Cancer Controls Research Articles

Testicular and Haematological Cancer Induce Very High Levels of Sperm Oxidative Stress.

Cancer impairs spermatogenesis, whereas results on sperm DNA integrity are controversial and no data are available about sperm oxidative stress. In cancer patients, we detected sperm DNA fragmentation (sDF) and both viable (ROS production in viable sperm fraction/viable spermatozoa) and total (ROS production in viable sperm fraction/total spermatozoa) oxidative stress. We found that cancer (22.50 (17.00-26.75)%, n = 85) increased sDF with respect to the control groups in both normozoospermic subfertile patients (NSP) (12.75 (8.63-14.88)%, n = 52, p < 0.001) and in healthy donors (HD) (8.50 (7.00-14.00)%, n = 19, p < 0.001). The induction of viable oxidative stress (n = 96) with cancer was even higher: 36.60 (24.05-58.65)% versus 11.10 (8.63-14.90)% in NSP (p < 0.001) and 9.60 (8.00-14.03)% in HD (p < 0.001). Similar, albeit lower, differences were found for total oxidative stress. SDF sharply correlated to viable oxidative stress when we considered all subjects (cancer patients and controls) (r = 0.591, p < 0.001, n = 134), but no correlation was found when only cancer patients were studied (r = 0.200; p > 0.05, n = 63). In conclusion, cancer significantly increases sDF and sperm oxidative stress levels. Additional mechanisms to oxidative attack might be responsible for increased sDF in cancer patients. Because sperm oxidative stress might affect the outcomes of sperm cryopreservation, of cancer treatments and of sperm epigenoma, the detection of oxidative stress could be of help in managing the reproductive issues of cancer patients.

Genetic Variants Associated with Longitudinal Cognitive Performance in Older Breast Cancer Patients and Controls.

Background: There have been no published genome-wide studies of the genetics of cancer- and treatment-related cognitive decline (CRCD); the purpose of this study is to identify genetic variants associated with CRCD in older female breast cancer survivors. Methods: Analyses included white non-Hispanic women with non-metastatic breast cancer aged 60+ (N = 325) and age-, racial/ethnic group-, and education-matched controls (N = 340) with pre-systemic treatment and one-year follow-up cognitive assessment. CRCD was evaluated using longitudinal domain scores on cognitive tests of attention, processing speed, and executive function (APE), and learning and memory (LM). Linear regression models of one-year cognition included an interaction term for SNP or gene SNP enrichment*cancer case/control status, controlling for demographic variables and baseline cognition. Results: Cancer patients carrying minor alleles for two SNPs, rs76859653 (chromosome 1) in the hemicentin 1 (HMCN1) gene (p = 1.624 × 10-8), and rs78786199 (chromosome 2, p = 1.925 × 10-8) in an intergenic region had lower one-year APE scores than non-carriers and controls. Gene-level analyses showed the POC5 centriolar protein gene was enriched for SNPs associated with differences in longitudinal LM performance between patients and controls. Conclusions: The SNPs associated with cognition in survivors, but not controls, were members of the cyclic nucleotide phosphodiesterase family, that play important roles in cell signaling, cancer risk, and neurodegeneration. These findings provide preliminary evidence that novel genetic loci may contribute to susceptibility to CRCD.

No association between MTHFR gene C677T/A1298C polymorphisms, serum folate, vitamin B12, homocysteine levels, and prostate cancer in an Algerian population.

Methylenetetrahydrofolate reductase (MTHFR) is an important enzyme involved in folate and homocysteine metabolism, which are necessary for DNA methylation and nucleotide synthesis. Genetic polymorphisms that reduce MTHFR activity have been linked to several diseases, including prostate cancer. In this study, we aimed to investigate whether MTHFR polymorphisms, along with serum levels of folate, vitamin B12, and homocysteine, are associated with prostate cancer risk in the Algerian population. A total of 106 Algerian men with newly diagnosed prostate cancer and 125 healthy controls were included in this case-control study. The MTHFR C677T and A1298C polymorphisms were analyzed using PCR/RFLP and Real-Time PCR TaqMan® assays, respectively. Serum levels of folate, total homocysteine, and vitamin B12 were measured using an automatic biochemistry analyzer. We found no significant differences in the genotype frequency of A1298C and C677T between prostate cancer patients and controls. Moreover, serum levels of folate, total homocysteine, and vitamin B12 were not significantly associated with prostate cancer risk (p > 0.05). However, age and family history were identified as significant risk factors (OR = 1.178, p = 0.00 and OR = 10.03, p = 0.007, respectively). Our study suggests that MTHFR C677T and A1298C, as well as serum levels of folate, total homocysteine, and vitamin B12, are not associated with prostate cancer risk in the Algerian population. However, age and family history are significant risk factors. Further studies with a larger sample size are required to confirm these findings.

