Breast Cancer Index and risk stratification in luminal subtypes: A trans-ATAC study.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. 534-534
Author(s):  
Ivana Sestak ◽  
Yi Zhang ◽  
Catherine A. Schnabel ◽  
Jack M. Cuzick ◽  
Mitchell Dowsett
Keyword(s):  
Breast Cancer ◽  
High Risk ◽  
Cox Regression ◽  
Early Stage ◽  
Risk Groups ◽  
Low Risk ◽  
Luminal A ◽  
Prognostic Information ◽  
Prognostic Performance ◽  
Breast Cancer Index

534 Background: The Breast Cancer Index (BCI) is a gene-expression based signature that provides prognostic information for overall (0-10 years) and late (5-10 years) distant recurrence (DR) and prediction of extended endocrine benefit in hormone receptor positive (HR+) early stage breast cancer. The current analysis aims to further characterize, correlate and compare the prognostic performance of BCI in luminal subtypes based on immunohistochemical classification. Methods: 670 postmenopausal women with HR+, LN- disease from the TransATAC cohort were included in this analysis. Luminal A-like tumors (LumA) were identified as those with ER+ and/or PR+ and HER2 -, and Ki67 < 20% by IHC. All other tumors were classified as Luminal B-like (LumB) for this analysis. Primary endpoint was DR. Cox regression models were used to examine BCI prognostic performance according to luminal subtype, adjusting for the clinicopathological model Clinical Treatment Score (CTS). Results: 452 (67.5%) patients were classified as LumA and 218 (32.5%) as LumB. BCI was highly prognostic in LumA cancers (adjusted HR = 1.57 (1.23-1.96), P < 0.001, ΔLR-χ2= 14.09), but not in LumB tumors (adjusted HR = 1.20 (0.94-1.52, P = 0.14, ΔLR-χ2= 2.23). In LumA, 10-year DR risks in BCI intermediate and high risk groups were very similar (25.6% (16.4-38.6) and 25.3% (13.5-44.3), respectively) and significantly different from BCI low (3.9% (2.1-7.0); HR = 7.47 (3.50-15.96) and HR = 8.13 (3.27-20.23), respectively). In LumB, 10-year DR risks in BCI low and BCI intermediate risk groups (13.8% (6.8-26.9) and 14.6% (8.3-24.9), respectively) were very similar and significantly lower than for the BCI high (29.1% (20.0-41.1)). Lum subtyping was only prognostic in the BCI low risk group (LumA vs. LumB: HR = 4.27 (1.65-11.02)) but not in the other two BCI risk groups. Conclusions: BCI provided significant prognostic information in Lum A subtype. These results show that BCI intermediate and high risk had similar risk of DR in LumA tumors, while shared similarly low risk of DR as BCI-low in LumB tumors. Further evaluation is needed to elucidate the distinct mechanisms underlying each classification system.

Utility of the Breast Cancer Index (BCI) in the clinical practice.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. e14723-e14723
Author(s):  
Saranya Kodali ◽  
Eswar Tipirneni ◽  
Kim Dittus
Keyword(s):  
Breast Cancer ◽  
Side Effects ◽  
High Risk ◽  
Endocrine Therapy ◽  
Early Stage ◽  
Late Recurrence ◽  
Low Risk ◽  
Breast Cancer Index ◽  
Pathologic Features ◽  
Poor Tolerance

