Different Stages Of Cancer Research Articles

Psychological characteristics of women with breast cancer who have applied for specialized medical care late

Long intervals between detecting breast cancer and the beginning of treatment can influence the prognosis of the course of the disease and survival. This research aims to reveal the psychological characteristics of women with breast cancer who applied for specialized medical care late after detecting a mass lesion in the breast. The methods used in the study were a questionnaire, a test method, and methods of mathematical data processing. The Analysis of Variance (ANOVA) method was used as a method of mathematical statistics. The study involved 149 women aged 32 to 80 years (mean age 55 years) with breast cancer of different stages under the care of an oncologist from the time of diagnosis up to 6 months, living in Chelyabinsk city and Chelyabinsk region, Russia, who took part in the study in 2019-2021. Based on empirical research, it was found that women who delayed contacting their doctor to diagnose and initiate treatment of breast cancer had a more positive worldview, a more diverse repertoire of coping strategies, expressed motivational and cognitive components of personal helplessness, and an internal locus of control, compared to women who addressed their physician at the first signs of breast cancer.

RNA-Interference-Mediated miR-122-Based Gene Regulation in Colon Cancer, a Structural In Silico Analysis

The role of microRNA 122 (miR-122) in colorectal cancer (CRC) has not been widely investigated. In the current study, we aimed to identify the prominent gene and protein interactors of miR122 in CRC. Based on their binding affinity, these targets were chosen as candidate genes for the creation of miR122-mRNA duplexes. Following this, we examined the miRNA-mediated silencing mechanism using the gene-silencing complex protein Argonaute (AGO). Public databases, STRING, and GeneMANIA were utilized to identify major proteins and genes interacting with miR-122. DAVID, PANTHER, UniProt, FunRich, miRwalk, and KEGG were used for functional annotation, pathway enrichment, binding affinity analysis, and expression of genes in different stages of cancer. Three-dimensional duplexes of hub genes and miR-122 were created using the RNA composer, followed by molecular interaction analysis using molecular docking with the AGO protein. We analyzed, classified, and scrutinized 93 miR-122 interactors using various bioinformatic approaches. A total of 14 hub genes were categorized as major interactors of miR-122. The study confirmed the role of various experimentally documented miR-122 interactors such as MTDH (Q86UE4), AKT1 (P31749), PTPN1 (P18031), MYC (P01106), GSK3B (P49841), RHOA (P61586), and PIK3CG (P48736) and put forth several novel interactors, with AKT3 (Q9Y243), NCOR2 (Q9Y618), PIK3R2 (O00459), SMAD4 (P61586), and TGFBR1 (P36897). Double-stranded RNA duplexes of the strongest interactors were found to exhibit higher binding affinity with AGO. In conclusions, the study has explored the role of miR-122 in CRC and has identified a closely related group of genes influencing the prognosis of CRC in multiple ways. Further, these genes prove to be targets of gene silencing through RNA interference and might serve as effective therapeutic targets in understanding and treating CRC.

Identification of Key Prognosis-related microRNAs in Early- and Late- Stage Gynecological Cancers Based on TCGA Data

Background: Gynecological cancers (GCs), mainly diagnosed in the late stages of the disease, remain the leading cause of global mortality in women. microRNAs (miRNAs) have been explored as diagnostic and prognostic biomarkers of cancer. Evaluating miRNA signatures to develop prognostic models could be useful in predicting high-risk patients with GC. Specifically, the identification of miRNAs associated with different stages of cancer can be beneficial in patients diagnosed with cancer. Objective: This study aimed to identify potential miRNA signatures for constructing optimal prognostic models in three major GCs using The Cancer Genome Atlas (TCGA) database Methods: Stage-specific Differentially Expressed microRNAs (DEmiRs) were identified and validated in public and in-house expression datasets. Moreover, various bioinformatics investigations were used to identify potential DEmiRs associated with the disease. All DEmiRs were analyzed using three penalized Cox regression models: lasso, adaptive lasso, and elastic net algorithms. The combined outcomes were evaluated using Best Subset Regression (BSR). Prognostic DEmiR models were evaluated using Kaplan–Meier plots to predict risk scores in patients. The biological pathways of the potential DEmiRs were identified using functional enrichment analysis. Results: A total of 65 DEmiRs were identified in the three cancer types; among them, 17 demonstrated dysregulated expression in public datasets of cervical cancer, and the expression profiles of 9 DEmiRs were changed in CCLE-OV cells, whereas those of 10 are dysregulated in CCLE-UCEC cells. Additionally, ten miRNA expression profiles were observed to be the same as DEmiRs in three OV cancer cell lines. Approximately 30 DEmiRs were experimentally validated in particular cancers. Furthermore, 23 DEmiRs were correlated with the overall survival of the patients. The combined analysis of the three penalized Cox models and BSR analysis predicted eight potential DEmiRs. A total of five models based on five DEmiRs (hsa-mir-526b, hsa-mir-508, and hsa-mir-204 in CESC and hsa-mir-137 and hsa-mir1251 in UESC samples) successfully differentiated high-risk and low-risk patients. Functional enrichment analysis revealed that these DEmiRs play crucial roles in GCs. Conclusion: We report potential DEmiR-based prognostic models to predict the high-risk patients with GC and demonstrate the roles of miRNA signatures in the early- and late-stage of GCs.

