Proliferation kinetics and prognosis in gastric cancer after resection

[Gastric cancer and adenocarcinoma of the esophagogastric junction: principles of neoadjuvant therapy]

According to the current European and German S3 guidelines, neoadjuvant chemotherapy is now an integral part of the treatment of locally advanced gastric cancer and adenocarcinoma of the esophagogastric junction. Neoadjuvant therapy seeks to achieve downsizing of the primary tumor, lowering of the T and N categories and eradication of micrometastases. As the indications for neoadjuvant treatment are based on pretherapeutic information alone, a sophisticated clinical staging plays a central role. Despite all progress made in the field of diagnostic work-up, clinical staging often fails. Despite this fact, controlled randomized trials showed that neoadjuvant chemotherapy enhances the rate of curative (R0) resections and reduces the likelihood of systemic relapse. Overall, survival can be improved by neoadjuvant chemotherapy. The current research is focused on the molecular prediction of response and early response monitoring with functional imaging. New targeted drugs are being integrated into the peri-operative treatment.

Genomic and genetic alterations influence the progression of gastric cancer

Gastric cancer is one of the leading causes of cancer-related deaths worldwide, although the incidence has gradually decreased in many Western countries. Two main gastric cancer histotypes, intestinal and diffuse, are recognised. Although most of the described genetic alterations have been observed in both types, different genetic pathways have been hypothesized. Genetic and epigenetic events, including 1q loss of heterozygosity (LOH), microsatellite instability and hypermethylation, have mostly been reported in intestinal-type gastric carcinoma and its precursor lesions, whereas 17p LOH, mutation or loss of E-cadherin are more often implicated in the development of diffuse-type gastric cancer. In this review, we summarize the sometimes contradictory findings regarding those markers which influence the progression of gastric adenocarcinoma.

Oncogenic pathway combinations predict clinical prognosis in gastric cancer

Many solid cancers are known to exhibit a high degree of heterogeneity in their deregulation of different oncogenic pathways. We sought to identify major oncogenic pathways in gastric cancer (GC) with significant relationships to patient survival. Using gene expression signatures, we devised an in silico strategy to map patterns of oncogenic pathway activation in 301 primary gastric cancers, the second highest cause of global cancer mortality. We identified three oncogenic pathways (proliferation/stem cell, NF-kappaB, and Wnt/beta-catenin) deregulated in the majority (>70%) of gastric cancers. We functionally validated these pathway predictions in a panel of gastric cancer cell lines. Patient stratification by oncogenic pathway combinations showed reproducible and significant survival differences in multiple cohorts, suggesting that pathway interactions may play an important role in influencing disease behavior. Individual GCs can be successfully taxonomized by oncogenic pathway activity into biologically and clinically relevant subgroups. Predicting pathway activity by expression signatures thus permits the study of multiple cancer-related pathways interacting simultaneously in primary cancers, at a scale not currently achievable by other platforms.

Oncogenic pathway combinations predict clinical prognosis in gastric cancer

Many solid cancers are known to exhibit a high degree of heterogeneity in their deregulation of different oncogenic pathways. We sought to identify major oncogenic pathways in gastric cancer (GC) with significant relationships to patient survival. Using gene expression signatures, we devised an in silico strategy to map patterns of oncogenic pathway activation in 301 primary gastric cancers, the second highest cause of global cancer mortality. We identified three oncogenic pathways (proliferation/stem cell, NF-κB, and Wnt/β-catenin) deregulated in the majority (>70%) of gastric cancers. We functionally validated these pathway predictions in a panel of gastric cancer cell lines. Patient stratification by oncogenic pathway combinations showed reproducible and significant survival differences in multiple cohorts, suggesting that pathway interactions may play an important role in influencing disease behavior. Individual GCs can be successfully taxonomized by oncogenic pathway activity into biologically and clinically relevant subgroups. Predicting pathway activity by expression signatures thus permits the study of multiple cancer-related pathways interacting simultaneously in primary cancers, at a scale not currently achievable by other platforms.

Gastric cancer is the second leading cause of global cancer mortality. With current treatments, less than a quarter of patients survive longer than five years after surgery. Individual gastric cancers are highly disparate in their cellular characteristics and responses to standard chemotherapeutic drugs, making gastric cancer a complex disease. Pathway based approaches, rather than single gene studies, may help to unravel this complexity. Here, we make use of a computational approach to identify connections between molecular pathways and cancer profiles. In a large scale study of more than 300 patients, we identified subgroups of gastric cancers distinguishable by their patterns of driving molecular pathways. We show that these identified subgroups are clinically relevant in predicting survival duration and may prove useful in guiding the choice of targeted therapies designed to interfere with these molecular pathways. We also identified specific gastric cancer cell lines mirroring these pathway subgroups, which should facilitate the pre-clinical assessment of responses to targeted therapies in each subgroup.