e14723 Background: Extended endocrine therapy (EET) greater than 5 years in early stage hormone receptor positive (HR+) breast cancer (BC) patients has shown benefit. However, EET is associated with side effects and there is no validated assay to determine which group of patients would derive benefit. Breast Cancer Index (BCI) is a validated bio-marker test that incorporates 2 distinct genomic assays and is prognostic/predictive. The objective of this study is to assess patient characteristics, pathologic features and patient preferences with regards to extending endocrine therapy after reviewing the BCI results. Methods: We performed a retrospective chart review on early stage HR+ BC patients from Jan, 2016 to Jan, 2017 at the University of Vermont Medical Center. We identified 25 cases on whom BCI was submitted. Results: Median age was 68 years. Majority of the patients were stage IA (64%). 56% of the tumors were moderately differentiated. All patients were ER +ve and 12% were HER2+. Median tumor size was 1.4 cm (0.3-4). 76% had poor tolerance to the ET and preferred the test to be sent. In LN-patients, BCI identified 42% as high risk and 52% as low risk for late recurrence and 32% who derive high benefit from EET. In LN+ patients, BCI identified 75% as high risk for late recurrence and 25% as low risk for late recurrence. 40% of the entire group were identified to highly benefit from EET (70% agreed to continue ET and 30% denied due to side effects). Conclusions: BCI is a reasonable test to consider in early stage HR+ BC, especially in patients with poor tolerance to ET. This test might aid in decision making with tolerability/compliance challenges to EET. [Table: see text]

Value of clinical treatment score post-5 years (CTS5) for late relapse risk assessment in patients with early-stage HER2+ breast cancer (BC) in the north central cancer treatment group (NCCTG) N9831 (Alliance) trial.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. 529-529
Author(s):  
Tanmayi Pai ◽  
Angelica Gil ◽  
Yaohua Ma ◽  
Zhuo Li ◽  
Pooja Advani ◽  
...  
Keyword(s):  
Breast Cancer ◽  
High Risk ◽  
Tumor Size ◽  
Cox Regression ◽  
Early Stage ◽  
Low Risk ◽  
Late Relapse ◽  
Intermediate Risk ◽  
Relapse Risk ◽  
Significant Difference

529 Background: Multiple prognostic models exist to predict late relapse risk in early stage hormone receptor-positive (HR+) breast cancer (BC). The CTS5 is one such model that has been validated in HR+ HER2-negative BC. The value of this model in HR+ HER2+ has not been established. Here, we assessed CTS5 in patients (pts) with early stage HER2+ BC treated in the NCCTG N9831 (Alliance) trial. Methods: Pts with stage I-III HER2+ HR+ BC who survived ≥ 5 years were included. The online CTS5 calculator was used to determine CTS5 score and risk group (low, intermediate, and high) based on age, tumor size, grade, and number of involved nodes. Kaplan-Meier (KM) estimates, Cox regression models, and C index were used for analysis. Results: From 3,130 pts, 1,204 pts met the criteria and were included. Median age was 49 (22-79) years and median tumor size was 2.4 (0.1-12) cm. 63.6% had grade 3 tumors, 33.6% grade 2, and 2.8% grade 1. Median follow up was 10.89 (5.01-15.32) years. Based on CTS5, 821 (68.2%) pts were classified as high risk, 289 (24%) as intermediate risk, and 94 (7.8%) as low risk. Overall, using univariate Cox regression analysis, there was no statistically significant difference in recurrence free survival (RFS) among pts with intermediate vs. low (HR 0.47 95%CI 0.18-1.22, p = 0.12) and high vs. low (HR1.23 95%CI0.57-2.67, p = 0.6) with the C index of 0.58. Among pts who received concurrent trastuzumab (H) with HR+ BC, there was also no statistical difference in RFS between high vs. low (HR 0.68 95%CI0.24-1.97, p = 0.48) with the C index of 0.55. Paradoxically, pts with intermediate risk had better RFS than low risk (HR 0.18 95%CI0.03-0.97, p = 0.05). As a continuous variable, there is also no significant improvement in RFS per 1 unit increase in CTS5 score (HR 1.19 95%CI 0.73-1.96, p = 0.49) with the C index of 0.54. After 5 years, 7.06% (n = 30/425) of HR+ pts treated with concurrent H recurred. Conclusions: The CTS5 model is not prognostic in pts with early stage HR+ HER2+ BC receiving adjuvant H. While most HR+ HER2+ pts are classified as high risk by CTS5, the recurrence between years 5-10 was low in pts who received adjuvant H. This study highlights the need to develop a new predictive model for risk of late relapse in this specific group of pts to enable clinicians to determine which pts would benefit from extended adjuvant endocrine therapy. Support: BCRF-19-161, U10CA180821, Genentech. https://acknowledgments.alliancefound.org Clinical trial information: NCT00005970 .