The Role of the Hypoxia-Related Unfolded Protein Response (UPR) in the Tumor Microenvironment.

Simple SummaryThe complex signaling networks that different cancers utilize for cell survival remain poorly understood. A major problem is the complexity of the tumor microenvironments (TME). Here, we discuss the role of intermittent hypoxia as one of the inducers of the UPR in the TME and the related implications of it for both cancer progression and therapeutic approaches.Despite our understanding of the unfolded protein response (UPR) pathways, the crosstalk between the UPR and the complex signaling networks that different cancers utilize for cell survival remains to be, in most cases, a difficult research barrier. A major problem is the constant variability of different cancer types and the different stages of cancer as well as the complexity of the tumor microenvironments (TME). This complexity often leads to apparently contradictory results. Furthermore, the majority of the studies that have been conducted have utilized two-dimensional in vitro cultures of cancer cells that were exposed to continuous hypoxia, and this approach may not mimic the dynamic and cyclic conditions that are found in solid tumors. Here, we discuss the role of intermittent hypoxia, one of inducers of the UPR in the cellular component of TME, and the way in which intermittent hypoxia induces high levels of reactive oxygen species, the activation of the UPR, and the way in which cancer cells modulate the UPR to aid in their survival. Although the past decade has resulted in defining the complex, novel non-coding RNA-based regulatory networks that modulate the means by which hypoxia influences the UPR, we are now just to beginning to understand some of the connections between hypoxia, the UPR, and the TME.

Identification of Long Non-Coding RNA MIR4435-2HG as a Prognostic Biomarker in Bladder Cancer.

The abnormal expression of long non-coding RNAs(lncRNAs) is closely related to the prognosis of patients. This finding may indicate a new target for the treatment of malignant tumors. Non-muscle invasive bladder cancer (NMIBC) is the most common subtype of bladder cancer, and BCG intravesical therapy is the first-line treatment for NMIBC, but about half of NMIBC patients relapse within two years after BCG treatment. Therefore, it is necessary to screen out lncRNAs related to the prognosis and treatment of BGC-resistant patients. Here, we performed differential expression analysis of lncRNAs in the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets, and screened MIR4435-2HG as the only BCG-response-related lncRNA. Then, the prognosis value of MIR4435-2HG was validated in several publicly available cohorts, and confirmed its prognostic value in bladder cancer of different stages. In addition, we also analyzed its genetic alterations, clinical relevance, function enrichment, and association with other biomarkers. Further validation of the expression of MIR4435-2HG might be helpful to instruct NMIBC prognosis and treatment.

