Back

Tumor response-speed heterogeneity as a novel prognostic factor in patients with mCRC

Liu, J.; Wang, X.; Sahin, I. H.; Imanirad, I.; Felder, S. I.; Kim, R. D.; Xie, H.

2022-07-29 oncology
10.1101/2022.07.22.22277828 medRxiv
Show abstract

PurposeDifferential tumor response to therapy is partially attributed to tumor heterogeneity. Additional efforts are needed to identify tumor heterogeneity parameters in response to therapy that are easily applicable in clinical practice. We aimed to describe tumor response-speed heterogeneity and evaluate its prognostic value in patients with metastatic colorectal cancer (mCRC). Patients and MethodsIndividual patient data from Amgen (NCT00364013) and Sanofi (NCT00305188; NCT00272051) trials were retrieved from Project Data Sphere. Patients in the Amgen 5-fluorouracil, leucovorin, oxaliplatin (FOLFOX) arm were used to establish response-speed heterogeneity. Its prognostic value was subsequently validated in the Sanofi FOLFOX arms and the Amgen panitumumab + FOLFOX arm. Kaplan-Meier method and Cox proportional hazards models were used for survival analyses. ResultsPatients with high response-speed heterogeneity in the Amgen FOLFOX cohort had significantly shorter (P<0.001) median progression-free survival (PFS) of 7.27 months (95%CI 6.12-7.96 months) and overall survival (OS) of 16.0 months (95%CI 13.8-18.2 months) than patients with low response-speed heterogeneity with median PFS of 9.41 months (95%CI 8.75- 10.89 months) and OS of 22.4 months (95%CI 20.1-26.7 months), respectively. Tumor response-speed heterogeneity was a poor prognostic factor of shorter PFS (HR 4.17, 95%CI 2.49-6.99, P<0.001) and shorter OS (HR 2.57, 95%CI 1.64-4.01, P<0.001), after adjustment for other common prognostic factors. Comparable findings were found in the external validation cohorts. ConclusionTumor response-speed heterogeneity to first-line chemotherapy was a novel prognostic factor associated with early disease progression and shorter survival in patients with mCRC. Implications for PracticeRoutine clinical decision making heavily relies on radiographic assessment of disease response to therapy. For patients with heterogeneous tumors, the degree and kinetics of individual tumor response to the same therapy can sometimes be vastly different. We explored a novel quantitative parameter to describe response-speed heterogeneity by utilizing individual patient data from previous clinical trials. This parameter was an independent prognostic factor associated with early disease progression and shorter survival. Complementary to existing molecular and radiographic tumor heterogeneity parameters, it may help practicing oncologists describe tumor response disparity and serve as a new prognostic factor for patients with mCRC.

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

1
Cancers
200 papers in training set
Top 0.2%
13.9%
2
Frontiers in Oncology
95 papers in training set
Top 0.2%
9.7%
3
JCO Precision Oncology
14 papers in training set
Top 0.1%
9.7%
4
British Journal of Cancer
42 papers in training set
Top 0.2%
6.6%
5
Clinical Cancer Research
58 papers in training set
Top 0.2%
6.6%
6
npj Precision Oncology
48 papers in training set
Top 0.1%
6.2%
50% of probability mass above
7
Scientific Reports
3102 papers in training set
Top 39%
3.5%
8
Cancer Medicine
24 papers in training set
Top 0.4%
3.5%
9
JCO Clinical Cancer Informatics
18 papers in training set
Top 0.3%
3.0%
10
Annals of Oncology
13 papers in training set
Top 0.2%
3.0%
11
Nature Communications
4913 papers in training set
Top 48%
2.0%
12
PLOS ONE
4510 papers in training set
Top 51%
1.8%
13
BMC Cancer
52 papers in training set
Top 1%
1.8%
14
JAMA Network Open
127 papers in training set
Top 2%
1.8%
15
JNCI: Journal of the National Cancer Institute
16 papers in training set
Top 0.3%
1.7%
16
BMJ Open
554 papers in training set
Top 9%
1.6%
17
PLOS Computational Biology
1633 papers in training set
Top 18%
1.4%
18
European Journal of Cancer
10 papers in training set
Top 0.2%
1.4%
19
JNCI Cancer Spectrum
10 papers in training set
Top 0.3%
1.4%
20
Molecular Cancer Therapeutics
33 papers in training set
Top 0.5%
1.2%
21
eBioMedicine
130 papers in training set
Top 3%
0.9%
22
Breast Cancer Research
32 papers in training set
Top 0.4%
0.9%
23
Frontiers in Immunology
586 papers in training set
Top 8%
0.7%
24
BMC Infectious Diseases
118 papers in training set
Top 6%
0.7%
25
Computational and Structural Biotechnology Journal
216 papers in training set
Top 10%
0.7%
26
Journal for ImmunoTherapy of Cancer
64 papers in training set
Top 1%
0.7%
27
International Journal of Cancer
42 papers in training set
Top 1%
0.7%
28
Translational Oncology
18 papers in training set
Top 0.5%
0.7%
29
Cancer Research
116 papers in training set
Top 4%
0.6%
30
Neuro-Oncology Advances
24 papers in training set
Top 0.5%
0.6%