Is There a Standard Adjuvant Therapy for Resected Pancreatic Cancer?

Investigating underlying molecular mechanisms, signaling pathways, emerging therapeutic approaches in pancreatic cancer

Pancreatic adenocarcinoma, a clinically challenging malignancy constitutes a significant contributor to cancer-related mortality, characterized by an inherently poor prognosis. This review aims to provide a comprehensive understanding of pancreatic adenocarcinoma by examining its multifaceted etiologies, including genetic mutations and environmental factors. The review explains the complex molecular mechanisms underlying its pathogenesis and summarizes current therapeutic strategies, including surgery, chemotherapy, and emerging modalities such as immunotherapy. Critical molecular pathways driving pancreatic cancer development, including KRAS, Notch, and Hedgehog, are discussed. Current therapeutic strategies, including surgery, chemotherapy, and radiation, are discussed, with an emphasis on their limitations, particularly in terms of postoperative relapse. Promising research areas, including liquid biopsies, personalized medicine, and gene editing, are explored, demonstrating the significant potential for enhancing diagnosis and treatment. While immunotherapy presents promising prospects, it faces challenges related to immune evasion mechanisms. Emerging research directions, encompassing liquid biopsies, personalized medicine, CRISPR/Cas9 genome editing, and computational intelligence applications, hold promise for refining diagnostic approaches and therapeutic interventions. By integrating insights from genetic, molecular, and clinical research, innovative strategies that improve patient outcomes can be developed. Ongoing research in these emerging fields holds significant promise for advancing the diagnosis and treatment of this formidable malignancy.

An SNP Marker Predicts Colorectal Cancer Outcomes with 5-Fluorouracil-Based Adjuvant Chemotherapy Post-Resection

Colorectal cancer (CRC) is a global health concern, necessitating adjuvant chemotherapy post-curative surgery to mitigate recurrence and enhance survival, particularly in intermediate-stage patients. However, existing therapeutic disparities highlight the need for biomarker-guided adjuvant chemotherapy to achieve better CRC inhibition. This study explores the molecular mechanisms underlying the inhibition of CRC through a genome-wide association study (GWAS) focused on 5-fluorouracil (5-FU)-based adjuvant therapy in intermediate-stage CRC patients, a domain previously unexplored. We retrospectively included 226 intermediate-stage CRC patients undergoing surgical resection followed by 5-FU-based adjuvant chemotherapy. The exploration cohort comprised 31 patients, and the validation cohort included 195 individuals. Genotyping was carried out using either Axiom Genome-Wide TWB 2.0 Array Plate-based or polymerase chain reaction-based methods on genomic DNA derived from collected tissue samples. Statistical analyses involved descriptive statistics, Kaplan-Meier analyses, and Cox proportional hazard analyses. From the GWAS, potential genetic predictors, GALNT14-rs62139523 and DNMBP-rs10786578 genotypes, of 5-FU-based adjuvant therapy following surgery in intermediate-stage CRC patients were identified. Validation in a larger cohort of 195 patients emphasized the predictive significance of GALNT14-rs62139523 genotypes, especially the "A/G" genotype, for improved overall and progression-free survival. This predictive association remained robust across various subgroups, with exceptions for specific demographic and clinical parameters such as age < 58 years old, CEA ≤ 2.5 ng/mL, tumor diameter > 44.0 mm, and tumor-free margin ≥ 50 mm. This study identifies that the GALNT14-rs62139523 "A/G" genotype modulates therapeutic outcomes, establishing it as a promising biomarker for predicting favorable responses to 5-FU-based adjuvant chemotherapy in intermediate-stage CRC patients, although further investigations are needed to detail these mechanisms.

Role of Artificial Intelligence and Machine Learning in Prediction, Diagnosis, and Prognosis of Cancer

Cancer is one of the most devastating, fatal, dangerous, and unpredictable ailments. To reduce the risk of fatality in this disease, we need some ways to predict the disease, diagnose it faster and precisely, and predict the prognosis accurately. The incorporation of artificial intelligence (AI), machine learning (ML), and deep learning (DL) algorithms into the healthcare system has already proven to work wonders for patients. Artificial intelligence is a simulation of intelligence that uses data, rules, and information programmed in it to make predictions. The science of machine learning (ML) uses data to enhance performance in a variety of activities and tasks. A bigger family of machine learning techniques built on artificial neural networks and representation learning is deep learning (DL). To clarify, we require AI, ML, and DL to predict cancer risk, survival chances, cancer recurrence, cancer diagnosis, and cancer prognosis. All of these are required to improve patient's quality of life, increase their survival rates, decrease anxiety and fear to some extent, and make a proper personalized treatment plan for the suffering patient. The survival rates of people with diffuse large B-cell lymphoma (DLBCL) can be forecasted. Both solid and non-solid tumors can be diagnosed precisely with the help of AI and ML algorithms. The prognosis of the disease can also be forecasted with AI and its approaches like deep learning. This improvement in cancer care is a turning point in advanced healthcare and will deeply impact patient's life for good.