Escherichia coli Biomarker Types in Colorectal Cancer Patients

Colorectal cancer is the second leading cause of cancer in the globe; increasing evidence suggests that the intestinal microbiota is a key factor associated with carcinogenesis of colorectal cancer (CRC) and colonic polyps. This study was conducted on 50 adult patients of both gender. These patients were proved colorectal cancer of different stages, and they were attending gastrointestinal center in Ramadi city, Gastroenterology and Liver Disease Center at Medical City Hospital Baghdad, during the period extended from November to February 2021. Thirty-five biopsies were taken from patients with colorectal cancer diagnosed in colonoscopy, and fifteen (15) stool specimens were taken from them. Each specimen was cultivated on blood agar, MacConkey agar, at 37°C for 24 hours. Then bacterial colonies were studied grossly, their size, color, elevation, texture, and odor; dry, stained smear was stained with Gram stain. A part of the test colony was submitted to biochemical investigation using a suitable sterile medium for each test. The bacterial diagnosis was confirmed using the VITIC system. For molecular research, Escherichia coli isolates were purified and maintained frozen at -20°C in a brain heart infusion broth containing 20% glycerol. Another 50 control adult, with normal colonoscopy from both genders. A stool specimen was taken from each control individually and processed as soon as possible in the same way for the patient group. Test E. coli isolated from both patient group and control group were tested for virulence genes different Frequency of 16S ribosomal RNA (16SrRNA) gene, cytotoxic necrotizing factor (CNF) gene, cytolethal distending toxin (CDT) gene, and polyketide synthase (PKS) genes. The Tumor Necrosis Factor (TNF) was measured in sera from patients with CRC and compared to healthy individuals. The genes implicated in carcinogenesis in E. coli strains, such as 16SrRNA, CNF, and CTD, were only found in test isolates of E. coli from patients, indicating that local E. coli containing such genes could become pathogens in such persons, contributing to CRC induction.

Assessing the interrelation between oestrogen receptor status, heart rate variability and serum nitric oxide in breast cancer patients: Understanding their prognostic relevance.

e12564 Background: Heart Rate Variability (HRV) is a non-invasive procedure to assess cardiac functions and provides an index of autonomic function that intricately controls vascular tone. Studying the alteration in HRV with agents producing oxidative stress will provide useful information about disease progression. Lower HRV indicates low level of Parasympathetic Nervous System activation and dysregulation of cardiac functions. Elements of tumour microenvironment like prostaglandin E2, oestrogen and hypoxia stimulate nitric oxide (NO) production which reacts with free radicals released by tumour tissue forming oxidising agents. NO enhances oxidative stress causing vascular dysfunction. Very few studies have reported an interrelationship between NO and HRV parameters in breast cancer. The aim of the study is to verify the relation between HRV and serum NO levels in ER+ and ER- breast cancer groups. Methods: Study design: Analytical, Cross sectional. Sample Size: 135 women above 20 years of age with and without breast cancer. 69 women with histologically proven breast cancer in different stages and 66 women who were healthy age matched controls were included. Oestrogen Receptor (ER) status was obtained from clinical records. Out of 69 women with breast cancer, 31 were ER- with 15 in stage 1 and 16 in stage 2. 38 women were ER+ with 5 in stage 2 and 33 in stage 3. Serum NO was measured using colorimetry. Heart Rate Variability was measured from lead II ECG using Power Lab 15T and lab chart software. Serum NO levels and HRV parameters were compared between ER groups. Results: ER+ women had higher HRV with parasympathetic predominance compared to ER- with p<0.001. ER+ women also had higher serum NO levels compared to ER- group with p<0.001. Though no direct correlation was noticed between NO and HRV, multiple analysis of variance showed significant (p<0.001) difference of all values across the groups. irrespective of menopausal status. Conclusions: A significant difference was observed in HRV of ER+ and ER- women with breast cancer. Most ER+ women were in stage 3 with significantly higher NO levels. Serum NO is expected to be the factor most responsible for HRV changes particularly in stage 3/ER+. Parasympathetic predominance seen in ER+ women possibly is due to high NO levels.[Table: see text]

PD-L1 is overexpressed on tumorspheres cultured from circulating cancer stem cells in patients with breast cancer.

