scholarly journals Identification of an Individualized Metabolism Prognostic Signature and Related Therapy Regimens in Early Stage Lung Adenocarcinoma

2021 ◽  
Vol 11 ◽  
Author(s):  
Junjie Hu ◽  
Huansha Yu ◽  
Liangdong Sun ◽  
Yilv Yan ◽  
Lele Zhang ◽  
...  
Keyword(s):  
High Risk ◽  
Adjuvant Therapy ◽  
Lung Adenocarcinoma ◽  
In Silico ◽  
Early Stage ◽  
Stage I ◽  
Stage Ii ◽  
Related Gene ◽  
High Risk Patients ◽  
Risk Patients

ObjectiveThe choice of adjuvant therapy for early stage lung adenocarcinoma (LUAD) remains controversial. Identifying the metabolism characteristics leading to worse prognosis may have clinical utility in offering adjuvant therapy.MethodsThe gene expression profiles of LUAD were collected from 22 public datasets. The patients were divided into a meta-training cohort (n = 790), meta-testing cohort (n = 716), and three independent validation cohorts (n = 345, 358, and 321). A metabolism-related gene pair index (MRGPI) was trained and validated in the cohorts. Subgroup analyses regarding tumor stage and adjuvant chemotherapy (ACT) were performed. To explore potential therapeutic targets, we performed in silico analysis of the MRGPI.ResultsThrough machine learning, MRGPI consisting of 12 metabolism-related gene pairs was constructed. MRGPI robustly stratified patients into high- vs low-risk groups in terms of overall survival across and within subpopulations with stage I or II disease in all cohorts. Multivariable analysis confirmed that MRGPI was an independent prognostic factor. ACT could not improve prognosis in high-risk patients with stage I disease, but could improve prognosis in the high-risk patients with stage II disease. In silico analysis indicated that B3GNT3 (overexpressed in high-risk patients) and HSD17B6 (down-expressed in high-risk patients) may make synergic reaction in immune evasion by the PD-1/PD-L1 pathway. When integrated with clinical characteristics, the composite clinical and metabolism signature showed improved prognostic accuracy.ConclusionsMRGPI could effectively predict prognosis of the patients with early stage LUAD. The patients at high risk may get survival benefit from PD-1/PD-L1 blockade (stage I) or combined with chemotherapy (stage II).

Using a clinicopathologic and gene expression model to identify melanoma patients at high risk for disease relapse.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. 10068-10068
Author(s):  
Alexander M. Eggermont ◽  
Domenico Bellomo ◽  
Félicia Tjien-Fooh ◽  
Renske Wever ◽  
Enrica Quattrocchi ◽  
...  
Keyword(s):  
Gene Expression ◽  
High Risk ◽  
Early Stage ◽  
Low Risk ◽  
Stage I ◽  
Diagnostic Tools ◽  
Disease Relapse ◽  
High Risk Patients ◽  
Risk Patients ◽  
Melanoma Patients