MicroRNA Dysregulation in Early Breast Cancer Diagnosis: A Systematic Review and Meta-Analysis.

Breast cancer continues to be the leading cause of death in women worldwide. Mammography, which is the current gold standard technique used to diagnose it, presents strong limitations in early ages where breast cancer is much more aggressive and fatal. MiRNAs present in numerous body fluids might represent a new line of research in breast cancer biomarkers, especially oncomiRNAs, known to play an important role in the suppression and development of neoplasms. The aim of this systematic review and meta-analysis was to evaluate dysregulated miRNA biomarkers and their diagnostic accuracy in breast cancer. Two independent researchers reviewed the included studies according to the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. A protocol for this review was registered in PROSPERO with the registration number "CRD42021256338". Observational case-control-based studies analyzing concentrations of microRNAs which have been published within the last 10 years were selected, and the concentrations of miRNAs in women with breast cancer and healthy controls were analyzed. Random-effects meta-analyses of miR-155 were performed on the studies which provided enough data to calculate diagnostic odds ratios. We determined that 34 microRNAs were substantially dysregulated and could be considered biomarkers of breast cancer. Individually, miR-155 provided better diagnostic results than mammography on average. However, when several miRNAs are used to screen, forming a panel, sensitivity and specificity rates improve, and they can be associated with classic biomarkers such us CA-125 or CEA. Based on the results of our meta-analysis, miR-155 might be a promising diagnostic biomarker for this patient population.

Circulating Extracellular-Vesicle-Incorporated MicroRNAs as Potential Biomarkers for Ischemic Stroke in Patients With Cancer.

This study aimed to evaluate whether extracellular-vesicle-incorporated microRNAs (miRNAs) are potential biomarkers for cancer-related stroke. This cohort study compared patients with active cancer who had embolic stroke of unknown sources (cancer-stroke group) with patients with only cancer, patients with only stroke, and healthy individuals (control groups). The expression profiles of miRNAs encapsulated in plasma exosomes and microvesicles were evaluated using microarray and validated using quantitative real-time polymerase chain reaction. The XENO-QTM miRNA assay technology was used to determine the absolute copy numbers of individual miRNAs in an external validation cohort. This study recruited 220 patients, of which 45 had cancer-stroke, 76 were healthy controls, 39 were cancer controls, and 60 were stroke controls. Three miRNAs (miR-205-5p, miR-645, and miR-646) were specifically incorporated into microvesicles in patients with cancer-related stroke, cancer controls, and stroke controls. The area under the receiver operating characteristic curves of these three miRNAs were 0.7692-0.8510 for the differentiation of patients with cancer-stroke from cancer-controls and 0.8077-0.8846 for the differentiation of patients with cancer-stroke from stroke controls. The levels of several miRNAs were elevated in the plasma exosomes of patients with cancer, but were lower than those in plasma microvesicles. An in vivo study showed that systemic injection of miR-205-5p promoted the development of arterial thrombosis and elevation of D-dimer levels. Stroke due to cancer-related coagulopathy was associated with deregulated expression of miRNAs, particularly microvesicle-incorporated miR-205-5p, miR-645, and miR-646. Further prospective studies of extracellular-vesicle-incorporated miRNAs are required to confirm the diagnostic role of miRNAs in patients with stroke and to screen the roles of miRNAs in patients with cancer.

Assessing the Effect of Cancer Diagnosis on Beliefs about Comorbid Diabetes

ObjectivesIncreasingly, patients diagnosed with cancer also live with chronic comorbidities, and it is important to understand the impact of a new cancer diagnosis on perceptions about preexisting conditions. This study assessed the effect of cancer diagnosis on beliefs about comorbid diabetes mellitus and assessed changes in beliefs about cancer and diabetes over time. Data SourcesWe recruited 75 patients with type 2 diabetes who were newly diagnosed with early-stage breast, prostate, lung, or colorectal cancer and 104 age-, sex-, and hemoglobin A1c−matched controls. Participants completed the Brief Illness Perception Questionnaire four times over 12 months. The authors examined within-patient and between-group differences in cancer and diabetes beliefs at baseline and over time. ResultsOverall, diabetes beliefs did not differ between cancer patients and controls at baseline. Cancer patients’ beliefs about diabetes varied significantly over time; they reported less concern about cancer, less emotional effect, and greater cancer knowledge over time. Participants without cancer were significantly more likely to report that diabetes affected their life across all time points, though this effect did not persist after adjustment for sociodemographic variables. ConclusionWhile all patients’ diabetes beliefs were similar at baseline and 12 months, cancer patients’ beliefs about both illnesses fluctuated during the months following cancer diagnosis. Implications for Nursing PracticeOncology nurses can play a key role in recognizing the effects of cancer diagnosis on beliefs about comorbid conditions and fluctuations in these beliefs during treatment. Assessing and communicating patient beliefs between oncology and other practitioners could produce more effective care plans based on patients’ current outlook on their health.