3052 Background: Circulating cancer cells, and in particular their very rare subpopulation, circulating cancer stem cells (cCSCs), are responsible for recurrence and metastasis. The exact role of cCSCs in escape of cancer from immunosurveillance is still unknown, but recent studies revealed that enhanced PDL-1 expression in cancer stem cells is linked to immune evasion and could crucially contribute to the maintenance of CSC self-renewal. Understanding the mechanisms behind this PDL-1 overexpression in cancer stem cells is critical for developing more effective anti-PD-1/PD-L1 therapy. Therefore the aim of the study was to determine the number of tumorspheres and expression of PD-L1 on tumorspheres cultured from cCSC in breast cancer patients. Methods: 110 patients with breast cancer in different stages of disease were included in this study. The determination of circulating cancer stem cells was performed using the sphere-forming assay. Additionally anti-PDL-1 antibody staining was applied to examine PDL-1 expression on breast tumorspheres. Results: We have developed an innovative in vitro platform for detection of cCSCs from peripheral blood of cancer patients. The number of tumorspheres increased significantly with tumor progression and aggressiveness of primary tumor. Patients with metastatic disease had statistically more tumorspheres as compared to patients without metastasis (30 vs 10/100µl blood, p < 0.05). Patients with multiple metastasis had more tumorspheres compared to patients with single metastases (60 vs 30/100µl blood, p < 0.05). The number of tumorspheres was positively correlated with Ki-67, Her2 status and grade score in primary breast tumors. We observed high PDL-1 expression and their considerable heterogeneity in enriched tumorspheres. Conclusions: The number of tumorspheres cultured from peripheral blood directly reflects aggressiveness and proliferation capacity of primary tumor. The presence of tumorspheres with expression of PDL-1 might suggest their immunregulatory potential. Better understanding of the interaction between cCSCs and tumor immunology may help to identify strategies to eradicate the minor subpopulation that escapes conventional therapy attack, thus providing a solution to the problem of drug resistance and metastasis.

DiaDeL: An Accurate Deep Learning-Based Model With Mutational Signatures for Predicting Metastasis Stage and Cancer Types.

Mutational signatures help identify cancer-associated genes that are being involved in tumorigenesis pathways. Hence, these pathways guide precision medicine approaches to find appropriate drugs and treatments. The pattern of mutations varies in different cancer types. Some mutations dysregulate protein function so that their accumulation is responsible for cancer development and might be associated with different cancer types. Therefore, mutations as a feature set can be used as an informative candidate to distinguish various cancer types. There are several options for demonstrating mutations. One might employ binary values to demonstrate mutation regions. Another potential method for extracting features is utilizing mutation interpreters. In this study, we investigate the trinucleotide mutational pattern of each cancer type. Moreover, we extract salient NMF-based mutational signatures across various cancer types. Then, we identify cancer-associated genes of a target cancer based on its salient signatures. We evaluate the cancer-associated genes using survival and gene expression analysis in different stages of cancer. Furthermore, we introduce DiaDeL, which is a deep learning-based binary classifier. The DiaDeL model uses mutational signatures as input features and distinct a cancer type from the others. Our proposed model outperforms six state-of-the-art methods with 0.824 and 0.88 for accuracy and AUC, respectively. The source code is available at https://github.com/sabdollahi/DiaDeL.

Adoption of Two-Dimensional Ultrasound Gastrointestinal Filling Contrast on Artificial Intelligence Algorithm in Clinical Diagnosis of Gastric Cancer.

This research was aimed to explore the value of gastrointestinal filling contrast-enhanced ultrasound (CEUS) and computed tomography (CT-)-enhanced scanning based on artificial intelligence (AI) algorithm in the evaluation of gastric cancer staging. 102 patients with gastric cancer were selected as the research objects. All of them underwent CEUS of gastrointestinal filling and 64-slice spiral CT before surgery. In addition, an improved mean shift algorithm was proposed based on differential optical flow and deep convolutional neural network (D-CNN), which was applied in image processing. The predicted positive rate (PPR), sensitivity, specificity, and accuracy of gastric cancer in different stages by CEUS and CT were calculated using pathological diagnosis results as the gold standard. 17 patients with T1 stage, 41 patients with T2-T3 stage, and 35 patients with T4 stage were detected by CEUS. 13 patients with T1 stage, 34 patients with T2-T3 stage, and 30 patients with T4 stage were detected by CT enhanced examination. The PPRs of CEUS for T1, T2-T3, and T4 stages of gastric cancer were higher than those of CT enhanced (P < 0.05). The PPR of CEUS for N0 staging of gastric cancer was higher than that of CT enhanced (P < 0.05), and it for N3 staging of gastric cancer was lower than that of CT enhanced (P < 0.05). From the analysis of M staging of gastric cancer, the PPRs of CEUS for M0 and M1 staging of gastric cancer were not statistically different from the PPRs of CT enhanced (P > 0.05). The sensitivity (95.6%), specificity (81.82%), and accuracy (94.12%) of CEUS in assessing resectability were significantly higher than those of CT enhancement (89.01%, 63.67%, and 86.27%, respectively), and the differences were statistically significant (P < 0.05). In summary, CEUS gastrointestinal filling based on the D-CNN algorithm could better improve the display rate of the tissue lesions around the stomach. It also helped to judge the lesion progress, the depth of infiltration, and lymph node metastasis of the lesion. In addition, it had excellent performance in evaluating the resectability of gastric cancer before surgery and had clinical promotion value.