scholarly journals Identification and Validation of m6A-Related lncRNA Signature as Potential Predictive Biomarkers in Breast Cancer

2021 ◽  
Vol 11 ◽  
Author(s):  
Wenchang Lv ◽  
Yichen Wang ◽  
Chongru Zhao ◽  
Yufang Tan ◽  
Mingchen Xiong ◽  
...  
Keyword(s):  
Breast Cancer ◽  
High Risk ◽  
Risk Score ◽  
Assessment Tool ◽  
Cox Regression ◽  
Screening Method ◽  
Predictive Biomarkers ◽  
Risk Groups ◽  
Low Risk ◽  
Main Challenge

The metastasis and poor prognosis are still regarded as the main challenge in the clinical treatment of breast cancer (BC). Both N6-methyladenosine (m6A) modification and lncRNAs play vital roles in the carcinogenesis and evolvement of BC. Considering the unknown association of m6A and lncRNAs in BC, this study therefore aims to discern m6A-related lncRNAs and explore their prognostic value in BC patients. Firstly, a total of 6 m6A-related lncRNAs were screened from TCGA database and accordingly constructed a prognostic-predicting model. The BC patients were then divided into high-risk and low-risk groups dependent on the median cutoff of risk score based on this model. Then, the predictive value of this model was validated by the analyses of cox regression, Kaplan-Meier curve, ROC curve, and the biological differences in the two groups were validated by PCA, KEGG, GSEA, immune status as well as in vitro assay. Finally, we accordingly constructed a risk prognostic model based on the 6 identified m6A-related lncRNAs, including Z68871.1, AL122010.1, OTUD6B-AS1, AC090948.3, AL138724.1, EGOT. Interestingly, the BC patients were divided into the low-risk and high-risk groups with different prognoses according to the risk score. Notably, the risk score of the model was an excellent independent prognostic factor. In the clinical sample validation, m6A regulatory proteins were differentially expressed in patients with different risks, and the markers of tumor-associated macrophages and m6A regulators were co-localized in high-risk BC tissues. This well-validated risk assessment tool based on the repertoire of these m6A-related genes and m6A-related lncRNAs, is of highly prognosis-predicting ability, and might provide a supplemental screening method for precisely judging BC prognosis.

An Autophagy-related Long Non-coding RNA Signature for Breast Cancer

2021 ◽  
Vol 24 ◽  
Author(s):  
Feng Jiang ◽  
Chuyan Wu ◽  
Ming Wang ◽  
Ke Wei ◽  
Jimei Wang
Keyword(s):  
Breast Cancer ◽  
High Risk ◽  
Cox Regression ◽  
Risk Group ◽  
Expression Profiles ◽  
Risk Groups ◽  
Low Risk ◽  
Optimal Cutoff ◽  
Non Coding Rna ◽  
Long Non Coding Rna

Background: The most prevalent malignant tumor in women is breast cancer (BC). Autophagic therapies have been identified for their contribution in BC cell death. Therefore, the potential prognostic role of long non-coding RNA (lncRNA) related to autophagy in patients with BC was examined. Methods: The lncRNAs expression profiles were derived from The Cancer Genome Atlas (TCGA) database. Throughout univariate Cox regression and multivariate Cox regression test, lncRNA with BC prognosis have been differentially presented. We then defined the optimal cutoff point between high and low-risk groups. The receiver operating characteristic (ROC) curves were drawn to test this signature. In order to examine possible signaling mechanisms linked to these lncRNAs, the Gene Set Enrichment Analysis (GSEA) has been carried out. Results: Based on the lncRNA expression profiles for BC, a 9 lncRNA signature associated with autophagy was developed. The optimal cutoff value for high-risk and low-risk groups was used. The high-risk group had less survival time than the low-risk group. The result of this lncRNA signature was highly sensitive and precise. GSEA study found that the gene sets have been greatly enriched in many cancer pathways. Conclusions: Our signature of 9 lncRNAs related to autophagy has prognostic value for BC, and these lncRNAs related to autophagy may play an important role in BC biology.

