scholarly journals Pancreatic cancer: Assessment of neoadjuvant chemotherapy outcome based on radiomics of pretreatment computed tomography.

2019 ◽  
Vol 5 (suppl) ◽  
pp. 56-56
Author(s):  
Xiang Li ◽  
Tianyu Tang ◽  
Tingbo Liang ◽  
Xueli Bai
Keyword(s):  
Computed Tomography ◽  
Pancreatic Cancer ◽  
Regression Analysis ◽  
Neoadjuvant Chemotherapy ◽  
Treatment Response ◽  
Tumor Size ◽  
Cox Regression ◽  
Supervised Machine Learning ◽  
Histopathological Response ◽  
Cox Regression Analysis

56 Background: To evaluate contrast enhanced-computed tomography (CE-CT) features to predicting treatment response and survival after neoadjuvant chemotherapy (NAC) for patients with borderline resectable and locally advanced pancreatic cancer. Methods: Sixty-one patients with pancreatic cancer receiving NAC were enrolled and underwent pre-treatment abdominal CE-CT. The patients were divided into groups according to post-treatment tumor size changes. Based on the pretreatment CE-CT images, 396 radiomic features were extracted from three-dimensional regions of interest. The optimal features were selected and three supervised machine learning classifiers were developed. Finally, univariate and multivariate analyses were performed to evaluate the ability of the selected features to predict the histopathological response and outcome. Results: Nine, seven, and five radiomic features, respectively, were selected as optimal features in three experiments. Two features, Haralick Entropy and Histogram Entropy, were consistent among the experiments and both were higher in patients with enlarged tumors. Moreover, a lower Histogram Entropy score was significantly associated with a better histopathological response (p = 0.008) and smaller tumor size (p = 0.041) in patients after tumor resection. In univariate Cox regression analysis, lower Histogram Entropy (p = 0.006) and lower Haralick Entropy (p = 0.001) predicted a better prognosis. Meanwhile, lower Haralick Entropy (p = 0.048) was an independent predictor of longer survival time in multivariate Cox regression analysis. Conclusions: Radiomic features are strongly correlated with NAC treatment response and prognosis in pancreatic cancer, suggesting the potential of imaging radiomics to help tailor the treatment of pancreatic cancer in the era of personalized medicine.

Pancreatic cancer: Assessment of neoadjuvant chemotherapy outcome based on radiomics of pretreatment computed tomography.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. e15767-e15767
Author(s):  
Xiang Li ◽  
Tianyu Tang ◽  
Xueli Bai ◽  
Tingbo Liang
Keyword(s):  
Computed Tomography ◽  
Pancreatic Cancer ◽  
Regression Analysis ◽  
Neoadjuvant Chemotherapy ◽  
Treatment Response ◽  
Cancer Patients ◽  
Tumor Size ◽  
Cox Regression ◽  
Cox Regression Analysis ◽  
Histopathologic Response

e15767 Background: The objective response rate to neoadjuvant chemotherapy (NAC) was limited to around 35% in pancreatic cancer and as more as 30% patients show no benefit to NAC. In this instance, predicting the response to NAC may play an important role in individual treatment for pancreatic cancer patients. We aim to evaluate contrast enhanced-computed tomography (CE-CT) features in predicting treatment response and survival after neoadjuvant chemotherapy (NAC) for patients with borderline resectable and locally advanced pancreatic cancer. Methods: Sixty-one pancreatic cancer patients receiving NAC were enrolled and underwent abdominal CE-CT before treatment. All patients were divided into groups according to the changes of tumor size after treatment. 396 radiomics features were extracted from three-dimensional ROIs (region of interest) based on pretreatment CE-CT images of each patient. The optimal features were selected and three supervised machine learning classifiers were developed. Finally, univariate and multivariate analyses were performed to evaluate the capability of the selected features in predicting histopathologic response and outcomes. Results: Nine, seven and five radiomics features were selected as optimal features for three experiments respectively. Two features, Haralick Entropy and Histogram Entropy, were found consistent in experiments and were both higher in patients with tumor enlargement. Moreover, lower Histogram Entropy was significantly associated with a better histopathologic response (p = 0.008) and smaller tumor size (p = 0.041) in patients with tumor resection. In univariate Cox regression analysis, lower Histogram Entropy (P = 0.006) and lower Haralick Entropy (P = 0.001) predicted a better prognosis. Meanwhile, lower Haralick Entropy (p = 0.048) was independent predictor for longer survival time in multivariate Cox regression analysis. Conclusions: Radiomics features are strongly correlated with NAC treatment response and prognosis in pancreatic cancer, suggesting the great potential of imaging radiomics to help tailoring the treatment into the era of personalized medicine