10068 Background: The identification of early stage melanoma patients at high risk for relapse is still difficult. Roughly 50% of melanoma deaths occur in patients who were initially diagnosed with nonmetastatic melanoma. Therefore, a strong clinical need has emerged for diagnostic tools that can identify melanoma patients at high risk for relapse. Here, we assessed the performance of a recently developed model (Bellomo et al., JCO Precis Oncol. 2020: in press), combining clinicopathologic and gene expression variables (CP-GEP), in identifying melanoma patients that have a high risk for disease relapse. Methods: We assessed the prognostic performance of the CP-GEP model in a cohort of 837 consecutive melanoma patients from Mayo Clinic who had a sentinel lymph node biopsy (SLNb) performed within 90 days of their diagnosis. The CP-GEP model combines Breslow thickness and patient age, with the expression of 8 genes in the primary tumor, to stratify patients according to their risk of relapse: CP-GEP High Risk or CP-GEP Low Risk. The main clinical endpoint of this study was five-year relapse free survival (RFS). Results: Patients were stratified based on SLNb status and CP-GEP classification. 76% of the patients were SLNb negative and had an RFS of 79% versus 52% for SLNb positive patients; HR, 3.21; P < 0.0001. 60% of the patients were identified as CP-GEP High Risk and had an RFS of 62% versus 87% for CP-GEP Low Risk patients; HR, 4.12; P < 0.0001. Within the SLNb negative group (637 patients of which 65% stage I), 51% of patients were classified as CP-GEP High Risk. Here, RFS was 70% for CP-GEP High Risk patients versus 89% for CP-GEP Low Risk patients; HR, 3.61; P < 0.0001. The prognosis of these CP-GEP High Risk patients is similar to stage IIC/IIIA patients with reported RFS ranging from 63% to 77%. This confirms the heterogeneity in prognosis among patients with stage I/II melanoma disease. Conclusions: The CP-GEP model can be successfully used to stratify patients based on their risk for relapse. In particular, it can be used to identify SLNb negative patients with a high risk for disease relapse who may benefit from therapeutic interventions. Independent validation studies are ongoing to validate the CP-GEP model in various patient populations. [Table: see text]

How to restrict liver biopsy to high-risk patients in early-stage Hodgkin's disease

2000 ◽  
Vol 79 (2) ◽  
pp. 73-78 ◽  
Author(s):  
D. Lieberz ◽  
M. Sextro ◽  
U. Paulus ◽  
J. Franklin ◽  
H. Tesch ◽  
...  
Keyword(s):  
High Risk ◽  
Liver Biopsy ◽  
Hodgkin's Disease ◽  
Early Stage ◽  
Hodgkin’S Disease ◽  
High Risk Patients ◽  
Risk Patients

scholarly journals Outcomes After Surgery in High-Risk Patients With Early Stage Lung Cancer

2016 ◽  
Vol 101 (3) ◽  
pp. 1043-1051 ◽  
Author(s):  
Manu S. Sancheti ◽  
John N. Melvan ◽  
Rachel L. Medbery ◽  
Felix G. Fernandez ◽  
Theresa W. Gillespie ◽  
...  
Keyword(s):  
Lung Cancer ◽  
High Risk ◽  
Early Stage ◽  
Early Stage Lung Cancer ◽  
High Risk Patients ◽  
Risk Patients ◽  
Stage Lung Cancer

scholarly journals Use of a Combination of CEA and Tumor Budding to Identify High-risk Patients with Stage II Colon Cancer

2017 ◽  
Vol 32 (3) ◽  
pp. 267-273 ◽  
Author(s):  
Changzheng Du ◽  
Weicheng Xue ◽  
Fangyuan Dou ◽  
Yifan Peng ◽  
Yunfeng Yao ◽  
...  
Keyword(s):  
Colon Cancer ◽  
High Risk ◽  
Disease Progression ◽  
Disease Free Survival ◽  
Stage Ii ◽  
Tumor Budding ◽  
High Risk Patients ◽  
Prognostic Accuracy ◽  
Risk Patients ◽  
Stage Ii Colon Cancer

Background High-risk patients with stage II colon cancer may benefit from adjuvant chemotherapy, but identifying this patient population can be difficult. We assessed the prognosis value for predicting tumor progression in patients with stage II colon cancer, of a panel of 2 biomarkers for colon cancer: tumor budding and preoperative carcinoembryonic antigen (CEA). Methods Consecutive patients (N = 134) with stage II colon cancer who underwent curative surgery from 2000 to 2007 were included. Multivariate analysis was used to evaluate the association of CEA and tumor budding grade with 5-year disease-free survival (DFS). The prognostic accuracy of CEA, tumor budding grade and the combination of both (CEA-budding panel) was determined. Results The study found that both CEA and tumor budding grade were associated with 5-year DFS. The prognostic accuracy for disease progression was higher for the CEA-budding panel (82.1%) than either CEA (70.9%) or tumor budding grade (72.4%) alone. Conclusions The findings indicate that the combination of CEA levels and tumor budding grade has greater prognostic value for identifying patients with stage II colon cancer who are at high-risk for disease progression, than either marker alone.