MS-ResNet: disease-specific survival prediction using longitudinal CT images and clinical data.

PurposeMedical imaging data of lung cancer in different stages contain a large amount of time information related to its evolution (emergence, development, or extinction). We try to explore the evolution process of lung images in time dimension to improve the prediction of lung cancer survival by using longitudinal CT images and clinical data jointly.MethodsIn this paper, we propose an innovative multi-branch spatiotemporal residual network (MS-ResNet) for disease-specific survival (DSS) prediction by integrating the longitudinal computed tomography (CT) images at different times and clinical data. Specifically, we first extract the deep features from the multi-period CT images by an improved residual network. Then, the feature selection algorithm is used to select the most relevant feature subset from the clinical data. Finally, we integrate the deep features and feature subsets to take full advantage of the complementarity between the two types of data to generate the final prediction results.ResultsThe experimental results demonstrate that our MS-ResNet model is superior to other methods, achieving a promising 86.78% accuracy in the classification of short-survivor, med-survivor, and long-survivor.ConclusionIn computer-aided prognostic analysis of cancer, the time dimension features of the course of disease and the integration of patient clinical data and CT data can effectively improve the prediction accuracy.

Nano-Theranostics for the Sensing, Imaging and Therapy of Prostate Cancers.

We highlight hereby recent developments in the emerging field of theranostics, which encompasses the combination of therapeutics and diagnostics in a single entity aimed for an early-stage diagnosis, image-guided therapy as well as evaluation of therapeutic outcomes of relevance to prostate cancer (PCa). Prostate cancer is one of the most common malignancies in men and a frequent cause of male cancer death. As such, this overview is concerned with recent developments in imaging and sensing of relevance to prostate cancer diagnosis and therapeutic monitoring. A major advantage for the effective treatment of PCa is an early diagnosis that would provide information for an appropriate treatment. Several imaging techniques are being developed to diagnose and monitor different stages of cancer in general, and patient stratification is particularly relevant for PCa. Hybrid imaging techniques applicable for diagnosis combine complementary structural and morphological information to enhance resolution and sensitivity of imaging. The focus of this review is to sum up some of the most recent advances in the nanotechnological approaches to the sensing and treatment of prostate cancer (PCa). Targeted imaging using nanoparticles, radiotracers and biomarkers could result to a more specialised and personalised diagnosis and treatment of PCa. A myriad of reports has been published literature proposing methods to detect and treat PCa using nanoparticles but the number of techniques approved for clinical use is relatively small. Another facet of this report is on reviewing aspects of the role of functional nanoparticles in multimodality imaging therapy considering recent developments in simultaneous PET-MRI (Positron Emission Tomography-Magnetic Resonance Imaging) coupled with optical imaging in vitro and in vivo, whilst highlighting feasible case studies that hold promise for the next generation of dual modality medical imaging of PCa. It is envisaged that progress in the field of imaging and sensing domains, taken together, could benefit from the biomedical implementation of new synthetic platforms such as metal complexes and functional materials supported on organic molecular species, which can be conjugated to targeting biomolecules and encompass adaptable and versatile molecular architectures. Furthermore, we include hereby an overview of aspects of biosensing methods aimed to tackle PCa: prostate biomarkers such as Prostate Specific Antigen (PSA) have been incorporated into synthetic platforms and explored in the context of sensing and imaging applications in preclinical investigations for the early detection of PCa. Finally, some of the societal concerns around nanotechnology being used for the detection of PCa are considered and addressed together with the concerns about the toxicity of nanoparticles–these were aspects of recent lively debates that currently hamper the clinical advancements of nano-theranostics. The publications survey conducted for this review includes, to the best of our knowledge, some of the most recent relevant literature examples from the state-of-the-art. Highlighting these advances would be of interest to the biomedical research community aiming to advance the application of theranostics particularly in PCa diagnosis and treatment, but also to those interested in the development of new probes and methodologies for the simultaneous imaging and therapy monitoring employed for PCa targeting.