Gastric cancer

Gastric cancer is one of the most common cancers and one of the most frequent causes of cancer-related deaths. The incidence, diagnostic studies, and therapeutic options have undergone important changes in the last decades, but the prognosis for gastric cancer patients remains poor, especially in more advanced stages. Surgery is the mainstay of treatment of this disease, even if it is associated with a high rate of locoregional and distant recurrence. There is ongoing debate regarding the role of adjuvant treatment In advanced disease, palliation of symptoms, rather than cure, is the primary goal of patient management. Several combination therapies have been developed and have been examined in phase III trials; however, in most cases, they have failed to demonstrate a survival advantage over the reference arm. This review summarizes the most important recommendations for the management of patients with gastric cancer.

A Markov model approach shows a large variation in the length of S phase in MCF-7 breast cancer cells

BACKGROUND

The potential doubling time of a tumor has been suggested to be a measurement of tumor aggressiveness; therefore, it is of interest to find reliable methods to estimate this time. Because of variability in length of the various cell cycle phases, stochastic modeling of the cell cycle might be a suitable approach.

METHODS

The relative movement curve and the DNA synthesis time were estimated by using local polynomial regression methods. Further, the rate of nucleotide incorporation was estimated by using a Markov pure birth process with one absorbing state to model the progression of the DNA distribution through S phase.

RESULTS

An estimate of the DNA synthesis time, with confidence intervals, was obtained from the relative movement curve. The Markov approach provided an estimate of the distribution of the time to complete S phase given the initial distribution. Using the Markov approach we also made an estimate of the mean number of active replicons during S phase.

CONCLUSIONS

A Markov pure birth process has shown to be useful to model the progression of cells through S phase and to increase knowledge about the variability in the length of S phase and a large variation is shown.

Prognostic factors and pathology of advanced gastric cancer

AIM

To investigate the prognostic factors and the relationship between clinicopathologic parameters and biological properties in advanced gastric cancer.

METHODS

In tumor samples from 61 primary advanced gastric cancer patients with curative resection, following parameters of sex, age, tumor size, grade of differentiation, depth of invasion, lymph node metastasis, lymphatics invasion and TNM stage were evaluated. In addition, DCs infiltration, PCNA-LI and AI were examined by TUNEL (terminal deoxynucleotidyl transferase-mediated deoxyuridine triphosphate biotin nick end labeling) or immunohistochemical methods. The prognostic impact of these parameters was analyzed by univariate and multivariate survival analysis.

RESULTS

PCNA-LI, AI and DCs infiltration were significantly correlated to lymph node metastasis, TNM stage and differentiation grade. Univariate Kaplan-Meier analysis showed that depth of invasion, lymph node metastasis, TNM stage, PCNA-LI and infiltration of DCs had prognostic significances for survial (Log-rank test, P <0.05), while multivariate Cox analysis indicated that only tumor size (RR=2.328) and TNM stage (RR =5.251) were independent prognostic factors for survival.

CONCLUSION

In advanced gastric cancer, UICC TNM stage and tumor size are independent prognostic factors, and infiltration of DCs and proliferation of cancer cells play a role in the prognostic outcome.

Inter-laboratory and inter-observer reproducibility of immunohistochemical assessment of the Ki-67 labelling index in a large multi-centre trial

Proliferative activity of tumour cells, as assessed by the Ki-67 labelling index, has been suggested as a potential prognostic indicator in many neoplastic diseases. Meaningful application of the immunohistochemically determined tumour cell growth fraction in clinical decision-making requires information about its inter-laboratory reproducibility. To assess the reproducibility of Ki-67 determined growth fraction, a multi-centre immunohistochemical trial was performed with 172 participating laboratories, each testing 30 different tissue samples. Evaluating 5160 Ki-67 labelling indices with a newly developed tissue microarray, good inter-observer reproducibility but high inter-laboratory variability was found. Reassessment of all stainings revealed considerable inter-laboratory differences in the intensity and frequency of labelled nuclei, suggesting that antigen retrieval or staining techniques are predominantly responsible for the inter-laboratory variability found in this trial. Consequently, cut-off levels for Ki-67, suggested to distinguish prognostic subgroups in tumours, appear to have limited reproducibility in a multi-centre approach. It is concluded that there is a need to standardize the immunohistochemical determination of the Ki-67 labelling index when it is used as a prognostic indicator in surgical pathology.