Research progress of individualized precision treatment for pancreatic cancer

Yong Tang*

Research progress of individualized precision treatment for pancreatic cancer

Yong Tang1*

1Department of Pancreatic Neoplasms, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer; Tianjin Key Laboratory of Cancer Prevention and Treatment; Tianjin Clinical Medical Research Center for Malignant Tumors,Tianjin 300060, China.

The author summarized the role of gene sequencing technology in the occurrence and development of pancreatic cancer and its relationship with prognosis, providing precise guidance for the treatment of individualized patients.

Currently, there is the extremely poor prognosis for pancreatic cancer. Despite the continuous development of various technologies, the long-term survival rate is not improved well. With the rapid development of genomics and biotechnology, the concept of tumor precision treatment has attracted much attention. Gene sequencing technology and biomarker detection have been used to deeply explore the mechanism of the occurrence and development of pancreatic cancer and applied it to clinical diagnosis and treatment, making it possible for patients to carry out individualized precision treatment for pancreatic cancer. Multiple-factor analysis combined with meaningful biological indicators is more helpful to determine individualized diagnosis and treatment measures. This paper summarizes the research results in the above aspects.

Pancreatic cancer, Precision treatment, Molecular typing, Multiple-factor analysis

Background

Currently, there is the extremely poor prognosis for pancreatic cancer. 80% of the patients have lost the opportunity of radical surgery at diagnosis, and the overall 5-year survival rate is less than 10% [1]. Chemotherapy is still the main treatment for pancreatic cancer [2]. Clinical chemotherapy schemes for pancreatic cancer include single drug and combined drug, which are mainly based on tumor stage and the physical condition of patients, with the low effective probability. Therefore, how to find an effective treatment plan according to individual characteristics will be conducive to improving the efficacy and prolonging the survival of patients [2]. In 2015, U.S. President Barack Obama put forward the "National Precision Medicine Plan" in his State of the Union address, which made precision medicine widely concerned. With the rapid development of genomics and biotechnology, the new concept of precision medicine has rapidly become a hot spot in the global medical field, making precision medicine possible [3, 4, 5].

Some scholars define precision medicine as fllowing. Through clinical and biological information data and omics technology, biomarkers of specific patients and disease types are analyzed, identified, verified and applied, the causes of diseases and treatment targets are defined, and different states and processes of diseases are accurately classified, so as to finally realize the purpose of individualized precision diagnosis and treatment of specific patients and diseases, including the following links: information collection (clinical and biological information data), omics analysis (precise biomarkers), individualized medical treatment (diagnosis, drug therapy and prognosis). Precision medicine aims to integrate clinical information, patient genetic characteristics and phenotype, and gene & protein expression profile to tailor precise diagnosis, treatment strategy and prognosis for patients.

Findings of gene sequencing in the mechanism of pancreatic cancer occurrence and development

Molecular biology studies have found that there are 12 core signaling pathways involved in the occurrence and development of pancreatic cancer, and pancreatic cancer may be a rare type in molecular biology. Yachida et al. carried out DNA sequencing for tissue samples of primary and metastatic foci (usually liver, lung and peritoneum) in 7 patients with advanced pancreatic cancer. It is found that the average course of pancreatic cancer is nearly 20 years. Among them, there were about 15 years from the appearance of the first pancreatic cancer tumor cell to diagnosis, and about 3−5 years from discovery to metastasis, suggesting that malignant transformation of pancreatic cancer is a long-term process[6]. Notta detected the genomes of 107 patients with pancreatic cancer and found that chromosome fragmentation events can lead to the simultaneous occurrence of two or more gene mutations necessary for the occurrence of pancreatic cancer, instead of the sequential occurrence previously thought [7]. These findings suggest that it is a great challenge for pancreatic cancer to be diagnosed and intervened before its lesions appear.

In 2008, Professor Jones and his team in the United States used polymerase chain reaction amplification and Sanger sequencing to detect exons in 24 cases with pancreatic ductal adenocarcinoma and verified them in 90 other pancreatic cancer samples. On average, 48 non-silent mutations occurred in each pancreatic cancer sample. The mutation involves 12 core signaling pathways, including 4 "high-frequency driver genes" of pancreatic cancer such as,,and. The mutation rate ofin pancreatic cancer was greater than 95%,, andwas greater than 90%,was 50%−75%, andwas 55%. There are also 7 low-frequency driver genes such as,,,,,and, which participate in the gene "topographic map" of pancreatic cancer [8], which is of great significance to the diagnosis, prognosis and individualized treatment of pancreatic cancer.