TP53 (rs1042522, rs28934571) and TP21 (rs1801270, rs1059234) Polymorphisms and Risk of Breast Cancer among Rural Women of Maharashtra: Findings from a Hospital Based Case- Control Study.

Various studies all around the world depicted the relationship of polymorphisms in tumor suppressor genes with risk of various cancers, but there are unambiguous conclusions on this association. A hospital based case-control study was designed to review the association of polymorphism of tumor suppressor genes p21 and p53 with breast cancer risk in women residing in rural Maharashtra. Two single nucleotide polymorphisms (SNPs) a C>A transversion (Ser>Arg) at codon 31 of exon 2 (rs1801270), C>T transition occurring 20bp upstream from stop codon of exon 3 (rs1059234) in p21 gene and G>C (Arg>Pro) transition at codon 72 of exon 4 (rs1042522), G>T (Arg>Ser) transition at codon 249 in exon 7 (rs28934571) in p53 gene were studied. To precise the quantitative assessment, we enrolled 800 subjects sorted into 400 clinically confirmed breast cancer patients and 400 healthy women from a tertiary care hospital (Krishna Hospital and Medical Research Centre) of south-western Maharashtra. The genetic polymorphisms in p21 and p53 genes was studied by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method using blood genomic DNA isolated from breast cancer patients and controls. The level of association of polymorphisms was assessed using Odds ratio (OR) with 95% confidence interval and p-value identified using logistic regression model. After the analysis of SNPs (rs1801270, rs1059234) of p21 and (rs1042522, rs28934571) in p53 gene our analysis suggested that heterozygote Ser/Arg genotype with OR=0.66; 95% CI: 0.47- 0.91; p=0.0003 and homozygote variant Arg/Arg genotype with OR=0.23; 95% CI: 0.13- 0.40; p<0.0001of rs1801270 of p21 was negatively associated with risk of breast cancer in studied population. The findings from this study supported that rs1801270 SNP of p21 was inversely associated with breast cancer risk in the studied rural women population.

Characterization of post-vaccination SARS-CoV-2 T cell subtypes in patients with different hematologic malignancies and treatments.

To evaluate the benefits of SARS-CoV-2 vaccination in cancer patients it is relevant to understand the adaptive immune response elicited after vaccination. Patients affected by hematologic malignancies are frequently immune-compromised and show a decreased seroconversion rate compared to other cancer patients or controls. Therefore, vaccine-induced cellular immune responses in these patients might have an important protective role and need a detailed evaluation. Certain T cell subtypes (CD4, CD8, Tfh, γδT), including cell functionality as indicated by cytokine secretion (IFN, TNF) and expression of activation markers (CD69, CD154) were assessed via multi-parameter flow cytometry in hematologic malignancy patients (N=12) and healthy controls (N=12) after a second SARS-CoV-2 vaccine dose. The PBMC of post-vaccination samples were stimulated with a spike-peptide pool (S-Peptides) of SARS-CoV-2, with CD3/CD28, with a pool of peptides from the cytomegalovirus, Epstein-Barr virus and influenza A virus (CEF-Peptides) or left unstimulated. Furthermore, the concentration of spike-specific antibodies has been analyzed in patients. Our results indicate that hematologic malignancy patients developed a robust cellular immune response to SARS-CoV-2 vaccination comparable to that of healthy controls, and for certain T cell subtypes even higher. The most reactive T cells to SARS-CoV-2 spike peptides belonged to the CD4 and Tfh cell compartment, being median (IQR), 3.39 (1.41-5.92) and 2.12 (0.55-4.14) as a percentage of IFN- and TNF-producing Tfh cells in patients. In this regard, the immunomodulatory treatment of patients before the vaccination period seems important as it was strongly associated with a higher percentage of activated CD4 and Tfh cells. SARS-CoV-2- and CEF-specific T cell responses significantly correlated with each other. Compared to lymphoma patients, myeloma patients had an increased percentage of SARS-CoV-2-specific Tfh cells. T-SNE analysis revealed higher frequencies of γδT cells in patients compared to controls, especially in myeloma patients. In general, after vaccination, SARS-CoV-2-specific T cells were also detectable in patients without seroconversion. Hematologic malignancy patients are capable of developing a SARS-CoV-2-specific CD4 and Tfh cellular immune response after vaccination, and certain immunomodulatory therapies in the period before vaccination might increase the antigen-specific immune response. A proper response to recall antigens (e.g., CEF-Peptides) reflects immune cellular functionality and might be predictive for generating a newly induced antigen-specific immune response as is expected after SARS-CoV-2 vaccination.