Neuroendocrine carcinoma of the cervix: A single institution’s experience.

2012 ◽  
Vol 30 (15_suppl) ◽  
pp. e15585-e15585
Author(s):  
Megan Preston ◽  
Georgia Anne-Lee McCann ◽  
David M. O'Malley ◽  
Christina Boutsicaris ◽  
Larry J. Copeland ◽  
...  
Keyword(s):  
Adjuvant Therapy ◽  
Metastatic Disease ◽  
Survival Data ◽  
Early Stage ◽  
Stage I ◽  
Stage Ii ◽  
Advanced Stage ◽  
Single Institution ◽  
Early Stage Disease ◽  
Stage Disease

e15585 Background: Neuroendocrine carcinomas (NEC) of the cervix comprise only 2% of all cervical cancers. As a result, prospective data is limited and treatment guidelines rely on literature from lung NEC. The objective of this study was to examine and report on our experience in the management of this rare, aggressive disease. Methods: This was an IRB-approved, single-institution, retrospective review. Study criteria included patients with cervical NEC diagnosed between 1990-2011. Demographic, treatment and survival data was collected. Progression-free survival (PFS) and overall survival (OS) was defined as the time from date of initial treatment until progression or death respectively, or date of last contact. Results: A total of 24 patients met inclusion criteria. The median age at diagnosis was 43. Median PFS was 13.6 months and median OS was 16.4 months. The majority of patients had advanced-stage disease (61% stage II-IV, 39% stage I). Of the 9 patients with stage I disease, 4 were treated with platinum + etoposide-based neoadjuvant chemotherapy and 5 were treated with initial radical surgery. Seven of the 9 patients had post-operative adjuvant therapy consisting of chemotherapy, chemo-radiation or radiation only. Seven of the 9 patients (78%) were alive at last follow-up. Of the two patients who were deceased, one had metastatic disease found at surgery and the other declined adjuvant therapy and died of recurrence. Patients with stage II-IV disease (n=15) had a median PFS and OS of 11.5 and 12.1 months, respectively. Only 2 had no evidence of disease at last encounter. The remainder died without achieving remission. Patients with metastatic disease had significantly worse survival when compared to those with loco-regional disease with a median OS of 8 vs. 28 months (p = .03), respectively. Conclusions: We report one of the largest single-institution experiences of neuroendocrine cervical cancer. Advanced-stage patients had a poor prognosis regardless of therapy. However, multi-modality therapy in early-stage disease resulted in an excellent prognosis (78% survival) for these rare, highly aggressive tumors. These findings support the goal of curative intent for early-stage disease using multi-modality therapy.

Genomic classifiers (ColoPrint/MSI-Print) predict outcome and chemotherapy benefit in stage II and III colon cancer patients.

2013 ◽  
Vol 31 (4_suppl) ◽  
pp. 378-378 ◽  
Author(s):  
Scott Kopetz ◽  
Zhi-Qin Jiang ◽  
Michael J. Overman ◽  
Christa Dreezen ◽  
Sun Tian ◽  
...  
Keyword(s):  
Colon Cancer ◽  
High Risk ◽  
Adjuvant Chemotherapy ◽  
Cancer Patients ◽  
Additional Treatment ◽  
Low Risk ◽  
Stage Ii ◽  
High Risk Patients ◽  
Risk Patients