Unraveling the Significance of Immune Contexture in Oral Cancer

Numerous epidemiological and molecular biological studies have shown that inflammatory cells and cytokines in the tissues that surround tumors contribute to tumor development and progression. The immune response to tumors is complex, involves the interaction of several cell types of the adaptive and the innate immune systems, and has an important role in the progression of a variety of solid tumors. Tumor-infiltrating lymphocytes (TILs) have been studied as an indicator of tumor inflammation, and it has been reported that TIL subsets have their own roles in cancer progression. The differences in T-cell repertoire in different stages of cancer influence the prognostic and predictive response of the patient. Several studies have reported that CD3+ and CD8 + TILs are associated with good clinical prognosis in different cancer types including head-and-neck cancer, although contradictory reports are available regarding the role of CD4+ T-cells and + regulatory T-cells (Treg cells; forkhead box protein 3 [FOXP3] cells). This review is an attempt to elucidate the concept of immune infiltrate in oral squamous cell carcinoma to comprehend the role of immunoscore as an adjunct to tumor, node, metastasis staging to guide patient treatment. Immunoscore could provide an excellent setting for immunotherapeutic strategies to complement current standard chemoradiation and may benefit high-risk patients. We emphasize the need to standardize methodology, scoring criterias and also to develop validated cutoff values. Tumor aggressiveness and therapy resistance are influenced by the interplay between tumor cells and their microenvironment, only a better understanding of this will permit a rational design of new immunotherapeutic approaches.

Abstract P4-04-08: Determination of PD-L1 expression on tumorspheres cultured from the peripheral blood in patients with breast cancer

Abstract Background Cancer stem cells (CSCs) are the critical subpopulation of cancer cells involved in tumor formation, progression, metastasis and drug resistance. CSCs also have been considered as the main cause of cancer recurrence. The exact role of CSCs in escape of cancer from immunosurveillance is still unknown, but recent studies revealed that enhanced PDL-1 expression in cancer stem cells is linked to immune evasion and could crucially contribute to the maintenance of CSC self-renewal. Understanding the mechanisms behind this PDL-1 overexpression in cancer stem cells is critical for developing more effective anti-PD-1/PD-L1 therapy. Therefore the aim of the study was to determine the number of tumorspheres and expression of PD-L1 on tumorspheres cultured from the peripheral blood in patients with breast cancer.Methods:110 patients with breast cancer in different stages of disease were included in this study. The determination of circulating tumor cells and circulating cancer stem cells (cCSC) was performed using maintrac and tumorsphere forming assay, respectively. Additionally anti-PDL-1 antibody staining was applied to examine PDL-1 expression on breast tumorspheres.Results:We developed an innovative in vitro platform for cultivation of CSCs from peripheral blood of solid cancer patients and confirmed for the first time that tumorspheres are positive for PDL-1 in breast cancer patients. Our data also show a considerable heterogeneity in the PDL-1 expression of tumorspheres. We confirmed once again that the number of tumorspheres increased significantly with tumor progression, especially with presence of metastasis. Patients with metastatic disease had statistically more tumorspheres as compared to patients without metastasis (30 vs 10/100µl blood, p&amp;lt;0.05). Patients with multiple metastasis had more tumorspheres compared to patients with single metastases (60 vs 30/100µl blood, p&amp;lt;0.05). The number of tumorspheres was positively correlated with proliferating index Ki-67 and grade score in primary breast tumor. Moreover, patients with HER2 positive tumors had more tumorspheres compared to patients with HER2 negative primary tumors (35 vs 10/100 µl blood, p&amp;lt;0.005). Conclusion:The number of tumorspheres cultured from peripheral blood directly reflects aggressiveness and proliferation capacity of primary tumor. The presence of tumorspheres with expression of PDL-1 might suggest their immunregulatory potential, but further studies are needed to validate the impact of PDL-1 expression on tumorspheres in patients with breast cancer. Citation Format: Monika Pizon, Dorothea Schott, Ulrich Pachmann, Katharina Pachmann. Determination of PD-L1 expression on tumorspheres cultured from the peripheral blood in patients with breast cancer [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P4-04-08.

