Improving the prognosis of pancreatic cancer: insights from epidemiology, genomic alterations, and therapeutic challenges
Zhichen Jiang1,2, Xiaohao Zheng3,4, Min Li5(), Mingyang Liu1()
1. State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China 2. Department of General Surgery, Division of Gastroenterology and Pancreas, Zhejiang Provincial People’s Hospital, Affiliated People’s Hospital, Hangzhou Medical College, Hangzhou 310014, China 3. Department of Pancreatic and Gastric Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China 4. Department of General Surgery, Beijing Friendship Hospital, Capital Medical University, Beijing 100050, China 5. Department of Medicine, The University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA
Pancreatic cancer, notorious for its late diagnosis and aggressive progression, poses a substantial challenge owing to scarce treatment alternatives. This review endeavors to furnish a holistic insight into pancreatic cancer, encompassing its epidemiology, genomic characterization, risk factors, diagnosis, therapeutic strategies, and treatment resistance mechanisms. We delve into identifying risk factors, including genetic predisposition and environmental exposures, and explore recent research advancements in precursor lesions and molecular subtypes of pancreatic cancer. Additionally, we highlight the development and application of multi-omics approaches in pancreatic cancer research and discuss the latest combinations of pancreatic cancer biomarkers and their efficacy. We also dissect the primary mechanisms underlying treatment resistance in this malignancy, illustrating the latest therapeutic options and advancements in the field. Conclusively, we accentuate the urgent demand for more extensive research to enhance the prognosis for pancreatic cancer patients.
Integrating microarray-based spatial transcriptomics and single-cell RNA-seq reveals tissue architecture in pancreatic ductal adenocarcinomas
RNA
2020
Pancreatic cancer mice
Sun
10x Visium
Hypoxic microenvironment induced spatial transcriptome changes in pancreatic cancer
RNA
2021
Pancreatic cancer
Zhou
10x Visium
Spatially restricted drivers and transitional cell populations cooperate with the microenvironment in untreated and chemo-resistant pancreatic cancer
RNA
2022
Pancreatic cancer
Hwang
DSP
Single-nucleus and spatial transcriptome profiling of pancreatic cancer identifies multicellular dynamics associated with neoadjuvant treatment
RNA
2022
Pancreatic cancer
Barkley
10x Visium
Cancer cell states recur across tumor types and form specific interactions with the tumor microenvironment
RNA
2022
IPMN
Sans
10x Visium
Spatial transcriptomics of intraductal papillary mucinous neoplasms of the pancreas identifies NKX6-2 expression as a driver of gastric differentiation and indolent biological potential
RNA
biorxiv
IPMN
Agostini
10x Visium, GeoMx
Transcriptomic dissection of intraepithelial papillary mucinous neoplasms progression by spatial technologies identified novel markers of pancreatic carcinogenesis
RNA
biorxiv
PanIN
Bell
10x Visium
PanIN and CAF transitions in pancreatic carcinogenesis revealed with spatial data integration
RNA
biorxiv
Tab.1
Study
Techniques
Subtypes
New subtype
Waddell
WGS
Stable, locally rearranged, scattered and unstable
Yes
Moffitt
Bulk RNA
Classical, basal-like
Yes
Rashid
Bulk RNA
No new; PurIST classifers for classical, basal-like
Faecal metagenomic classifiers based on a set of 27 microbial species
NA
NA
0.84
167