378 Background: Although the benefit of chemotherapy in stage II and III colon cancer patients is significant, many patients might not need adjuvant chemotherapy because they have a good prognosis even without additional treatment. ColoPrint is a gene expression classifier that distinguish patients with low or high risk of disease relapse. It was developed using whole genome expression data and has been validated in public datasets, independent European patient cohorts and technical studies (Salazar 2011 JCO, Maak 2012 Ann Surg). Methods: In this study, the commercial ColoPrint test was validated in stage II (n=96) and III patients (n=95) treated at the MD Anderson Cancer Center from 2003 to 2009. Frozen tissue specimen, clinical parameters, MSI-status and follow-up data (median follow-up 64 months) were available. The 64-gene MSI-signature developed to identify patients with deficient mismatch repair system (Tian 2012 J Path) was evaluated for its accuracy to identify MSI patients and also for prognosis. Results: In this cohort, ColoPrint classified 56% of stage II and III patients as being at low risk. The 3-year Relapse-Free-Survival (RFS) was 90.6% for Low Risk and 78.4% for High Risk patients with a HR of 2.33 (p=0.025). In uni-and multivariate analysis ColoPrint and stage were the only significant factors to predict outcome. The MSI-signature classified 47 patients (24.6%) as MSI-H and most MSI-H patients were ColoPrint low risk (81%). Patients who were ColoPrint low risk and MSI-H by signature had the best outcome with a 3-year RFS of 95% while patients with ColoPrint high risk had a worse outcome independently of the MSI-status. Low risk ColoPrint patients had a good outcome independent of stage or chemotherapy treatment (90.1% 3-year RFS for treated patients, 91.4% for untreated patients) while ColoPrint high risk patients treated with adjuvant chemotherapy had 3-year RFS of 84%, compared to 70.1% 3-year RFS in untreated patients (p=0.026). Conclusions: The combination of ColoPrint and MSI-Print improves the prognostic accuracy in stage II and stage III patients and may help the identification of patients at higher risk who are more likely to benefit from additional treatment

The potential of a CLIA-certified prognostic/predictive molecular test to address the rising costs of non-small cell lung cancer.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e21671-e21671
Author(s):  
Michael J Mann ◽  
David Jablons ◽  
Ken O'Day ◽  
Wayne Su ◽  
Padma Sundar
Keyword(s):  
Lung Cancer ◽  
High Risk ◽  
Adjuvant Therapy ◽  
Risk Stratification ◽  
Small Cell ◽  
Stage I ◽  
Molecular Test ◽  
Small Cell Lung ◽  
Prospective Data ◽  
Risk Patients

e21671 Background: Treating recurrences of non-small cell lung cancer (NSCLC) is increasingly expensive but still rarely curative. Disease free survival (DFS) among resected stage I-IIA patients remains only 50-70%. Guidelines advocate adjuvant therapy in “high-risk” patients in this population to reduce these costly and deadly recurrences, but recognize that conventional criteria have not been validated to stratify risk or predict benefit. A CLIA-certified, commercially available 14-gene expression risk profile (DetermaRx) has been extensively validated among stage I-IIA non-squamous NSCLC patients; prospective data now suggest that the test predicts improved DFS with adjuvant therapy. We therefore studied the potential economic impact of this molecular test on early stage NSCLC. Methods: Model variables included: relative increase in DFS with adjuvant treatment of molecular intermediate- and high-risk patients (25.5%; range 12.3-41.3%); cost of adjuvant ($8,760; $8,144-$9,376) or late-stage ($284,500; $224,900-345,200) treatment; and compliance with recommendations for adjuvant therapy (75%; 60-90%). Ranges were based on: historical trials and recent prospective data, published cost literature, and published survey data, respectively. Parameters were varied in a multifactorial, one-way sensitivity analysis to assess the impact of parameter uncertainty. Results: Reduction of recurrences with implementation of the 14-gene assay resulted in an average cost savings of $11,608/patient (potential systems savings of ~$450 million), even when including the cost of molecular risk stratification ($4000/patient) and of cisplatin-based adjuvant chemotherapy for molecular high- and intermediate-risk patients. Lower bound assumptions for relative improvement, cost of care, and compliance yielded persistent savings of $3,699, $8,091 and $8,486, respectively. Conclusions: Utilization of this predictive molecular risk stratification assay in the management of stage I-IIA non-squamous NSCLC has the potential to significantly reduce lung cancer costs in an era of targeted therapy and immunotherapy, while at the same time improving DFS and saving lives.

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