Factors Predictive of Distant Metastases in Patients With Breast Cancer Who Have a Pathologic Complete Response After Neoadjuvant Chemotherapy

2005 ◽  
Vol 23 (28) ◽  
pp. 7098-7104 ◽  
Author(s):  
Ana M. Gonzalez-Angulo ◽  
Sean E. McGuire ◽  
Thomas A. Buchholz ◽  
Susan L. Tucker ◽  
Henry M. Kuerer ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Regression Analysis ◽  
Neoadjuvant Chemotherapy ◽  
Distant Metastasis ◽  
Cox Regression ◽  
Clinical Stage ◽  
Pathologic Complete Response ◽  
Distant Metastases ◽  
Complete Response ◽  
Cox Regression Analysis

Purpose To identify clinicopathological factors predictive of distant metastasis in patients who had a pathologic complete response (pCR) after neoadjuvant chemotherapy (NC). Methods Retrospective review of 226 patients at our institution identified as having a pCR was performed. Clinical stage at diagnosis was I (2%), II (36%), IIIA (27%), IIIB (23%), and IIIC (12%). Eleven percent of all patients were inflammatory breast cancers (IBC). Ninety-five percent received anthracycline-based chemotherapy; 42% also received taxane-based therapy. The relationship of distant metastasis with clinicopathologic factors was evaluated, and Cox regression analysis was performed to identify independent predictors of development of distant metastasis. Results Median follow-up was 63 months. There were 31 distant metastases. Ten-year distant metastasis-free rate was 82%. Multivariate Cox regression analysis using combined stage revealed that clinical stages IIIB, IIIC, and IBC (hazard ratio [HR], 4.24; 95% CI, 1.96 to 9.18; P < .0001), identification of ≤ 10 lymph nodes (HR, 2.94; 95% CI, 1.40 to 6.15; P = .004), and premenopausal status (HR, 3.08; 95% CI, 1.25 to 7.59; P = .015) predicted for distant metastasis. Freedom from distant metastasis at 10 years was 97% for no factors, 88% for one factor, 77% for two factors, and 31% for three factors (P < .0001). Conclusion A small percentage of breast cancer patients with pCR experience recurrence. We identified factors that independently predicted for distant metastasis development. Our data suggest that premenopausal patients with advanced local disease and suboptimal axillary node evaluation may be candidates for clinical trials to determine whether more aggressive or investigational adjuvant therapy will be of benefit.

scholarly journals Bioinformatics-Based Identification of Tumor Microenvironment-Related Prognostic Genes in Pancreatic Cancer

2021 ◽  
Vol 12 ◽  
Author(s):  
Shaojie Chen ◽  
Feifei Huang ◽  
Shangxiang Chen ◽  
Yinting Chen ◽  
Jiajia Li ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Overall Survival ◽  
Regression Analysis ◽  
Tumor Microenvironment ◽  
Operating Characteristic ◽  
Cox Regression ◽  
Time Dependent ◽  
Concordance Index ◽  
Cox Regression Analysis ◽  
Score Model

