Guidance on metastatic colorectal cancer, breast cancer issued in UK

2007 ◽  
Vol &NA; (1574) ◽  
pp. 4
Author(s):  
&NA;
Keyword(s):  
Breast Cancer ◽  
Colorectal Cancer ◽  
Metastatic Colorectal Cancer ◽  
Cancer Breast

scholarly journals 65 Identification of frequently presented non-mutated tumor-specific immunogens for the development of both off-the-shelf and personalized vaccines without need for tumor biopsy

2021 ◽  
Vol 9 (Suppl 3) ◽  
pp. A72-A72
Author(s):  
Orsolya Lorincz ◽  
Levente Molnar ◽  
Zsolt Csiszovszki ◽  
Eszter Somogyi ◽  
Jozsef Toth ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Colorectal Cancer ◽  
T Cells ◽  
T Cell ◽  
Metastatic Colorectal Cancer ◽  
Cancer Vaccines ◽  
T Cell Responses ◽  
Tumor Biopsy ◽  
Cell Responses ◽  
Antigen Selection

BackgroundVaccines have little chance of destroying heterogeneous tumor cells since they rarely induce polyclonal T-cell responses against the tumor. The main challenge is the accurate identification of tumor targets recognizable by T cells. Presently, 6–8% of neoepitopes selected based on the patients‘ tumor biopsies are confirmed as real T cell targets.1 2. To overcome this limitation, we developed a computational platform called Personal Antigen Selection Calculator (PASCal) that identifies frequently presented immunogenic peptide sequences built on HLA-genetics and tumor profile of thousands of real individuals.3 Here we show the performance of PASCal for the identification of both shared and personalized tumor targets in metastatic colorectal cancer (mCRC) and breast cancer subjects.MethodsExpression frequency of the tumor-specific antigens (TSAs) ranked in PASCal’s database (based on 7,548 CRC specimen) was compared to the RNA-sequencing data of CRC tumors obtained from TCGA. Using PASCal, 12 shared PEPIs (epitopes restricted to at least 3 HLA class I alleles of a subject from an in silico cohort) derived from 7 TSAs were selected as frequent targets (calculated probability: average 2.5 [95%CI 2.4–2.8] TSAs/patient). Spontaneous immune responses against each of the twelve 9mer peptides were determined by ELISpot using PBMCs of 10 mCRC subjects who participated in the OBERTO-101 study.4 PEPIs selected for a breast cancer subject based on her HLA genotype were also tested.ResultsEach of the 106 tumors analyzed expressed at least 13, average 15 of the 20 top-ranked TSAs in PASCal’s database confirming their prevalence in CRC. 7/10 subjects had spontaneous CD8+ T-cell responses against at least one peptide selected with PASCal. Each peptide (12/12) was recognized by at least one patient. Patients‘ T-cells reacted with average 3.6/12 (30%) peptides confirming the expression of average 2.8 [95%CI 1.0–4.6] TSAs (n=10). After HLA-matching, among the subjects for whom we could select at least 4 PEPIs (average 5) from the list of 12 peptides (n=6), average 2.5 (50%) peptides were positive. Of the 12 PEPIs selected with PASCal for a breast cancer subject, we detected spontaneous T-cell responses against 9 PEPIs, indicating that at least 75% of the selected peptides were present in the subject’s tumor and were recognized by T-cells.ConclusionsPASCal platform accommodates both tumor- and patient heterogeneity and identifies non-mutated tumor targets that may trigger polyclonal cytotoxic T-cell responses. It is a rapid tool for the design of both off-the-shelf and personalized cancer vaccines negating the need for tumor biopsy.ReferencesWells DK, van Buuren MM, Dang KK, et al. Key parameters of tumor epitope immunogenicity revealed through a consortium approach improve neoantigen prediction. Cell 2020:183(3):818–34.e13.Bulik-Sullivan B, Busby J, Palmer CD, et al. Deep learning using tumor HLA peptide mass spectrometry datasets improves neoantigen identification. Nat Biotech 2018:37:55–63.Somogyi E, Csiszovszki Z, Lorincz O, et al. 1181PDPersonal antigen selection calculator (PASCal) for the design of personal cancer vaccines. Annal Oncol 2019:30(Supplement_5):v480-v81.Hubbard J, Cremolini C, Graham R, et al. P329 PolyPEPI1018 off-the shelf vaccine as add-on to maintenance therapy achieved durable treatment responses in patients with microsatellite-stable metastatic colorectal cancer patients (MSS mCRC). J ImmunoTher Cancer 2019:7(1):282.

scholarly journals Function of N6-Methyladenosine Modification in Tumors

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Nan Zhang ◽  
Yuxin Zuo ◽  
Yu Peng ◽  
Lielian Zuo
Keyword(s):  
Breast Cancer ◽  
Colorectal Cancer ◽  
Gastric Cancer ◽  
Nasopharyngeal Carcinoma ◽  
Liver Cancer ◽  
Nuclear Export ◽  
Tumor Proliferation ◽  
Cancer Breast

N6-Methyladenosine (m6A) modification is a dynamic and reversible methylation modification at the N6-position of adenosine. As one of the most prevalent posttranscriptional methylation modifications of RNA, m6A modification participates in several mRNA processes, including nuclear export, splicing, translation, and degradation. Some proteins, such as METTL3, METTL14, WTAP, ALKBH5, FTO, and YTHDF1/2/3, are involved in methylation. These proteins are subdivided into writers (METTL3, METTL14, WTAP), erasers (ALKBH5, FTO), and readers (YTHDF1/2/3) according to their functions in m6A modification. Several studies have shown that abnormal m6A modification occurs in tumors, including colorectal cancer, liver cancer, breast cancer, nasopharyngeal carcinoma, and gastric cancer. The proteins for m6A modification are involved in tumor proliferation, angiogenesis, metastasis, immunity, and other processes. Herein, the roles of m6A modification in cancer are discussed, which will improve the understanding of tumorigenesis, as well as the diagnosis, treatment, and prognosis of tumors.