A Novel Role of Galectin-3 and Thyroglobulin in Prognosis and Differentiation of Different Stages of Thyroid Cancer and Elucidation of the Potential Contribution of Bcl-2, IL-8 and TNF-α.

Thyroid cancer is among the most prevalent cancers with different types and stages. New markers are required for the prognosis and diagnosis of the disease. The present study aimed to detect the role of new markers, including galectin-3 (Gal-3) and thyroglobulin (TG), in the prognosis and staging of thyroid cancer. The study also investigated the potential apoptotic and inflammatory mechanisms involved in thyroid cancer through the determination of B-cell lymphoma 2 (Bcl-2), interleukin-8 (IL-8) and tumor necrosis factor α (TNFα) during the different stages of the cancer using a series of molecular methods. Histopathological and immunohistochemical examinations were also performed. A total of 300 subjects were classified into: 100 normal healthy subjects matched in age and sex, 100 patients with thyroid carcinoma stage I (T1N0M0) and 100 patients with thyroid carcinoma stage 2 (T2N1M1). Interestingly, the present study revealed a significant increase in the levels of TG and Gal-3 in thyroid cancer patients compared to the control group. Furthermore, the levels of Bcl-2, IL-8 and TNF-α significantly increased in the patient serum. The histopathological examination and immunohistochemical observations confirmed the molecular and hematological findings. Collectively, the present study concluded that serum TG and Gal-3 could be useful markers in the prognosis and staging of patients with thyroid cancer. Furthermore, the determination of Bax, Bcl-2, IL-8 and TNF-α levels constitute a major important marker for investigation of the mechanisms of apoptosis and inflammation in thyroid cancer. To our knowledge, this is the first study that used both galectin-3 and TG as tumor markers in the prognosis and differentiation between the different stages of cancer.

Colorectal cancer biomarker, AABH (Aspartyl [Asparaginyl] β- hydroxylase), a companion imaging and treatment strategy.

25 Background: Colorectal cancer (CRC) is the third most common type of cancer diagnosed in the US and Canada. WHO, Canadian Cancer Society (CCS), the National Comprehensive Cancer Network (NCCN) and American Cancer Society (ACS) recommend that men and women begin CRC screening at age 50 or younger if at high risk. Recommended screening procedures: Annual occult fecal blood test (OFBT), a colonoscopy every 5 years, OFBT and colonoscopy every 5 years, or a colonoscopy every 10 years. According to The Surveillance, Epidemiology, and End Results (SEER) Program, only 39% of CRC are diagnosed in stage I, 36% are diagnosed in stage II, 19% are diagnosed with metastasis. The corresponding 5-year survival rates are 89.8%, 67.7%, and 10.3%. Neither the CCS nor the ACS recommends a blood test to be done as part of screening. This is due to the fact that, until now, there has not been a blood test with adequate sensitivity or specificity for screening. Methods: In this study we discovered that aspartyl (asparaginyl) β-Hydroxylase (AABH) measurement in serum can be used as a screening test for CRC. AABH has been detected by immunohistochemical staining (IHC) on the cell surface of different cancers including CRC. It has been detected by IHC in &gt; 97% of tumor specimens tested (n &gt; 210) but has not been found in tissue samples from normal individuals. Results: This observation and the observation that AABH is found in the serum of patients with cancer, but not in non cancer patients, led us to develop a Sandwich ELISA Assay to measure AABH in serum. In the current study we have quantified AABH levels in CRC patients and compared it with normal individual. Increased levels of AABH were found in the serum of 99% of patients with CRC in all different stages of Cancer (n = 277). In normal individuals, AABH was essentially undetectable in serum (n = 195). AABH was identified in serum from patients with CRC irrespective of cancer stage. All serum AABH levels for stages I, II, III and IV were more than 3.0 ng/mL. Conclusions: Thus, our data indicate that by measuring AABH in the serum, we should be able to detect CC at an earlier stage than it is currently detected, resulting to a much better 5-year survival for colon cancer.