ObjectiveGrowing evidence has highlighted that the immune and stromal cells that infiltrate in pancreatic cancer microenvironment significantly influence tumor progression. However, reliable microenvironment-related prognostic gene signatures are yet to be established. The present study aimed to elucidate tumor microenvironment-related prognostic genes in pancreatic cancer.MethodsWe applied the ESTIMATE algorithm to categorize patients with pancreatic cancer from TCGA dataset into high and low immune/stromal score groups and determined their differentially expressed genes. Then, univariate and LASSO Cox regression was performed to identify overall survival-related differentially expressed genes (DEGs). And multivariate Cox regression analysis was used to screen independent prognostic genes and construct a risk score model. Finally, the performance of the risk score model was evaluated by Kaplan-Meier curve, time-dependent receiver operating characteristic and Harrell’s concordance index.ResultsThe overall survival analysis demonstrated that high immune/stromal score groups were closely associated with poor prognosis. The multivariate Cox regression analysis indicated that the signatures of four genes, including TRPC7, CXCL10, CUX2, and COL2A1, were independent prognostic factors. Subsequently, the risk prediction model constructed by those genes was superior to AJCC staging as evaluated by time-dependent receiver operating characteristic and Harrell’s concordance index, and both KRAS and TP53 mutations were closely associated with high risk scores. In addition, CXCL10 was predominantly expressed by tumor associated macrophages and its receptor CXCR3 was highly expressed in T cells at the single-cell level.ConclusionsThis study comprehensively investigated the tumor microenvironment and verified immune/stromal-related biomarkers for pancreatic cancer.

scholarly journals Analysis of CK5/6 and EGFR and Its Effect on Prognosis of Triple Negative Breast Cancer

2021 ◽  
Vol 10 ◽  
Author(s):  
Zhen Wang ◽  
Lei Liu ◽  
Ying Li ◽  
Zi’an Song ◽  
Yi Jing ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Regression Analysis ◽  
Neoadjuvant Chemotherapy ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Cox Regression ◽  
Multivariate Logistic Regression Analysis ◽  
Pathological Examination ◽  
Cox Regression Analysis ◽  
Tumor Stages

BackgroundTriple-negative breast cancer (TNBC) is considered to be higher grade, more aggressive and have a poorer prognosis than other types of breast cancer. Discover biomarkers in TNBC for risk stratification and treatments that improve prognosis are in dire need.MethodsClinical data of 195 patients with triple negative breast cancer confirmed by pathological examination and received neoadjuvant chemotherapy (NAC) were collected. The expression levels of EGFR and CK5/6 were measured before and after NAC, and the relationship between EGFR and CK5/6 expression and its effect on prognosis of chemotherapy was analyzed.ResultsThe overall response rate (ORR) was 86.2% and the pathological complete remission rate (pCR) was 29.2%. Univariate and multivariate logistic regression analysis showed that cT (clinical Tumor stages) stage was an independent factor affecting chemotherapy outcome. Multivariate Cox regression analysis showed pCR, chemotherapy effect, ypT, ypN, histological grades, and post- NAC expression of CK5/6 significantly affected prognosis. The prognosis of CK5/6-positive patients after NAC was worse than that of CK5/6-negative patients (p=0.036). Changes in CK5/6 and EGFR expression did not significantly affect the effect of chemotherapy, but changes from positive to negative expression of these two markers are associated with a tendency to improve prognosis.ConclusionFor late-stage triple negative breast cancer patients receiving NAC, patients who achieved pCR had a better prognosis than those with non- pCR. Patients with the change in expression of EGFR and CK5/6 from positive to negative after neoadjuvant chemotherapy predicted a better prognosis than the change from negative to positive group.

Oncological outcomes of neoadjuvant chemotherapy in patients with locally advanced upper tract urothelial carcinoma: A multicenter study.

2018 ◽  
Vol 36 (6_suppl) ◽  
pp. 429-429
Author(s):  
Shingo Hatakeyama ◽  
Yuka Kubota ◽  
Hayato Yamamoto ◽  
Takahiro Yoneyama ◽  
Yasuhiro Hashimoto ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Neoadjuvant Chemotherapy ◽  
Urothelial Carcinoma ◽  
Lymphovascular Invasion ◽  
Cox Regression ◽  
Locally Advanced ◽  
Upper Tract Urothelial Carcinoma ◽  
Cancer Specific Survival ◽  
Cox Regression Analysis ◽  
Oncological Outcomes