Guidance of gene sequencing for treatment of pancreatic cancer

Genotyping of pancreatic cancer: The current technological development makes it possible to accurately integrate clinical typing and genotyping of pancreatic cancer, thus realizing precision medicine of pancreatic cancer [9]. Waddell et al. analyzed 100 cases with pancreatic cancer by next-generation whole genome sequencing. According to the chromosome structure rearrangement, they were divided into 4 gene subtypes: stable type, local rearrangement type, dispersal type and unstable type. The study found that 5 unstable patients received platinum chemotherapy due to recurrence of pancreatic cancer, 4 patients responded to chemotherapy, 2 patients received PR and 2 patients received CR, while 3 patients of other types did not respond to chemotherapy, which indicated that gene mutations of different subtypes corresponded to specific drug targets, and genome copy number affected the efficacy of chemotherapy drugs. The results suggested that DNA damage (platinum), chemotherapy drugs preventing DNA repair and PARP inhibitors had better efficacy on unstable pancreatic cancer [10]. The latest POLO research results showed that for patients with advanced metastatic pancreatic cancer withmutation, PARP inhibitor Olaparib was used for maintenance therapy after first-line platinum-containing chemotherapy, which significantly prolongs progression-free survival (mPFS: 7.4 m vs 3.8 m; HR = 0. 53), and reduce the risk of disease progression by 47% compared with placebo control group. 1 year later, there was 33.7% vs 4.5% in Olaparib treatment group vs placebo group for no disease progression; 2 years later, there was 22.1% vs 9.6% in Olaparib treatment group vs placebo group for no disease progression. As a result, the clinical treatment mode of advanced pancreatic cancer may undergo major changes [11].

Bailey et al. used whole genome and deep exome sequencing to carry out integrated genome analysis on 456 cases with pancreatic cancer and its histopathological variation, and found 32 significant mutant genes in 10 signaling pathways. Through RNA sequence data analysis, pancreatic cancer was divided into four types: squamous cell type, pancreatic progenitor cell type, ADEX type and immunogenic type. Studies have found that each subtype has different survival rates, genetic characteristics and different sensitivities to different treatment methods. Squamous cell tumors are rich inandgene mutations, with up-regulation oftranscription network and methylation of fate-determining genes in pancreatic endoderm cells and the extremely poor prognosis. The average survival is just 4m, which is half of the other subtypes. Pancreatic progenitor cell tumors can preferentially express genes involved in early pancreatic development. Endocrine and exocrine tumors can not only regulate K-ras activation, but also up-regulate genes related to pancreatic exocrine and exocrine differentiation. Immunogenic tumors can up-regulate immune network genes including acquired immunosuppressive pathways. These four types are closely related to histology and prognosis. Most squamous adenocarcinoma is squamous cell type with a median survival time of 13.3 m. Acinar cell carcinoma is ADEX type with a median survival time of 25.7 m. Pancreatic carcinoma originating from cystic tumor is pancreatic progenitor cell type or immunogenic type with a median survival time of 23.7 m and 30m. Different molecular typing can select different therapeutic targets, such as up-regulation ofandin immuno-prototype pancreatic cancer, which can be considered to use immunotherapy in later clinical research [12].

American scholars apply non-negative matrix factorization to differentiate gene expression between pancreatic cancer tissue and tumor stroma, and classify pancreatic cancer tissue according to gene expression difference between tumor tissue and stroma. According to the gene difference of matrix, pancreatic cancer can be divided into activated type and normal type, and according to the gene difference of cancer tissue, pancreatic cancer can be divided into basal cell type and classic type. Clinical follow-up found that pancreatic cancer with basal cell type of cancer tissue has poor prognosis, but may benefit from postoperative adjuvant therapy. Classical/normal stroma pancreatic cancer tissue has the best prognosis, while classical pancreatic cancer patients cannot benefit from postoperative adjuvant therapy[13].