scholarly journals Assessment of the prognostic and predictive utility of the breast cancer index (BCI): An NCIC CTG MA.14 study.

2012 ◽  
Vol 30 (15_suppl) ◽  
pp. 561-561
Author(s):  
Dennis Sgroi ◽  
Paul Edward Goss ◽  
Judy-Anne W. Chapman ◽  
E. Richardson ◽  
Shemeica N. Binns ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cox Regression ◽  
Risk Index ◽  
Prospective Trial ◽  
Predictive Performance ◽  
Risk Groups ◽  
Primary Objective ◽  
Prognostic Performance ◽  
Breast Cancer Index ◽  
Significant Difference

561 Background: Breast Cancer Index (BCI), a continuous risk index, combines the ratio of HOXB13 to IL17BR (H/I) and the molecular grade index (MGI) (Jerevall et al., British J Cancer, 2011). Here, the prognostic and predictive performance of BCI for BC relapse in MA.14 trial was examined. Methods: MA.14 randomly assigned 667 hormone receptor positive (HR+) women to 5 years of tamoxifen (TAM) +/- 2 years of octreotide LAR (TAM-OCT). A representative subgroup of 299 patients was profiled by RT-PCR for BCI. The primary objective was to determine the prognostic performance of BCI based on relapse-free survival (RFS) with median 9.8 years follow-up. Association of BCI was assessed with step-wise forward stratified Cox regression. Pre-defined categories of low (L), intermediate (I) and high (H) BCI risk groups were used to provide adjusted 5- and 10-year RFS. Results: 292 of 299 patient samples passed internal analytical quality control. The 292 patients contained 49% LN+ patients and had 19.9% BC relapses. Both continuous and pre-specified BCI risk groups were significant multivariate factors (p<0.0001; p=0.007) with higher BCI associated with shorter RFS. Adjusted univariate hazard ratios and 95% CI were 2.53 (1.36 – 4.71) for BCI-H vs -L and 1.28 (0.65 – 2.52) for BCI-I vs -L. With both LN- and LN+ included, BCI-L had 5- and 10-year RFS of 94.0% and 87.5%; -I, 91.8% and 83.9%; and -H, 81.5% and 74.7%. No significant difference in BCI’s ability to stratify patients into 3 risk groups was observed between LN-/no chemotherapy subgroup vs balance of MA.14 patients (p=0.26). Higher pathologic T-stage was multivariately associated with shorter RFS (p=0.01). Interactions between trial therapy and BCI was not significant (p=0.40). Conclusions: This study confirmed the strong prognostic effect of BCI on breast cancer recurrence. BCI was prognostic in both LN- and LN+ patients. The lower 10-year RFS in the BCI-L group than in our previous studies reflected the mixed LN-/LN+ population examined. Like the parent MA.14 trial, BCI did not predict benefit of adding OCT to TAM therapy (Pritchard et al., J Clin Oncol, 2011). This retrospective study is an independent validation of the prognostic performance of BCI within a prospective trial.