Identification of lncRNAs involved in response to ionizing radiation in fibroblasts of long-term survivors of childhood cancer and cancer-free controls.

Long non-coding ribonucleic acids (lncRNAs) are involved in the cellular damage response following exposure to ionizing radiation as applied in radiotherapy. However, the role of lncRNAs in radiation response concerning intrinsic susceptibility to late effects of radiation exposure has not been examined in general or in long-term survivors of childhood cancer with and without potentially radiotherapy-related second primary cancers, in particular. Primary skin fibroblasts (n=52 each) of long-term childhood cancer survivors with a first primary cancer only (N1), at least one second primary neoplasm (N2+), as well as tumor-free controls (N0) from the KiKme case-control study were matched by sex, age, and additionally by year of diagnosis and entity of the first primary cancer. Fibroblasts were exposed to 0.05 and 2 Gray (Gy) X-rays. Differentially expressed lncRNAs were identified with and without interaction terms for donor group and dose. Weighted co-expression networks of lncRNA and mRNA were constructed using WGCNA. Resulting gene sets (modules) were correlated to the radiation doses and analyzed for biological function. After irradiation with 0.05Gy, few lncRNAs were differentially expressed (N0: AC004801.4; N1: PCCA-DT, AF129075.3, LINC00691, AL158206.1; N2+: LINC02315). In reaction to 2 Gy, the number of differentially expressed lncRNAs was higher (N0: 152, N1: 169, N2+: 146). After 2 Gy, AL109976.1 and AL158206.1 were prominently upregulated in all donor groups. The co-expression analysis identified two modules containing lncRNAs that were associated with 2 Gy (module1: 102 mRNAs and 4 lncRNAs: AL158206.1, AL109976.1, AC092171.5, TYMSOS, associated with p53-mediated reaction to DNA damage; module2: 390 mRNAs, 7 lncRNAs: AC004943.2, AC012073.1, AC026401.3, AC092718.4, MIR31HG, STXBP5-AS1, TMPO-AS1, associated with cell cycle regulation). For the first time, we identified the lncRNAs AL158206.1 and AL109976.1 as involved in the radiation response in primary fibroblasts by differential expression analysis. The co-expression analysis revealed a role of these lncRNAs in the DNA damage response and cell cycle regulation post-IR. These transcripts may be targets in cancer therapy against radiosensitivity, as well as provide grounds for the identification of at-risk patients for immediate adverse reactions in healthy tissues. With this work we deliver a broad basis and new leads for the examination of lncRNAs in the radiation response.

Abstract LB064: Using a genomic only approach to a radiation-age association for supplementing differentiation amongst lung diseases and cancer using PMBCs

Abstract Purpose: Ionizing radiation may serve as a reference variable to estimating biological age since it mirrors cumulative DNA damage similar to aging processes. To do this, we aim to establish a rad-age association using genomics as its foundation and clinical applicability with lung disease as an overlapping health concern. Methods: Two datasets were combined and used to empirically find the age cutoff between young and old patients: GSE42488 (Data-A1) and GSE53351 (Data-A2). With age as both a categorical and continuous variable, two other datasets that include radiation exposure are used to test the interaction between radiation and age: GSE21240 (Data-B1) and GSE23515 (Data-B2). A radiation only data was also used in conjunction to evaluate trend analysis with increasing exposure levels: GSE20173 (Data-R1). The gene lists are oriented in preranked lists for both pathway and diseases functional analysis. Finally, these genes are used to evaluate another dataset via GSE42834 (Data-D1) on the clinical relevance in differentiating lung diseases given ethnicity and sex using both pairwise t-tests and linear models including pneumonic, tuberculosis, active and non-active sarcoidosis, lung cancer, and healthy controls. Results: Using 12 well-known genes associated with aging, a threshold of 29 years old was found to be the difference between young and old patients. The two interaction tests (rad and age as continuous plus rad and age as categorical) yielded 234 unique genes such that pathway analysis flagged IL-1 signaling and PRPP biosynthesis as significant with high cell proliferation diseases and carcinomas being a common trend. From the radiation only t-tests, we see a trend of continued upregulation in gene expression as radiation levels increase in 15 of the 17 common genes. When looking at pairwise comparison of disease, ethnicity, or sex, 10 genes were statistically significant, 3 of which had a combination of pairwise significance and fold-change, while LAPTM4B (probe identifier ILMN1680196) was the only gene with significant interaction (p-value=0.004) between lung disease, ethnicity, and sex and fold change greater than two. Conclusion: The results corroborate an initial association between radiation and age given inflammation and metabolic pathways and multiple genes emphasizing mitochondrial function, oxidation, and histone modification. Being able to tie rad-age genes to lung disease supplements a geroscience approach in future work. Citation Format: Nathan A. Ruprecht, Sonalika Singhal, Kalli Schaefer, Jappreet S. Gill, Benu Bansal, Sandeep K. Singhal. Using a genomic only approach to a radiation-age association for supplementing differentiation amongst lung diseases and cancer using PMBCs [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 2 (Clinical Trials and Late-Breaking Research); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(8_Suppl):Abstract nr LB064.

