (MCB) according to their correlations of methylation levels in tumor DNAs. The MCBs with higher methylation levels in tumor DNAs than that of healthy cfDNAs (from the discovery dataset) were defined as our hypermethylation biomarkers. For each cfDNA sample, a hypermethylation score (HM-score) was computed to measure the overall methylation level difference of selected biomarkers. The performance of our method was evaluated with the real-world dataset, while the limit of detection was estimated using the simulated low-ctDNA samples. Results: Our model based on 37 hypermethylation MCB biomarkers achieved an area under the curve (AUC) of 0.89 and 0.86 in the real-world pan-cancer discovery and validation cfDNA datasets, respectively. Furthermore, the overall specificity and sensitivity are 100% and 76.19% in the discovery dataset, and 96.67% and 72.86% in the validation dataset. In the validation dataset, 28/40 (70%) of early-stage colorectal cancer patients and 10/20 (50%) of non-small-cell lung cancer patients were successfully diagnosed. Additionally, all the simulated samples with theoretical ctDNA factions over 0.5% were predicted as diseased, demonstrating the ability of our method to detect tumor signals at early stages. Conclusions: Our cfDNA-based epigenetic method outperforms currently available methods in various cancer types, and is promising to be applied to early-stage cancer detection and samples with low ctDNA fractions.

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