Recurrence risk stratification by Dutch clinical risk criteria for early-stage luminal breast cancer patients in Taiwan: A population-based analysis.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e12509-e12509
Author(s):  
Lei Lei ◽  
Han-Ching Chan ◽  
Wang Xiao Jia ◽  
Tzu-Pin Lu ◽  
Skye Hung-Chun Cheng
Keyword(s):  
Breast Cancer ◽  
High Risk ◽  
Adjuvant Chemotherapy ◽  
Early Stage ◽  
Risk Groups ◽  
Low Risk ◽  
Luminal Breast Cancer ◽  
Breast Cancer Patients ◽  
Risk Patients

e12509 Background: Dutch clinical risk criteria (low-risk definition: age > 35 years and (grade 1 with tumor ≤3cm, grade 2 with tumor ≤2cm, or grade 3 with tumor ≤1cm) have been used to stratify the benefit of MammaPrint and Oncotype DX for the decision-making regarding adjuvant chemotherapy for early-stage luminal breast cancer. We propose that the criteria could help to identify low-risk patients who could barely benefit from multi-gene testing. Methods: Breast cancer patients from Taiwan Cancer Database initially treated with primary surgeries between 2008 and 2012 who met the following criteria: (1) pathologic node-negative, (2) hormone receptor-positive, (3) HER2-negative, (4) undergone hormonal therapy, and (5) a minimum follow-up time of 5-year if free from any event, were enrolled in this study. Out of the total 2679 eligible patients, 1074 (40.1%) patients received adjuvant chemotherapy in addition to endocrine therapy. The study endpoints included breast cancer-specific survival (BCSS) and overall survival (OS). Kaplan-Meier statistics estimated the difference between clinical outcomes in low- and high-risk groups. Results: The median follow-up time of BSCC and OS was 5.9 years (range, 0-7 years) and 5.8 years (range, 0-7 years), respectively. There were statistical significances of 5-year BCSS (n = 2679) and 5-year OS (n = 2636) between low-risk and high-risk groups (in both endpoints, P < 0.0001). According to the Dutch criteria, low-risk patients with and without adjuvant chemotherapy had a 5-year BCSS of 99.0% vs. 99.2% and a 5-year OS of 98.4% vs. 97.4%, respectively. High-risk patients with and without adjuvant chemotherapy had a 5-year BCSS of 97.7% vs. 98.1% and a 5-year OS of 96.4% vs. 95.3%, respectively. Conclusions: The benefit of chemotherapy in low-risk patients classified by Dutch criteria might be very small since the breast cancer mortality was less than 1% with a minimum of 5-year follow-up. Dutch criteria cannot identify high-risk patients who would benefit from chemotherapy. We assumed that multi-gene testing in low-risk patients would not be cost-effective.

scholarly journals Risk Evaluation of Early-stage Hormone Receptor-positive and Human Epidermal Growth Factor Receptor 2-negative Breast Cancer Patients: a Population-based Study From Taiwan

2021 ◽  
Author(s):  
Lei Lei ◽  
Han-Ching Chan ◽  
Tzu-Pin Lu ◽  
Hung-Chun Skye Cheng
Keyword(s):  
Breast Cancer ◽  
High Risk ◽  
Prognostic Value ◽  
Risk Group ◽  
Early Stage ◽  
Growth Factor Receptor ◽  
Risk Groups ◽  
Low Risk ◽  
Hormone Receptor Positive ◽  
Epidermal Growth

Abstract PURPOSE: To assess the prognostic value of the Dutch criteria for patients with early-stage hormone receptor-positive and human epidermal growth factor receptor 2-negative breast cancer from the Taiwan Cancer Database. PATIENTS AND METHODS:We included 8,295 patients with early-stage node-negative breast cancer who underwent surgery during January 2008–December 2012. Patients were stratified into low- and high-risk groups based on the Dutch criteria. The Kaplan–Meier method and log-rank test were used to estimate the difference in breast cancer-specific survival (BCSS) and overall survival (OS) between groups. Multivariable analysis was used to evaluate the prognostic value of the Dutch criteria.RESULTS: Overall, the low-risk and high-risk groups comprised 5,375 and 2,920 patients, respectively. In the low- and high-risk groups, the 5-year BCSS rate was 99.6% and 98.2% (P<0.0001) and the 5-year OS rate was 98.3% and 96.8% (P<0.0001), respectively. The hazard ratio for BCSS was 4.18 (95% confidence interval [CI], 2.63–6.63, P<0.0001), and the hazard ratio for OS was 1.94 (95% CI, 1.48–2.55); both were significantly poorer in the high-risk group than in the low-risk group. In the low-risk group, the 5-year BCSS and OS of patients who did and did not receive adjuvant chemotherapy were similar (99.5% versus 99.6% [P=0.927] and 98.8% and 98.1% [P=0.0683], respectively). CONCLUSIONS: The prognosis of low-risk patients as classified using the Dutch criteria is excellent with or without adjuvant chemotherapy. The benefit of multi-gene testing for chemotherapy decision-making might be minimal in these patients.