A Single-Center Retrospective Study to Compare the Efficacy and Safety of Modified FOLFIRINOX with S-1 as Adjuvant Chemotherapy in 71 Patients with Resected Pancreatic Carcinoma

BACKGROUND Studies are ongoing to determine the optimal adjuvant chemotherapy (ACT) for resected pancreatic carcinoma (PC). FOLFIRINOX is a chemotherapy regimen including oxaliplatin, irinotecan, leucovorin, and 5-fluorouracil (5-FU). S-1 is a fluoropyrimidine derivative widely used as ACT for gastrointestinal malignancy. This single-center retrospective study aimed to compare the efficacy and safety of modified FOLFIRINOX (mFOLFIRINOX) with S-1 as ACT for resected PC. MATERIAL AND METHODS A total of 71 patients with PC who accepted ACT after R0 resection between February 2016 and January 2019 were enrolled in this retrospective study. Among these patients, 34 received mFOLFIRINOX regimen chemotherapy (mFFX group), while 37 received S-1 monochemotherapy (S-1 group). The mFOLFIRINOX regimen included oxaliplatin 65 mg/m², leucovorin 400 mg/m², irinotecan 150 mg/m², 5-FU 400 mg/m², and continuous 5-FU 2400 mg/m² (for 46 h), in a 2-week schedule. The S-1 monochemotherapy (80-120 mg/day according to body surface area [BSA], in 2 divided doses for 2 week) was administrated every 3 weeks. We followed up these patients and analyzed the relapse-free survival (RFS), overall survival (OS), and chemotherapy-induced adverse events (AEs). RESULTS The mFFX group demonstrated a markedly higher 3-year RFS (P=0.0332) and OS (P=0.0346) than the S-1 group. Patients in the mFFX group experienced significantly more common and severe thrombocytopenia (P=0.0372), fatigue (P=0.0226), nausea/vomiting (P=0.0337), and diarrhea (P=0.0018). No chemotherapy-induced death was documented. CONCLUSIONS This retrospective study indicated that if dose adjustment and adverse events management are properly administrated, mFOLFIRINOX regimen chemotherapy could result in an improved survival compared with S-1 monochemotherapy for resected PC.

Risk factors and outcomes for patients with pancreatic cancer undergoing surgical exploration without resection due to metastatic disease: A national cohort study

BACKGROUND

Unresectable disease is sometimes diagnosed during surgery in patients with pancreatic ductal adenocarcinoma (PDAC). This study aimed to identify preoperative risk factors for metastatic disease diagnosed at surgical exploration and to investigate and compare survival in resected and non-resected patients.

METHODS

Patients were identified from the Swedish National Pancreatic and Periampullary Cancer Registry 2010-2018. Predictors of metastatic disease were evaluated with a multivariable logistic regression model, and survival was evaluated with Kaplan-Meier estimates and log-rank tests.

RESULTS

In total, 1938 patients with PDAC were scheduled for surgery. An unresectable situation was diagnosed intraoperatively in 399 patients (20.6%), including 234 (12.1%) with metastasized disease. Independent risk factors for metastasis were involuntary weight loss (OR = 1.72; 95% CI: 1.27-2.33) and elevated carbohydrate antigen 19-9 (CA19-9) (35-599 U/mL, OR = 1.79, 95% CI: 1.11-2.89; ≥ 600 U/mL, OR = 3.24, 95% CI: 2.04-5.17). Overall survival was lower among patients with metastasized disease than that among patients with a resectable tumor (P < 0.001).

CONCLUSIONS

Involuntary weight loss and an elevation of CA19-9 are preoperative risk factors for diagnosing metastasized disease during surgical exploration.