429 Background: The clinical impact of neoadjuvant chemotherapy (NAC) on oncological outcomes in patients with locally advanced upper tract urothelial carcinoma (UTUC) remains unclear. We investigated the oncological outcomes of platinum-based NAC for locally advanced UTUC. Methods: A total of 426 patients who underwent radical nephroureterectomy at five medical centers between January 1995 and April 2017 were examined retrospectively. Of the 426 patients, 234 were treated for a high-risk disease (stages cT3–4 or locally advanced [cN+] disease) with or without NAC. NAC regimens were selected based on eligibility of cisplatin. We retrospectively evaluated post-therapy pathological downstaging, lymphovascular invasion, and prognosis stratified by NAC use. Multivariate Cox regression analysis was performed for independent factors for prognosis. Results: Of 234 patients, 101 received NAC (NAC group) and 133 did not (Control [Ctrl] group). The regimens in the NAC group included gemcitabine and carboplatin (75%), and gemcitabine and cisplatin (21%). Pathological downstagings of the primary tumor and lymphovascular invasion were significantly improved in the NAC than in the Ctrl groups. NAC for locally advanced UTUC significantly prolonged recurrence-free and cancer-specific survival. Multivariate Cox regression analysis using an inverse probability of treatment weighted (IPTW) method showed that NAC was selected as an independent predictor for prolonged recurrence-free and cancer-specific survival. However, the influence of NAC on overall survival was not statistically significant. Conclusions: Platinum-based NAC for locally advanced UTUC potentially improves oncological outcomes. Further prospective studies are needed to clarify the clinical benefit of NAC for locally advanced UTUC.

scholarly journals Influence of Old Age on Risk of Lymph Node Metastasis and Survival in Patients With T1 Colorectal Cancer: A Population-Based Analysis

2021 ◽  
Vol 11 ◽  
Author(s):  
Hua Ye ◽  
Bin Zheng ◽  
Qi Zheng ◽  
Ping Chen
Keyword(s):  
Colorectal Cancer ◽  
Regression Analysis ◽  
Lymph Node ◽  
Elderly Patients ◽  
Old Age ◽  
Tumor Size ◽  
Cox Regression ◽  
Cox Regression Analysis ◽  
T1 Colorectal Cancer ◽  
Well Differentiated

BackgroundWe aimed at determining the influence of old age on lymph node metastasis (LNM) and prognosis in T1 colorectal cancer (CRC).MethodsWe collected data from eligible patients in Surveillance, Epidemiology, and End Results database between 2004 and 2015. Independent predictors of LNM were identified by logistic regression analysis. Cox regression analysis, propensity score-matched analysis, and competing risks analysis were used to analyze the associations between old age and lymph node (LN) status and to validate the prognostic value of old age on cancer-specific survival (CSS).ResultsIn total, 10,092 patients were identified. Among them, 6,423 patients (63.6%) had greater than or equal to 12 examined lymph nodes (LNE ≥12), and 5,777 patients (57.7%) were 65 years or older. The observed rate of LNM was 4.6% (15 out of 325) in T1 CRC elderly patients, with tumor size &lt;3 cm, well differentiated, with negative carcinoembryonic antigen (CEA) level, and adenocarcinoma. Logistic regression models demonstrated that tumor size ≥3 cm (odds ratio, OR = 1.316, P = 0.038), poorly differentiated (OR = 3.716, P &lt; 0.001), older age (OR = 0.633 for ages 65–79 years, OR = 0.477 for age over 80 years, both P &lt;0.001), and negative CEA level (OR = 0.71, P = 0.007) were independent prognostic factors. Cox regression analysis demonstrated that CSS was not significantly different between elderly patients undergoing radical resection with LNE ≥12 and those with LNE &lt;12 (hazard ratio = 0.865, P = 0.153), which was firmly validated after a propensity score-matched analysis by a competing risks model.ConclusionsThe predictive value of tumor size, grading, primary site, histology, CEA level, and age for LNM should be considered in medical decision making about local resection. We found that tumor size was &lt;3 cm, well differentiated, negative CEA level, and adenocarcinoma in elderly patients with T1 colorectal cancer which was suitable for local excision.

scholarly journals A Novel Autophagy-Related IncRNAs Signature for Prognostic Prediction and Clinical Value in Patients With Pancreatic Cancer