scholarly journals A prognostic model based on seven immune-related genes predicts the overall survival of patients with hepatocellular carcinoma

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Qian Yan ◽  
Wenjiang Zheng ◽  
Boqing Wang ◽  
Baoqian Ye ◽  
Huiyan Luo ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Overall Survival ◽  
High Risk ◽  
Risk Score ◽  
Immune Cells ◽  
Prognostic Model ◽  
Risk Groups ◽  
Low Risk ◽  
Prognostic Performance ◽  
Immune Related Genes

Abstract Background Hepatocellular carcinoma (HCC) is a disease with a high incidence and a poor prognosis. Growing amounts of evidence have shown that the immune system plays a critical role in the biological processes of HCC such as progression, recurrence, and metastasis, and some have discussed using it as a weapon against a variety of cancers. However, the impact of immune-related genes (IRGs) on the prognosis of HCC remains unclear. Methods Based on The Cancer Gene Atlas (TCGA) and Immunology Database and Analysis Portal (ImmPort) datasets, we integrated the ribonucleic acid (RNA) sequencing profiles of 424 HCC patients with IRGs to calculate immune-related differentially expressed genes (DEGs). Survival analysis was used to establish a prognostic model of survival- and immune-related DEGs. Based on genomic and clinicopathological data, we constructed a nomogram to predict the prognosis of HCC patients. Gene set enrichment analysis further clarified the signalling pathways of the high-risk and low-risk groups constructed based on the IRGs in HCC. Next, we evaluated the correlation between the risk score and the infiltration of immune cells, and finally, we validated the prognostic performance of this model in the GSE14520 dataset. Results A total of 100 immune-related DEGs were significantly associated with the clinical outcomes of patients with HCC. We performed univariate and multivariate least absolute shrinkage and selection operator (Lasso) regression analyses on these genes to construct a prognostic model of seven IRGs (Fatty Acid Binding Protein 6 (FABP6), Microtubule-Associated Protein Tau (MAPT), Baculoviral IAP Repeat Containing 5 (BIRC5), Plexin-A1 (PLXNA1), Secreted Phosphoprotein 1 (SPP1), Stanniocalcin 2 (STC2) and Chondroitin Sulfate Proteoglycan 5 (CSPG5)), which showed better prognostic performance than the tumour/node/metastasis (TNM) staging system. Moreover, we constructed a regulatory network related to transcription factors (TFs) that further unravelled the regulatory mechanisms of these genes. According to the median value of the risk score, the entire TCGA cohort was divided into high-risk and low-risk groups, and the low-risk group had a better overall survival (OS) rate. To predict the OS rate of HCC, we established a gene- and clinical factor-related nomogram. The receiver operating characteristic (ROC) curve, concordance index (C-index) and calibration curve showed that this model had moderate accuracy. The correlation analysis between the risk score and the infiltration of six common types of immune cells showed that the model could reflect the state of the immune microenvironment in HCC tumours. Conclusion Our IRG prognostic model was shown to have value in the monitoring, treatment, and prognostic assessment of HCC patients and could be used as a survival prediction tool in the near future.