Faecal metagenomic classifiers based on a set of 27 microbial species + CA19-9
NA
NA
0.94
167
Microbiota
30 gut microbiomes
NA
NA
0.78–0.82
155
30 gut microbiomes + CA19-9
NA
NA
0.81–0.97
155
Tab.3
Fig.2
Fig.3
Theme
Target
Included population
Approach
Time
Effectiveness
DOI
Conclusion
Gem-based clinical trials
NA
Advanced PC patients
GEM+5-FU
2002
OS: 6.7 Ms; PFS: 2.2 Ms
10.1200/JCO.2002.11.149
(1) GEM-based chemotherapy can bring survival outcomes to patients with advanced PC and patients with operable PC; (2) FOLFIRINOX can bring more survival benefits than GEM, but FOLFIRINOX is more demanding for patients; (3) GEM can improve the efficacy of 5-FU-based adjuvant chemoradiotherapy, and radiotherapy can improve the therapeutic effect of GEM
GEM
OS: 5.4 Ms; PFS: 2.2 Ms
Advanced PC patients
pemetrexed+GEM
2005
OS: 6.2 Ms; PFS: 3.9 Ms
10.1093/annonc/mdi309
GEM
OS: 6.3 Ms; PFS: 3.3 Ms
Patients with complete surgical resection of PC
Postoperative: GEM
2007
MDFS: 13.4 Ms; DFS at 3 years:23.5%; DFS at 5 years:16.5%; during a median follow-up of 53 Ms, 74% had relapsed
10.1001/jama.297.3.267
Postoperative: untreated
MDFS: 6.9 Ms; DFS at 3 years: 7.5%; DFS at 5 years: 5.5%; during a median follow-up of 53 Ms, 92% had relapsed
Most of the current clinical trials of targeted therapy are unsuccessful. Even a few of them have effects, but when they enter phase III clinical trials, they cannot achieve ideal results
Matrix metalloproteinases
Unresectable PC patients
Marimastat
2001
OS: 125 Ds; 1-year survival: 20%
10.1200/JCO.2001.19.15.3447
Thymidylate synthase
Advanced PC patients
GEM+Tomudex
2003
OS: 185 Ds
10.1093/annonc/mdg150
FTase
Advanced PC patients
R115777
2003
PFS: 4.9 Ws; OS: 19.7 Ws
10.1200/JCO.2003.08.040
mTOR pathway
Patients with gemcitabine- refractory, metastatic PC
RAD001 (everolimus)
2009
PFS: 1.8 Ms; OS: 4.5 Ms
10.1200/JCO.2008.18.9514
EGFR
Patients with R0- or R1-PC
GEM+cetuximab
2013
OS: 22.4 Ms; DFS: 10.0 Ms
10.1093/annonc/mdt270
IGF1R pathway
Patients with previously untreated metastatic PC
GEM
2015
OS: 7.2 Ms
10.1093/annonc/mdv027
Ganitumab+GEM
OS: 7.0 Ms
The MEK and PI3K/AKT pathways
Patients with gemcitabine-refractory, metastatic PC
Selumetinib+MK-2206
2017
OS: 3.9 Ms; PFS: 1.9 Ms
10.1001/jamaoncol.2016.5383
mFOLFOX (oxaliplatin plus fluorouracil)
OS: 6.7 Ms; PFS: 2 Ms
Src kinase
Patients with locally advanced, non-metastatic PC
GEM+dasatinib
2017
OS: 375 Ds; PFS: 167 Ds
10.1093/annonc/mdw607
GEM
OS: 393 Ds; PFS: 166 Ds
EGFR
Untreated, unresectable, advanced/metastatic PC patients
GEM+nimotuzumab
2017
OS: 8.6 Ms; PFS: 5.1 Ms
10.1093/annonc/mdx343
GEM
OS: 6.0 Ms; PFS: 3.4 Ms
The EGFR tyrosine kinase
Patients with resectable PDAC post-R0 resection
GEM+erlotinib
2017
OS: 24.5 Ms; DFS: 11.4 Ms
10.1200/JCO.2017.72.6463
GEM
OS: 26.5 Ms; DFS: 11.4 Ms
Wee1 kinase
Newly diagnosed, locally advanced PC patients
AZD1775 (adavosertib)+GEM+radiation
2019
OS: 21.7 Ms; DFS: 9.4 Ms
10.1200/JCO.19.00730
FTase
Advanced PC patients
Tipifarnib+GEM
2004
OS: 193 Ds; PFS: 112 Ds
10.1200/JCO.2004.10.112
GEM
OS: 182 Ds; PFS: 108 Ds
Ras-dependent signaling and angiogenic pathways
Advanced PC patients
GEM+sorafenib
2012
OS: 8 Ms; PFS: 3.8 Ms; 6-month PFS: 33%
10.1093/annonc/ mds135
GEM
OS: 9.2 Ms; PFS: 5.7 Ms; 6-month PFS: 48%
JAK/STAT pathway
Patients with gemcitabine-refractory, metastatic PC
Ruxolitinib+capecitabine
2015
OS: 4.5 Ms
10.1200/JCO.2015.61.4578
Capecitabine
OS: 4.3 Ms
SHH
PC patients not suitable for curative treatment with no prior metastatic therapy
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