2020 ◽  
Vol 8 ◽  
Author(s):  
Zhengdong Deng ◽  
Xiangyu Li ◽  
Yuanxin Shi ◽  
Yun Lu ◽  
Wei Yao ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Regression Analysis ◽  
Cox Regression ◽  
Risk Scores ◽  
Migration And Invasion ◽  
Characteristic Analysis ◽  
Cox Regression Analysis ◽  
Validation Set ◽  
Prognostic Prediction

Autophagy is an important bioprocess throughout the occurrence and development of cancer. However, the role of autophagy-related lncRNAs in pancreatic cancer (PC) remains obscure. In the study, we identified the autophagy-related lncRNAs (ARlncRNAs) and divided the PC patients from The Cancer Genome Atlas into training and validation set. Firstly, we constructed a signature in the training set by the least absolute shrinkage and selection operator penalized cox regression analysis and the multivariate cox regression analysis. Then, we validated the independent prognostic role of the risk signature in both training and validation set with survival analysis, receiver operating characteristic analysis, and Cox regression. The nomogram was established to demonstrate the predictive power of the signature. Moreover, high risk scores were significantly correlated to worse outcomes and severe clinical characteristics. The Pearson’s analysis between risk scores with immune cells infiltration, tumor mutation burden, and the expression level of chemotherapy target molecules indicated that the signature could predict efficacy of immunotherapy and targeted therapy. Next, we constructed an lncRNA–miRNA–mRNA regulatory network and identified several potential small molecule drugs in the Connectivity Map (CMap). What’s more, quantitative real-time PCR (qRT-PCR) analysis showed that serum LINC01559 could serve as a diagnostic biomarker. In vitro analysis showed inhibition of LINC01559 suppressed PC cell proliferation, migration, and invasion. Additionally, silencing LINC01559 suppressed gemcitabine-induced autophagy and promoted the sensitivity of PC cells to gemcitabine. In conclusion, we identified a novel ARlncRNAs signature with valuable clinical utility for reliable prognostic prediction and personalized treatment of PC patients. And inhibition of LINC01559 might be a novel strategy to overcome chemoresistance.

scholarly journals А New Combination of Prognostic Markers in Follicular Lymphoma That Influences the Choice of Therapy

Blood ◽  
2021 ◽  
Vol 138 (Supplement 1) ◽  
pp. 4520-4520
Author(s):  
Ekaterina S. Nesterova ◽  
Nataliya A. Severina ◽  
Bella V. Biderman ◽  
Andrey B. Sudarikov ◽  
Tatiana N. Obukhova ◽  
...  
Keyword(s):  
Risk Factors ◽  
Regression Analysis ◽  
Follicular Lymphoma ◽  
Tumor Size ◽  
Cox Regression ◽  
Proliferation Index ◽  
Ki 67 ◽  
Cox Regression Analysis ◽  
Risk Of Death ◽  
Probability Of Death