Unveiling DNA damage repair-based molecular subtypes, tumor microenvironment and pharmacogenomic landscape in gastric cancer.

Objective: The current molecular classification system for gastric cancer covers genomic, molecular, and morphological characteristics. Non-etheless, classification of gastric cancer based upon DNA damage repair is still lacking. Here, we defined DNA damage repair-based subtypes across gastric cancer and identified clinicopathological, tumor microenvironment and pharmacogenomic features. Methods: Unsupervised clustering analysis was executed in the TCGA-STAD cohort based upon the transcriptional expression profiling of DNA damage repair genes. LASSO computational approach was adopted for generating a DNA damage repair-relevant gene signature. The identified subtypes or signature were externally verified in the GSE84426 or GSE84433 cohort. The transcriptional levels of immunomodulators, abundance of immune cells and somatic mutations were measured, respectively. Immunotherapeutic response, and drug sensitivity were investigated. The DNA damage repair-relevant genes were further experimentally verified. Results: Two DNA damage repair-based subtypes were identified, with the notable heterogeneity in prognostic stratification, tumor microenvironment and somatic mutations. The gene signature was generated for risk stratification and prognostic prediction, which was in relation to immunomodulators and immune cells. High-risk cases were more likely to respond to immunotherapy, with distinct pharmacogenomic landscapes between low- and high-risk groups. Higher levels of PAPPA2, MPO, MAGEA11, DEPP1, CPZ, and COLEC12 and lower level of CYTL1 were proven in gastric cancer cells versus controls. Silencing CYTL1 facilitated intracellular ROS accumulation and suppressed migration in gastric cancer cells. Conclusion: Collectively, the DNA damage repair-based classification is a suitable complement to existing molecular classification system, and the quantitative gene signature provides a robust tool in selecting specific therapeutic options.

Diagnoses in multiple types of cancer based on serum Raman spectroscopy combined with a convolutional neural network: Gastric cancer, colon cancer, rectal cancer, lung cancer

Cancer is one of the major diseases that seriously threaten human health. Timely screening is beneficial to the cure of cancer. There are some shortcomings in current diagnosis methods, so it is very important to find a low-cost, fast, and nondestructive cancer screening technology. In this study, we demonstrated that serum Raman spectroscopy combined with a convolutional neural network model can be used for the diagnosis of four types of cancer including gastric cancer, colon cancer, rectal cancer, and lung cancer. Raman spectra database containing four types of cancer and healthy controls was established and a one-dimensional convolutional neural network (1D-CNN) was constructed. The classification accuracy of the Raman spectra combined with the 1D-CNN model was 94.5%. A convolutional neural network (CNN) is regarded as a black box, and the learning mechanism of the model is not clear. Therefore, we tried to visualize the CNN features of each convolutional layer in the diagnosis of rectal cancer. Overall, Raman spectroscopy combined with the CNN model is an effective tool that can be used to distinguish different cancer from healthy controls.

Alterations of commensal microbiota are associated with pancreatic cancer.