Prompt of biomarkers for postoperative adjuvant therapy

A prospective study found that the level of human equilibrative nucleoside transporter 1 (hENT1) may predict the prognosis of patients with gemcitabine adjuvant therapy after pancreatic cancer surgery, and gemcitabine therapy is not suitable for pancreatic cancer patients with low expression level of tumor hENT1. The study included 380 patients (87.6%) and 1,808 biopsy specimens. One hundred and seventy-six patients received gemcitabine, with a median overall survival time of 23.4 m (95% CI = 18.3−26.0), while 176 patients received 5-fluorouracil/folinic acid had a median overall survival time of 23.5 m (95% CI = 19.8−27.3,= 0. 62). Among gemcitabine-treated patients, the median overall survival time was 17.1 m (95% CI = 14.3−23.8) for patients with low hENT1 expression, and 26.2 m (95% CI = 21.2−31.4;= 0. 002) for patients with high hENT1 expression. In the 5-fluorouracil group, the median overall survival time of patients with low and high expression of hENT1 was 25.6 m (95% CI = 20.1−27.9) and 21.9 m (95% CI = 16.0−28.3;=0.36), respectively [14]. However, hENT1, as a biomarker for predicting gemcitabine benefits, is only effective in postoperative adjuvant therapy. A subsequent systematic review, including 770 patients with pancreatic cancer after resection, also confirmed this conclusion [15]. When there is metastasis, hENT1 cannot effectively predict whether patients can benefit from gemcitabine [16, 17].

Multiple-factor analysis for prognostic treatment of pancreatic cancer

The prognosis of tumor is affected by multiple factors. Comprehensive multiple-factor analysis can help the selection of individualized treatment for pancreatic cancer. Previous studies on the influence of multiple factors have mostly paid attention to clinical features, and less analysis has been made on some biological index factors. Some scholars have added DNA ploidy of tumor cells to the analysis on the influence of multiple factors on prognosis, and found that different ploidy are independent determinants of prognosis. There were 25 diploid and 11 tetraploid pancreatic cancer patients in this group, with an average survival of 28 m and 30 m respectively, and 26 non-tetraploid patients with an average survival of 5 m. The positive rate of p21 and p53 in pancreatic cancer tissues was 89% and 51%, respectively. The expression of p21 and p53 was closely correlated with clinical stages. Single-factor analysis showed that DNA ploidy, retroperitoneal infiltration, surgical method, liver metastasis, clinical stage, p21 expression and duodenal infiltration were closely correlated with prognosis. In multiple-factor analysis, only DNA ploidy and clinical stage were independent prognostic determinants. In 39 patients with radical resection, the average survival time of diploid, tetraploid and aneuploid were 31 m, 30 m and 7 m respectively (< 0.01). Among the patients with radical resection, 2/30 died of diploid and tetraploid pancreatic cancer and 4/9 died of aneuploid pancreatic cancer. The influence weights of multiple factors on the outcome are different. According to the influence weights of various factors, researchers use the column chart method to help judge the prognosis and choose treatment. More and more researchers use the column chart to predict the prognosis of tumors [18, 19]. Japanese scholars from five Japanese hospitals used prospective research methods to collect data on inoperable pancreatic cancer patients receiving gemcitabine-based chemotherapy, and the results showed that 204 cases were in stage III and 327 cases in stage IV, and the overall median survival time was 11.3 m. The nomogram could predict the survival probability and median survival time of 6 m, 2 m and 18 m, including the following 6 parameters: age, gender, physical condition, tumor size, local lymph node metastasis and distant metastasis. The deduced nomographic chart is helpful to provide valuable information for the individualized treatment decisions of patients in the early stage after diagnosis [20].

In conclusion, with the development of molecular biology technology, gene sequencing have deeply revealed the role of gene mutation in the occurrence and development of pancreatic cancer and its relationship with prognosis, which is expected to accurately guide the treatment of individualized patients. The efficacy and prognosis of pancreatic cancer patients are affected by multiple factors. Multiple factor analysis can be used to find meaningful biological indicators, so as to determine individualized characteristics. Therefore, it may be a research direction for individualized precision diagnosis and treatment in the future.

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hENT1, human equilibrative nucleoside transporter 1.

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The authors declare that they have no conflict of interest.

: 08 December 2020

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Yong Tang. Research progress of individualized precision treatment for pancreatic cancer. Precision Medicine Research 2020, 2 (4): 165–170.

: Xiao-Hong Sheng.

: 15 September 2020,

04 December 2020,

*Corresponding to: Yong Tang. Cancer Institute and Hospital, Tianjin Medical University, No. 1 Huanhu Xilu Road, Hexi District, Tianjin 300060, China. Email: tli001@163.com.