Abstract Background: Follicular lymphoma (FL) is characterized by clinical and morphological heterogeneity. It is based on the pathogenetic mechanisms of the development of tumor cells. The identification and assessment of risk factors associated with the course of the disease and treatment outcome in FL is an important task, as it allows to evaluate and predict the effectiveness of therapy. Objective: Identify and estimate risk factors for overall survival (OS) and progression free survival (PFS) in FL. Patients and Methods: The prospective exploratory study conducted at National Research Center for Hematology (Moscow) from 01/2017 to 04/2021 included patients (pts)(in total, 80) with FL. Morpho-immunohistochemical, cytogenetic and molecular studies were performed on biopsies of lymph nodes taken before the start of therapy. The mutational status of exon 16 and intron polymorphism rs_2072407 of the EZH2 gene were investigated by Sanger sequencing. 18q21/BCL-2 rearrangements were determined by conventional cytogenetic analysis and/or FISH study. The results obtained in a blind study were compared with the effect of the therapy. Results: Of the 80 pts 34 were male: Me (median) age 50 years (range 30-72) and 46 were female: Me 56 (range 21-81). The median follow-up (FU) time was 53 months. As a result of the study in the multivariate Cox regression model (likelihood-ratio test, p=0.01) of significant factors, selected in the previously univariate analysis, the following statistically significant (Wald test) risk factors for OS and PFS (the events: progression, relapse, or death) were obtained: • BCL-2 gene rearrangements (no vs yes) • EZH2 gene genotypes (AA/AG vs GG) • proliferation index Ki-67 (&gt;35%) • morphological grade (3А vs 1/2) • tumor size (&gt;6 cm /bulky/) (Tab. 1, Fig. 1) The BCL-2 rearrangements were found in 45 from 80 pts (56%; 95 % CI 45-66). The probability of BCL-2 rearrangements is estimated to be about 0.5 (50%). According to the results of Cox-regression analysis (by OS) in the absence of BCL-2 rearrangements, the risk of death in FL was generally significantly (p = 0.01) higher than in the group with its presence: HR = 4.3 (95 % CI 1.5-13.0) (Fig. 2) Mutations in the 16th exon of the EZH2 gene (mutEZH2) were found in 10/80 (13%) pts. Analysis of EZH2 gene mutations with BCL-2 rearrangements revealed that in the mutEZH2 group with the presence of BCL-2 rearrangements, the number of deaths associated with progression is significantly less than in the control initial groups (mutEZH2 with BCL-2 rearrangements - 0/6, mutEZH2 without BCL-2 rearrangements - 2/4, wEZH2 with BCL-2 rearrangements - 3/39 (8%), wEZH2 without BCL-2 rearrangements - 11/31 (35%)) . The prognostic significance of EZH2 genotypes in lymphomas was studied for the first time in this study. The frequencies of rs_2072407 genotypes were: AA - 24% (19), AG - 42% (34), and GG - 34% (27). AA and AG genotypes of the EZH2 gene in pts with FL were associated with an increased risk of death (compared to the GG genotype) : HR = 2.9 (95% CI: 1.2-10.6), p = 0.01 (Fig. 3). The GG variant in most cases was associated with wEZH2 (26/27 (96%)) with BCL-2 rearrangements (16/26 (62%)) and a favorable prognosis (26/27 (96%)) (p = 0.01). Index of proliferative activity Ki-67&gt; 35% (n = 40) and Ki-67 ≤ 35% (n = 40) were equally common in the study group. With a Ki-67&gt; 35%, the probability of death is 2.9 (95% CI 1.1-9.7) times higher. The frequency distribution of morphological grade was as follows: grade 3A - 53% (n = 43) and grade 1-2 - 47% (n = 37). At grade 3A, the probability of death is 2.5 (95% CI 1.1-7.8) times higher. The number of pts with tumor size &gt;6 cm (bulky) and ≤ 6 cm in the sample is approximately the same (41 and 39, respectively), the presence of bulky increased the mortality risk by 2.1 (95% CI 1.0-6.5) times. A short time from the manifestation of the disease to appeal to medical care is a predictor of poor prognosis, but this result we received earlier on a large sample of pts was not significant on a smaller sample. Conclusions: As a result of the multivariable Cox regression analysis, we identified and confirmed the previously obtained factors (bulky, grade 3A, Ki-67 &gt; 35%, short medical history), and discovered new biogenetic factors (BCL-2 rearrangements and the GG rs2072407 genotype of the EZH2 gene). The model based on these independent risk factors improves the accuracy of predicting adverse events and allows to use more personalized treatment options for patients with FL. Figure 1 Figure 1. Disclosures No relevant conflicts of interest to declare.

Residual cancer burden (RCB) is practical and may be more informative than pathological response following neoadjuvant chemotherapy (NC) for locally advanced breast cancer (LABC)

2007 ◽  
Vol 25 (18_suppl) ◽  
pp. 21103-21103
Author(s):  
D. Sivasubramaniam ◽  
R. Komrokji ◽  
S. Dhaliwal ◽  
V. Sundarajan ◽  
Z. Nahleh
Keyword(s):  
Breast Cancer ◽  
Regression Analysis ◽  
Neoadjuvant Chemotherapy ◽  
Advanced Breast Cancer ◽  
Cox Regression ◽  
Locally Advanced Breast Cancer ◽  
Locally Advanced ◽  
Pathological Response ◽  
P Value ◽  
Cox Regression Analysis