Dysbiosis commonly occurs in pancreatic cancer, but its specific characteristics and interactions with pancreatic cancer remain obscure. The 16S rRNA sequencing method was used to analyze multisite (oral and gut) microbiota characteristics of pancreatic cancer, chronic pancreatitis, and healthy controls. Differential analysis was used to identify the pancreatic cancer-associated genera and pathways. A random forest algorithm was adopted to establish the diagnostic models for pancreatic cancer. The chronic pancreatitis group exhibited the lowest microbial diversity, while no significant difference was found between the pancreatic cancer group and healthy controls group. Diagnostic models based on the characteristics of the oral (area under the curve (AUC) 0.916, 95% confidence interval (CI) 0.832-1) or gut (AUC 0.856; 95% CI 0.74, 0.972) microbiota effectively discriminate the pancreatic cancer samples in this study, suggesting saliva as a superior sample type in terms of detection efficiency and clinical compliance. Oral pathogenic genera (Granulicatella, Peptostreptococcus, Alloprevotella, Veillonella, etc.) and gut opportunistic genera (Prevotella, Bifidobacterium, Escherichia/Shigella, Peptostreptococcus, Actinomyces, etc.), were significantly enriched in pancreatic cancer. The 16S function prediction analysis revealed that inflammation, immune suppression, and barrier damage pathways were involved in the course of pancreatic cancer. This study comprehensively described the microbiota characteristics of pancreatic cancer and suggested potential microbial markers as non-invasive tools for pancreatic cancer diagnosis.

Abstract 5434: Machine-learning-based epigenetic detection of early-stage lung cancers using the EpiCheck liquid biopsy platform

Abstract Alterations in DNA methylation are one of the earliest, most common signatures of cancer development, making them ideal biomarkers for early detection. Methylation profiling of plasma cell-free DNA (cfDNA) has significant potential to expand the use of liquid biopsies to cancer screening. The EpiCheck platform combines methylation-sensitive restriction endonuclease (MSRE) digestion with whole genome sequencing to comprehensively map genome-wide DNA methylation changes with high fidelity. In this proof-of-concept study, MSRE-NGS was used to interrogate a liquid biopsy atlas focused on early-stage lung cancers to i) identify informative NGS methylation biomarkers in plasma, and ii) develop a machine learning method to discriminate between cancer and high-risk, non-cancer controls. The EpiCheck lung cancer atlas was constructed using biospecimens from academic (UBC, Vanderbilt, Cleveland Clinic) and commercial biobanks, and from a prospective multi-center study (NCT04968548). Plasma samples were collected from 93 high-risk primary lung cancer patients (62% stage I) and 90 high-risk individuals without cancer. Extracted DNA was digested with methylation-sensitive endonucleases and sequenced at an average depth of 600x. Methylation levels of ~6 million genomic loci were rank ordered using Student's t-test. Gene set enrichment analysis (GSEA) was performed on the top ranking 1000 differentially methylated loci. A logistic regression classifier with Lasso regularization was trained on 100,000 loci, and performance was examined by mean AUC using 5-fold cross-validation. A total of 23,130 loci exhibited significant differential methylation patterns between cancers and controls (p&amp;lt;0.01, FDR corrected). Of these, 20,159 and 2,971 lung cancer loci were hypermethylated and hypomethylated, respectively. Biological characterization using GSEA identified enrichments in transcriptional regulation and developmental control. In particular, loci were enriched for Polycomb Repressive Complex regulated genes, suggesting a possible connection to abnormal epigenetic regulation via histone modification in lung cancer. Construction of a machine learning logistic regression model based on the five training folds utilized 224 loci on average, and achieved a mean cross-validation AUC of 0.93 when distinguishing plasma cancer cases vs controls. Our findings demonstrate that the MSRE-NGS EpiCheck platform identified putative biomarkers within the plasma methylome for detecting early-stage lung cancer. A machine learning model trained on methylation targets performed with high accuracy in discriminating lung cancer patients from high-risk healthy individuals. Additional studies are required for defining the strength of the approach and for validating its use in non-invasive lung cancer screening. Citation Format: Dvir Netanely, Stephen Lam, Anna McGuire, Stephen Deppen, Eric Grogan, Fabien Maldonado, Michael Gieske, Joseph Seaman, Kimberly Rieger-Christ, Satish Kalanjeri, Luis Herrera, Nichole Tanner, Garrett B. Sherwood, Orna Savin, Shacade Danan, Sarah Zaouch, Nimrod Axelrad, Revital Knirsh, Ofir Shliefer, Keren Manor, Radha Duttagupta, Aharona Shuali, Peter J. Mazzone, Gerard A. Silvestri, Catherine A. Schnabel, Danny Frumkin, Adam Wasserstrom. Machine-learning-based epigenetic detection of early-stage lung cancers using the EpiCheck liquid biopsy platform. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5434.