A Novel Immune-Related Prognostic Signature Predicting Survival in Patients with Pancreatic Adenocarcinoma

Pancreatic adenocarcinoma (PAAD) carries the lowest survival rate of all major organ cancers, which is of dismal prognosis and high mortality rate. Thus, the present study attempted to identify a few novel prognostic biomarkers and establish an immune-related prognostic signature which could predict the prognosis of PAAD. Four prognostic immune-related genes (IRGs) including S100A6, S100A10, S100A16, and SDC1 were screened by differentially expressed gene (DEG) identification and weighted gene coexpression network analysis (WGCNA). Subsequent analysis proved the high expression of these IRGs in PAAD tissues, suggested by TCGA-PAAD data, merged microarray-acquired dataset (MMD), GEPIA, and Oncomine webtool. By using MMD and TCGA-PAAD data, S100A6 (MMD: AUC = 0.897; TCGA: AUC = 0.843), S100A10 (MMD: AUC = 0.880; TCGA: AUC = 0.780), S100A16 (MMD: AUC = 0.878; TCGA: AUC = 0.838), and SDC1 (MMD: AUC = 0.885; TCGA: AUC = 0.812) exhibited excellent diagnostic efficiency for PAAD. By conducting connectivity map (CMap) analysis, we concluded that three molecule drugs (sulpiride, famotidine, and nalidixic acid) might have worked in the treatment of PAAD. Then, an immune-related prognostic index was constructed, which was validated as an independent prognostic factor for PAAD patients (P=0.004). We further constructed a nomogram by using this immune-related signature and age, the prognostic value of which was validated by using concordance index (C-index = 0.780) and area under curve (AUC = 0.909). Moreover, the immune-related prognostic signature was associated with response to anti-PD-1/L1 immunotherapy. To sum up, four IRGs were screened out and verified to be novel immune-related prognostic biomarkers in PAAD. Besides, sulpiride, famotidine, and nalidixic acid might be potential choices in the treatment of PAAD. An immune-related signature was established to show great potential for prognosis prediction for PAAD, independently, which might guide more effective immunotherapy strategies. A nomogram is further established by using this immune-related prognostic index, which might contribute to more effective prognosis prediction in PAAD patients.

Identification of DDX31 as a Potential Oncogene of Invasive Metastasis and Proliferation in PDAC

Background: Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest malignant tumors worldwide and has poor prognosis. DEAD box proteins31 (DDX31) participate in cellular processes involving RNA secondary structure changes. However, the functions of DDX31 in PDAC remain to be elucidated.

Methods: The key gene DDX31 was identified using a combination of a risk model and weighted gene co-expression network analysis (WGCNA) with R software. The biological functions of DDX31 in PDAC were investigated through bioinformatics analysis and in vitro experiments.

Results: Combining with WGCNA and risk model, DDX31 was identified as a potential factor of the invasive metastasis properties of PDAC, and its expression was closely related to the malignant differentiation of PDAC. The results of gene set enrichment analysis (GSEA) showed that DDX31 was correlated with cell invasive metastasis and proliferation by activating MAPK signaling pathway. The inhibition of DDX31 inhibited the invasion and migration of PDAC cells. Survival analysis showed that DDX31 expression was negatively associated with the poor prognosis in patients with PDAC.

Interpretation:DDX31 may be a potential factor for PDAC. The inhibition of DDX31 may be a potential way to treat PDAC.

Prognostic Factors and Effect of Adjuvant Chemoradiation Following Chemotherapy in Resected Pancreatic Cancer Patients With Lymph Node Metastasis or R1 Resection

Pancreatic ductal adenocarcinoma (PDAC) is a lethal disease with a poor prognosis. In resectable PDAC, the recurrence rate is still high even when surgery and adjuvant chemotherapy (CT) are applied. Regional lymph node metastasis and positive margins are associated with higher recurrence risk and worse survival. Adjuvant radiotherapy has been explored, but its efficacy remains controversial. In recent years, some characteristics have been reported to stratify patients who may benefit from adjuvant chemoradiation (CRT), such as lymph node metastasis and margin status. Adjuvant chemotherapy followed by chemoradiation (CT-CRT) was also proposed. A total of 266 patients with resectable PDAC who have lymph node metastasis or R1 resection after surgery were enrolled. In multivariate Cox regression analyses, pancreatic body or tail tumor location (HR 0.433, p<0.0001, compared with pancreatic head) and adjuvant CT predicted a better survival, while there were no significant differences among the different CT regimens. Higher T stage indicated poor survival (stage I: reference; stage II: HR 2.178, p=0.014; stage III: HR 3.581, p=0.001). Propensity score matching was applied in 122 patients to explore the role of CRT. A cohort of 51 patients (31 and 20 patients in the CT and CT-CRT groups, respectively) was generated by matching. Further analyses revealed adjuvant CT-CRT was associated with prolonged survival compared with CT alone (HR 0.284, p=0.014) and less frequent local recurrences (56.5% vs. 21.4% in the CT and CT-CRT group, respectively). However, no significant differences in disease-free survival among these two groups were observed.