TGF-β signaling and the interaction between platelets and T-cells in tumor microenvironment: Foes or friends?

T-cells, as the main immune cells in fighting against cancer cells, are usually overwhelmed by many factors. Tumor microenvironment (TME) changes are one of the factors that can limit T-cells functions. On the other hand, platelets which are known as the main source of transforming growth factor-β (TGF-β) in TME, are seemingly insignificant immune cells that can affect T-cell functions. There is a hypothesis that platelets might prevent tumor growth by stimulating cellular immunity, especially T-cells in pre-cancer status while they can inhibit T-cells and stimulate tumor growth in the advanced stage of cancer. Therefore, platelets could act as a double-edged sword in the activation of T-cells under pre-cancer and advanced stages of cancer conditions. In this review, the interaction between platelets and T cells in pre-cancer and advanced stages of cancer and the role of TGF-β signaling in different stages of cancer will be discussed.

Fractal Dimension Analysis to Detect the Progress of Cancer Using Transmission Optical Microscopy

Fractal dimension, a measure of self-similarity in a structure, is a powerful physical parameter for the characterization of structural property of many partially filled disordered materials. Biological tissues are fractal in nature and reports show a change in self-similarity associated with the progress of cancer, resulting in changes in their fractal dimensions. Here, we report that fractal dimension measurement is a potential technique for the detection of different stages of cancer using transmission optical microscopy. Transmission optical microscopy of a thin tissue sample produces intensity distribution patterns proportional to its refractive index pattern, representing its mass density distribution. We measure fractal dimension detection of different cancer stages and find its universal feature. Many deadly cancers are difficult to detect in their early to different stages due to the hard-to-reach location of the organ and/or lack of symptoms until very late stages. To study these deadly cancers, tissue microarray (TMA) samples containing different stages of cancers are analyzed for pancreatic, breast, colon, and prostate cancers. The fractal dimension method correctly differentiates cancer stages in progressive cancer, raising possibilities for a physics-based accurate diagnosis method for cancer detection.

Stage Classification of Lung Cancer using the Comparative Analysis of the Machine Learning Techniques

Stage classification today is widely used in the fields of biological sciences and engineering, The idea of the stage classification is to perform a clinical analysis of the spread of the disease . Lung cancer which is termed as Lung Carcinoma is a highly dangerous lung tumour which is defined by the uncontrolled growth of cells in the tissues of the lung. This growth of cells leading to the tumour identifies the different stages of cancer. The tumours are identified based on the probability density function. The goal is to design models for the stage classification of the of cancer patients . The description of the extent of a tumour consists of three components: T for extent of the primary tumour, N for involvement of lymph nodes, and M for distant metastases. Each T, N, and M component is divided into several categories (eg, T1, T2). This study proposes to build a classification system that can identify the stage classification using the lung cancer dataset for better accuracy. An “IQ-OTHNCCD” lung cancer dataset of 1190 images representing CT scan slices of 110 cases is used in this research.

Mitochondrial Redox Metabolism: The Epicenter of Metabolism during Cancer Progression.

Mitochondrial redox metabolism is the central component in the cellular metabolic landscape, where anabolic and catabolic pathways are reprogrammed to maintain optimum redox homeostasis. During different stages of cancer, the mitochondrial redox status plays an active role in navigating cancer cells’ progression and regulating metabolic adaptation according to the constraints of each stage. Mitochondrial reactive oxygen species (ROS) accumulation induces malignant transformation. Once vigorous cell proliferation renders the core of the solid tumor hypoxic, the mitochondrial electron transport chain mediates ROS signaling for bringing about cellular adaptation to hypoxia. Highly aggressive cells are selected in this process, which are capable of progressing through the enhanced oxidative stress encountered during different stages of metastasis for distant colonization. Mitochondrial oxidative metabolism is suppressed to lower ROS generation, and the overall cellular metabolism is reprogrammed to maintain the optimum NADPH level in the mitochondria required for redox homeostasis. After reaching the distant organ, the intrinsic metabolic limitations of that organ dictate the success of colonization and flexibility of the mitochondrial metabolism of cancer cells plays a pivotal role in their adaptation to the new environment.