Abstract 5766: Prospective evaluation of cell-free DNA fragmentomes for lung cancer detection

Abstract Background: Less than 10% of eligible persons undergo annual lung cancer screening by low-dose computed tomography (LDCT). Greater uptake of LDCT is hampered in part by its cost, inaccessibility, and balance of benefit to risk. A blood-based, low-cost, widely available initial blood test could boost screening participation and improve the net benefit of screening, if it were sensitive for cancer detection and affordable. The DELFI (DNA evaluation of fragments for early interception) technology uses low-coverage, whole-genome sequencing and machine learning to identify patterns of circulating cell-free DNA (cfDNA) fragmentation indicative of cancer. We report initial results of the cfDNA analysis from DELFI-L101 (NCT04825834), a prospective, observational, national case-control study to train and test DELFI classifiers for lung cancer detection. Methods: Eligible participants were adults ≥50 years old with current or previous smoking histories of ≥20 pack-years and recent or planned thoracic CT imaging. At enrollment, medical history was recorded and blood samples were collected for DELFI analysis. A classifier for lung cancer detection was developed using repeated 10-fold cross-validation. A split study approach for the purposes of independent validation of the classifier is forthcoming. Results: The study cohort included 242 patients with lung cancer and 652 individuals without cancer. Study participants largely represented those of a lung cancer screening population, with 45% stage I/IA. Most participants were ≥65 years old with roughly equal proportions of men and women. There was broad representation across lung cancer risk factors among both cases and controls. The cross-validated area under the receiver operator characteristic curve (AUC) was 0.81 for lung cancer detection. AUCs for adenocarcinoma and squamous cell carcinoma were not significantly different, but the AUC for small cell lung cancer was significantly higher than that for adenocarcinoma (p&amp;lt;.001) and squamous cell carcinoma (p=.02). Clinically meaningful sensitivity to detect all stages of disease was achieved. Conclusions: A classifier developed using samples collected prospectively distinguished between lung cancer cases and controls with robust cross-validated performance across all stages and lung cancer subtypes. A cfDNA DELFI fragmentome test could represent an affordable, high-performing blood test that may improve lung cancer screening. Citation Format: Peter J. Mazzone, Kwok-Kin Wong, Jun-Chieh J. Tsay, Harvey I. Pass, Anil Vachani, Allison Ryan, Jacob Carey, Debbie Jakubowski, Tony Wu, Yuhua Zong, Carter Portwood, Keith Lumbard, Joseph Catallini, Nicholas C. Dracopoli, Tara Maddala, Peter B. Bach, Robert B. Scharpf, Victor E. Velculescu. Prospective evaluation of cell-free DNA fragmentomes for lung cancer detection. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5766.

Evidence of sex differences in cancer-related cardiac complications in mouse models of pancreatic and liver cancer.

Abnormal heart rate variability (HRV) is commonly observed in cancer patients who have undergone targeted therapy and/or surgery, yet the effects of cancer itself on cardiac function remain underexplored. Specifically, there is limited knowledge about sex-specific manifestations of HRV in cancer patients. Transgenic mouse models are widely used to study different types of cancer. Here, we aimed to investigate the sex-specific effects of cancer on cardiac function using transgenic mouse models of pancreatic and liver cancers. This study used male and female transgenic mice with cancer and wild-type controls. Cardiac function was assessed by recording electrocardiograms in conscious mice. RR intervals were detected to determine HRV using time and frequency domain analyses. Histological analysis with Masson's trichrome staining was performed to determine structural changes. In females, increased HRV was observed in both pancreatic and liver cancer-bearing mice. In contrast, in males, increased HRV was observed only in the liver cancer group. Male pancreatic cancer mice demonstrated autonomic balance shift showing an increase in parasympathetic to sympathetic tone. The heart rate (HR) was higher in control and liver cancer male mice groups than in females. Histological analysis did not show significant sex differences but suggested a higher degree of remodeling in liver cancer mice than in control, specifically in the right atrium and left ventricle. This study revealed sex differences in cancer's HR modulation. Specifically, female cancer mice had lower median HR and higher HRV. These findings indicate that sex must be considered when using HRV as a cancer biomarker.

Incidence of Breast Cancer among Blood Groups of Women in the Holy Governorate of Karbala

Introduction: Breast cancer is a significant problem that affects women all over the world and is a leading cause of death among these patients. ABO blood groups are stable and vary by socioeconomic, geographical, and ethnic groupings. Blood type affects susceptibility and results. Objective: Previous studies have discovered a correlation between ABO blood type and Rh system as risk factors for breast cancer. Aim: To identify the association of breast cancer prevalence between women’s blood groups and the Rh factor system in Karbala Governorate. Materials and Methods: A total of 1026 women were chosen, with 736 cases and 290 controls. The case group includes patients with breast cancer, and all of them had their cancer diagnosis confirmed by biopsy. The control group consisted of women who had never been diagnosed with cancer of breast. Results: Blood group type O (39.7%), blood group type A (26.1%), blood group type B (25.4%), and blood group type AB (8.8%) were the most common ABO blood types among cancer of breast patients. The percentages of groups of ABO blood for healthy donor control were as follows: blood group type O (40.0%), blood group type A (27.6%), blood group type B (21.7%), and AB (10.7%) with P = 0.05 or higher. There is a significant difference in the Rh factor between breast cancer patients and healthy control (P = 0.003). There were noticeable differences in age categories between patients diagnosed with breast cancer and the controls in this study (P = 0.000). Conclusion: There is no correlation between ABO blood types and breast cancer in this group of Iraqi women. There is a statistically significant difference, with a P value of 0.003, between patients diagnosed with breast cancer and healthy controls in terms of the Rh factor.