21103 Background: Complete pathological response (pCR) has been considered a reliable endpoint to assess the benefit of NC. However, different pathological responses ranging from near complete response to resistance would likely indicate different prognostic groups. Method: We studied patients with locally advanced breast cancer (LABC) who received NC between 2001–2006 at the University of Cincinnati. Pathological response to therapy was evaluated. In addition, RCB was quantified according to MD Anderson RCB Calculator index that combines pathologic measurements of primary tumor (size and cellularity) and nodal metastases (number and size). We examined the correlation between pCR, RCB, event-free survival (EFS) and over all survival (OS) by Cox regression analyses. Result: Pathological slides of 32 patients were analyzed. Median age 52, 38% white and 62% African American. Stage IIB 12% , Stage IIIA 19%, Stage IIIB 53% and Stage IIIC 16% . 72% invasive ducal, 6% invasive lobular and 22% inflammatory cancer. Forty seven percent of tumors were ER +/or PR+ , 53% ER-/PR-, 28% HER-2 /neu + ( IHC 3+ or FISH HER2 gene to chromosome 17 ration > 2.2). Tumor response was as follows: 22% (n=7) achieved pCR , RCB scores ranged between 0- 4.87. By univariate Cox regression analysis, RCB correlated with EFS {Hazard ratio (HR) 1.57 (95% CI 1.04–2.38), p-value 0.018}, and with OS {HR 1.74 (95% CI 0.91 -3.32), p value-0.09}. However, pCR did not seem to correlate with EFS {HR 0 .24 (95%CI 0.03 -1.86–2.38), p-value .172} or OS {HR 0.03 (95% CI 0–89),p value-0.40}. By multivariate Cox regression analysis, RCB was noted to be an independent predictive variable for EFS {HR 1.59 (95% CI 1.04–2.43), p value-0.033} while pCR was not {HR 0.90 (95% CI 0.52–1.57), p value-0.7. Conclusion: RCB was easily quantifiable and appears to be a better predictor of outcome following neoadjuvant chemotherapy in LABC compared to pCR. Higher RCB scores were associated with higher EFS and lower rate of OS. Prospective trials are needed to further evaluate the role of RCB as an endpoint following NC. No significant financial relationships to disclose.

scholarly journals Identification of a Ubiquitination-Related Gene Risk Model for Predicting Survival in Patients With Pancreatic Cancer

2020 ◽  
Vol 11 ◽  
Author(s):  
Hao Zuo ◽  
Luojun Chen ◽  
Na Li ◽  
Qibin Song
Keyword(s):  
Pancreatic Cancer ◽  
Regression Analysis ◽  
Cancer Patients ◽  
Risk Model ◽  
Cox Regression ◽  
Expression Profiles ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Transcriptional Level ◽  
Cox Regression Analysis

Pancreatic cancer is known as “the king of cancer,” and ubiquitination/deubiquitination-related genes are key contributors to its development. Our study aimed to identify ubiquitination/deubiquitination-related genes associated with the prognosis of pancreatic cancer patients by the bioinformatics method and then construct a risk model. In this study, the gene expression profiles and clinical data of pancreatic cancer patients were downloaded from The Cancer Genome Atlas (TCGA) database and the Genotype-tissue Expression (GTEx) database. Ubiquitination/deubiquitination-related genes were obtained from the gene set enrichment analysis (GSEA). Univariate Cox regression analysis was used to identify differentially expressed ubiquitination-related genes selected from GSEA which were associated with the prognosis of pancreatic cancer patients. Using multivariate Cox regression analysis, we detected eight optimal ubiquitination-related genes (RNF7, NPEPPS, NCCRP1, BRCA1, TRIM37, RNF25, CDC27, and UBE2H) and then used them to construct a risk model to predict the prognosis of pancreatic cancer patients. Finally, the eight risk genes were validated by the Human Protein Atlas (HPA) database, the results showed that the protein expression level of the eight genes was generally consistent with those at the transcriptional level. Our findings suggest the risk model constructed from these eight ubiquitination-related genes can accurately and reliably predict the prognosis of pancreatic cancer patients. These eight genes have the potential to be further studied as new biomarkers or therapeutic targets for pancreatic cancer.

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