scholarly journals Lack of Association between Common Polymorphisms in Selenoprotein P Gene and Susceptibility to Colorectal Cancer, Breast Cancer, and Prostate Cancer: A Meta-Analysis

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Hanjiang Xu ◽  
Fan Mo ◽  
Jun Zhou ◽  
Zongyao Hao ◽  
Xianguo Chen ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Prostate Cancer ◽  
Colorectal Cancer ◽  
Cancer Susceptibility ◽  
Meta Analysis ◽  
Selenoprotein P ◽  
Tumor Type ◽  
Cancer Breast ◽  
P Gene ◽  
Breast And Prostate Cancer

Background and Objective. Selenoprotein P (SEPP1) is the major selenoprotein in plasma. Previous studies have demonstrated that SEPP1 expression was reduced in human prostate and colon tumors. Nowadays, studies concerning SEPP1 gene polymorphisms and cancer susceptibility have been extensively investigated, whereas results from these studies remain debatable rather than conclusive. Thus, we performed the present meta-analysis to comprehensively assess the association between two common polymorphisms (rs3877899 and rs7579) in SEPP1 and cancer susceptibility. Method. We search the PubMed, Embase, Google Scholar, and Wanfang (China) databases (up to December 1, 2020) to identify all eligible publications. The pooled odds ratio (OR) correspondence with 95% confidence interval (CI) was calculated to evaluate the associations. Results. Finally, nine eligible studies with 7,157 cases and 6,440 controls and five studies with 2,278 cases and 2,821 controls were enrolled in rs3877899 and rs7579 polymorphisms, individually. However, a null significant association was detected between the two polymorphisms in SEPP1 and susceptibility to colorectal, breast, and prostate cancer in all comparison models. Subsequently, subgroup analysis based on tumor type, no significant association was identified for prostate, breast, and colorectal cancer. In addition, when the stratification analyses were conducted by the source of control, HWE status, and ethnicity, yet no significant association was found. Conclusions. The current meta-analysis shows that SEPP1 rs3877899 and rs7579 polymorphisms may not be associated with susceptibility to colon cancer, breast cancer, and prostate cancer, and further well-designed studies with a larger sample size are warranted to validate our findings.

Risk-adjustment models for breast, lung, and colorectal cancer cost, utilization, and outcomes in a commercially insured population.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. e18340-e18340
Author(s):  
Bhuvana Sagar ◽  
Yu Shen Lin ◽  
Liana Desharnais Castel
Keyword(s):  
Breast Cancer ◽  
Colorectal Cancer ◽  
Hospital Admissions ◽  
Hospital Length ◽  
Hospital Length Of Stay ◽  
Her2 Positive ◽  
Cost Drivers ◽  
Cancer Breast ◽  
Clinical Biomarkers ◽  
Cost Utilization

e18340 Background: Advances in oncology have led to rising costs which are unsustainable, necessitating value-based arrangements that maximize quality and overall outcomes. Our objective was to identify clinical and patient factors that predict higher costs and utilization among breast, lung, and colorectal cancer in a commercial population. Methods: We conducted a longitudinal analysis of claims in a sample of 9,748 commercially insured patients with breast, lung, and colorectal cancer, to measure costs and utilization based on presence of metastases, proxies for clinical biomarkers, patient demographics, and treatments. Results: Episode Risk Group (ERG) risk score, metastasis, and facility provider affiliation were cost drivers for all three types of cancer (breast, lung, and colorectal). Hypertension and younger age were cost drivers for breast cancer. In addition, HER2 positive status (β = 68,946, SE = 2,104, p < .0001) was significant in breast cancer, and VEGF in both lung (β = 56,975, SE = 10,138, p < .0001) and colorectal (β = 24,400, SE = 5,671, p < .0001) cancers. Metastasis also was associated with greater hospital admissions and hospital length of stay in all three cancers. Chemotherapy and supportive drug therapies accounted for the highest proportions of total medical costs among beneficiaries observed. Conclusions: Value-based reimbursement models in oncology should appropriately risk adjust by accounting for key cost drivers. Although claims-based methodologies may be further augmented with clinical data, we recommend adjusting for the factors we identified in models to predict costs and outcomes in breast, lung, and colorectal cancers.

scholarly journals Personalized Medicine in Screening for Malignant Disease: A Review of Methods and Applications

2013 ◽  
Vol 8 ◽  
pp. BMI.S11153 ◽  
Author(s):  
F. Schmalfuss ◽  
P.L. Kolominsky-Rabas
Keyword(s):  
Breast Cancer ◽  
Prostate Cancer ◽  
Colorectal Cancer ◽  
Personalized Medicine ◽  
Literature Search ◽  
Malignant Disease ◽  
Decisive Role ◽  
Routine Clinical Practice ◽  
Cancer Breast ◽  
Potential Applications

Personalized medicine (PM) is currently a hot topic in the professional world. It is often called the medicine of the future and has already achieved resounding success in the area of targeted therapy. Nevertheless, integration of the concepts of PM into routine clinical practice is slow. This review is intended to give an overview of current and potential applications of PM in oncology. PM could soon play a decisive role, especially in screening. The relevance of PM in screening was examined in the case of four common cancers (colorectal cancer, lung cancer, breast cancer, and prostate cancer). A literature search was performed. This showed that biomarkers in particular play a crucial role in screening. In summary, it can be emphasized that there are already numerous known promising biomarkers in malignant disease. This results in several possibilities for individualizing and revolutionizing screening.

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