Impact of Resection Margin Status in Patients with Pancreatic Cancer: a National Cohort Study

AIM

To assess the predictors and influence of resection margins and the role of neoadjuvant and adjuvant therapy on survival for a national cohort of patients with resected pancreatic cancer.

METHODS

Using the National Cancer Data Base between 2004 and 2016, 56,532 patients were identified who underwent surgical resection for pancreatic adenocarcinoma. Univariate and multivariate models were employed to identify factors predicting R0/R1 resection and assess the impact on survival.

RESULTS

In total, 48,367 (85.6%) patients were found to have negative margins (R0) compared to 8165 (14.4%) who had microscopic residual tumor (R1). Factors predicting positive margin on univariate analysis included male gender, Medicare, advanced stage, moderately or poorly differentiated tumor, lymphovascular invasion, and tumors > 2 cm. Factors predicting R0 resection included receipt of neoadjuvant therapy and treatment at an Academic/Research Center. Following adjustment for other factors, margin status remained an independent predictor for overall survival (HR: 1.24; 95% CI 1.22-1.27, p < 0.001) (1-, 3-, and 5-year overall survival rates (R0: 77%, 37%, and 25% vs R1: 62%, 19%, and 10%).

CONCLUSIONS

A positive margin predicts a poorer survival than R0 resections regardless of stage and receipt of adjuvant therapy. Several modifiable factors significantly predict the likelihood of R0 resection including neoadjuvant treatment and treatment at Academic/Research Programs. Knowledge about these factors can help guide patient management by offering neoadjuvant treatment modalities at Academic as well as Community hospitals.

The molecular biology of pancreatic adenocarcinoma: translational challenges and clinical perspectives

Pancreatic cancer is an increasingly common cause of cancer mortality with a tight correspondence between disease mortality and incidence. Furthermore, it is usually diagnosed at an advanced stage with a very dismal prognosis. Due to the high heterogeneity, metabolic reprogramming, and dense stromal environment associated with pancreatic cancer, patients benefit little from current conventional therapy. Recent insight into the biology and genetics of pancreatic cancer has supported its molecular classification, thus expanding clinical therapeutic options. In this review, we summarize how the biological features of pancreatic cancer and its metabolic reprogramming as well as the tumor microenvironment regulate its development and progression. We further discuss potential biomarkers for pancreatic cancer diagnosis, prediction, and surveillance based on novel liquid biopsies. We also outline recent advances in defining pancreatic cancer subtypes and subtype-specific therapeutic responses and current preclinical therapeutic models. Finally, we discuss prospects and challenges in the clinical development of pancreatic cancer therapeutics.

Pancreatic Cancer (PDAC): Introduction of Evidence-Based Complementary Measures into Integrative Clinical Management

The most common form of pancreatic cancer is pancreatic ductal adenocarcinoma (PDAC), which comprises some 85% of all cases. Currently, this is the fourth highest cause of cancer mortality worldwide and its incidence is rising steeply. Commonly applied clinical therapies offer limited chance of a lasting cure and the five-year survival rate is one of the lowest of the commonly occurring cancers. This review cultivates the hypothesis that the best management of PDAC would be possible by integrating 'western' clinical medicine with evidence-based complementary measures. Protecting the liver, where PDAC frequently first spreads, is also given some consideration. Overall, the complementary measures are divided into three groups: dietary factors, nutraceutical agents and lifestyle. In turn, dietary factors are considered as general conditioners, multi-factorial foodstuffs and specific compounds. The general conditioners are alkalinity, low-glycemic index and low-cholesterol. The multi-factorial foodstuffs comprise red meat, fish, fruit/vegetables, dairy, honey and coffee. The available evidence for the beneficial effects of the specific dietary and nutraceutical agents was considered at four levels (in order of prominence): clinical trials, meta-analyses, in vivo tests and in vitro studies. Thus, 9 specific agents were identified (6 dietary and 3 nutraceutical) as acceptable for integration with gemcitabine chemotherapy, the first-line treatment for pancreatic cancer. The specific dietary agents were the following: Vitamins A, C, D and E, genistein and curcumin. As nutraceutical compounds, propolis, triptolide and cannabidiol were accepted. The 9 complementary agents were sub-grouped into two with reference to the main 'hallmarks of cancer'. Lifestyle factors covered obesity, diabetes, smoking, alcohol and exercise. An integrative treatment regimen was devised for the management of PDAC patients. This involved combining first-line gemcitabine chemotherapy with the two sub-groups of complementary agents alternately in weekly cycles. The review concludes that integrated management currently offers the best patient outcome. Opportunities to be investigated in the future include emerging modalities, precision medicine, the nerve input to tumors and, importantly, clinical trials.