Gene expression variability in long-term survivors of childhood cancer and cancer-free controls in response to ionizing irradiation

BackgroundDifferential expression analysis is usually adjusted for variation. However, most studies that examined the expression variability (EV) have used computations affected by low expression levels and did not examine healthy tissue. This study aims to calculate and characterize an unbiased EV in primary fibroblasts of childhood cancer survivors and cancer-free controls (N0) in response to ionizing radiation.MethodsHuman skin fibroblasts of 52 donors with a first primary neoplasm in childhood (N1), 52 donors with at least one second primary neoplasm (N2 +), as well as 52 N0 were obtained from the KiKme case–control study and exposed to a high (2 Gray) and a low dose (0.05 Gray) of X-rays and sham- irradiation (0 Gray). Genes were then classified as hypo-, non-, or hyper-variable per donor group and radiation treatment, and then examined for over-represented functional signatures.ResultsWe found 22 genes with considerable EV differences between donor groups, of which 11 genes were associated with response to ionizing radiation, stress, and DNA repair. The largest number of genes exclusive to one donor group and variability classification combination were all detected in N0: hypo-variable genes after 0 Gray (n = 49), 0.05 Gray (n = 41), and 2 Gray (n = 38), as well as hyper-variable genes after any dose (n = 43). While after 2 Gray positive regulation of cell cycle was hypo-variable in N0, (regulation of) fibroblast proliferation was over-represented in hyper-variable genes of N1 and N2+. In N2+, 30 genes were uniquely classified as hyper-variable after the low dose and were associated with the ERK1/ERK2 cascade. For N1, no exclusive gene sets with functions related to the radiation response were detected in our data.ConclusionN2+ showed high degrees of variability in pathways for the cell fate decision after genotoxic insults that may lead to the transfer and multiplication of DNA-damage via proliferation, where apoptosis and removal of the damaged genome would have been appropriate. Such a deficiency could potentially lead to a higher vulnerability towards side effects of exposure to high doses of ionizing radiation, but following low-dose applications employed in diagnostics, as well.

Functionally distinct BMP1 isoforms show an opposite pattern of abundance in plasma from non-small cell lung cancer subjects and controls.

Advancements in deep plasma proteomics are enabling high-resolution measurement of plasma proteoforms, which may reveal a rich source of novel biomarkers previously concealed by aggregated protein methods. Here, we analyze 188 plasma proteomes from non-small cell lung cancer subjects (NSCLC) and controls to identify NSCLC-associated protein isoforms by examining differentially abundant peptides as a proxy for isoform-specific exon usage. We find four proteins comprised of peptides with opposite patterns of abundance between cancer and control subjects. One of these proteins, BMP1, has known isoforms that can explain this differential pattern, for which the abundance of the NSCLC-associated isoform increases with stage of NSCLC progression. The presence of cancer and control-associated isoforms suggests differential regulation of BMP1 isoforms. The identified BMP1 isoforms have known functional differences, which may reveal insights into mechanisms impacting NSCLC disease progression.

The Firmicutes/Bacteroidetes Ratio as a Risk Factor of Breast Cancer

The gut microbiome can reflect the health condition of the entire body. Firmicutes and Bacteroidetes, the major phyla of the colon, can influence diseases related to obesity which are also risk factors for breast cancer. Therefore, the Firmicutes/Bacteroidetes (F/B) ratio was analyzed in patients with breast cancer. Bacterial extracellular vesicles were extracted from the serum of patients with breast cancer and healthy controls. Phyla Firmicutes and Bacteroidetes were analyzed using microbiome sequencing. Prognostic factors for breast cancer and serological test results were analyzed for correlations with the F/B ratio. The F/B ratio was three times lower in patients with breast cancer than in healthy controls. In addition, the risk factor for breast cancer, such as fasting serum glucose, was found to be related to the F/B ratio. The F/B ratio can be used as a risk factor of breast cancer and as a clue to explain underlying mechanisms affecting the development of breast cancer.