scholarly journals CanAssist Breast Impacting Clinical Treatment Decisions in Early-Stage HR+ Breast Cancer Patients: Indian Scenario

2019 ◽  
Author(s):  
Satish Sankaran ◽  
Jyoti Bajpai Dikshit ◽  
Chandra Prakash SV ◽  
SE Mallikarjuna ◽  
SP Somashekhar ◽  
...  
Keyword(s):  
High Risk ◽  
Early Stage ◽  
Risk Groups ◽  
Treatment Decisions ◽  
Low Risk ◽  
Not Given ◽  
Breast Cancer Patients ◽  
Number Of Patients ◽  
Risk Of Cancer ◽  
The Impact

AbstractCanAssist Breast (CAB) has thus far been validated on a retrospective cohort of 1123 patients who are mostly Indians. Distant metastasis–free survival (DMFS) of more than 95% was observed with significant separation (P < 0.0001) between low-risk and high-risk groups. In this study, we demonstrate the usefulness of CAB in guiding physicians to assess risk of cancer recurrence and to make informed treatment decisions for patients. Of more than 500 patients who have undergone CAB test, detailed analysis of 455 patients who were treated based on CAB-based risk predictions by more than 140 doctors across India is presented here. Majority of patients tested had node negative, T2, and grade 2 disease. Age and luminal subtypes did not affect the performance of CAB. On comparison with Adjuvant! Online (AOL), CAB categorized twice the number of patients into low risk indicating potential of overtreatment by AOL-based risk categorization. We assessed the impact of CAB testing on treatment decisions for 254 patients and observed that 92% low-risk patients were not given chemotherapy. Overall, we observed that 88% patients were either given or not given chemotherapy based on whether they were stratified as high risk or low risk for distant recurrence respectively. Based on these results, we conclude that CAB has been accepted by physicians to make treatment planning and provides a cost-effective alternative to other similar multigene prognostic tests currently available.

scholarly journals Development and Verification of the Hypoxia- and Immune-Associated Prognostic Signature for Pancreatic Ductal Adenocarcinoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Dongjie Chen ◽  
Hui Huang ◽  
Longjun Zang ◽  
Wenzhe Gao ◽  
Hongwei Zhu ◽  
...  
Keyword(s):  
High Risk ◽  
Pancreatic Ductal Adenocarcinoma ◽  
Risk Score ◽  
Cox Regression ◽  
Pearson Correlation ◽  
Risk Groups ◽  
Low Risk ◽  
Ductal Adenocarcinoma ◽  
Prognostic Signature ◽  
Score Model

We aim to construct a hypoxia- and immune-associated risk score model to predict the prognosis of patients with pancreatic ductal adenocarcinoma (PDAC). By unsupervised consensus clustering algorithms, we generate two different hypoxia clusters. Then, we screened out 682 hypoxia-associated and 528 immune-associated PDAC differentially expressed genes (DEGs) of PDAC using Pearson correlation analysis based on the Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression project (GTEx) dataset. Seven hypoxia and immune-associated signature genes (S100A16, PPP3CA, SEMA3C, PLAU, IL18, GDF11, and NR0B1) were identified to construct a risk score model using the Univariate Cox regression and the Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression, which stratified patients into high- and low-risk groups and were further validated in the GEO and ICGC cohort. Patients in the low-risk group showed superior overall survival (OS) to their high-risk counterparts (p &lt; 0.05). Moreover, it was suggested by multivariate Cox regression that our constructed hypoxia-associated and immune-associated prognosis signature might be used as the independent factor for prognosis prediction (p &lt; 0.001). By CIBERSORT and ESTIMATE algorithms, we discovered that patients in high-risk groups had lower immune score, stromal score, and immune checkpoint expression such as PD-L1, and different immunocyte infiltration states compared with those low-risk patients. The mutation spectrum also differs between high- and low-risk groups. To sum up, our hypoxia- and immune-associated prognostic signature can be used as an approach to stratify the risk of PDAC.

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