Association between gene expression profiles and clinical outcome of pemetrexed-based treatment in patients with advanced non-squamous non-small cell lung cancer: exploratory results from a phase II study

Role of Microbiota-Derived Metabolites in Prostate Cancer Inflammation and Progression

Prostate cancer (PCa) is the most commonly detected malignancy in men worldwide. PCa is a slow-growing cancer with the absence of symptoms at early stages. The pathogenesis has not been entirely understood including the key risk factors related to PCa development like diet and microbiota derived metabolites. Microbiota may influence the host's immunological responses, inflammatory responses, and metabolic pathways, which may be crucial for the development and metastasis. Similarly, short-chain fatty acids, methylamines, hippurate, bile acids, and other metabolites generated by microbiota may have potential roles in cancer inflammation and progression of cancer. Most studies have focused on the role of metabolites and their pathways involved in chronic inflammation, tumor initiation, proliferation, and progression. In summary, the review discusses the role of microbiota and microbial-derived metabolite-built strategies in inflammation and progression of the PCa.

Exploring Prognostic Gene Factors in Breast Cancer via Machine Learning

Breast cancer remains the most prevalent cancer in women. To date, its underlying molecular mechanisms have not been fully uncovered. The determination of gene factors is important to improve our understanding on breast cancer, which can correlate the specific gene expression and tumor staging. However, the knowledge in this regard is still far from complete. Thus, this study aimed to explore these knowledge gaps by analyzing existing gene expression profile data from 3149 breast cancer samples, where each sample was represented by the expression of 19,644 genes and classified into Nottingham histological grade (NHG) classes (Grade 1, 2, and 3). To this end, a machine learning-based framework was designed. First, the profile data were analyzed by using seven feature ranking algorithms to evaluate the importance of features (genes). Seven feature lists were generated, each of which sorted features in accordance with feature importance evaluated from a special aspect. Then, the incremental feature selection method was applied to each list to determine essential features for classification and building efficient classifiers. Consequently, overlapping genes, such as AURKA, CBX2, and MYBL2, were deemed as potentially related to breast cancer malignancy and prognosis, indicating that such genes were identified to be important by multiple feature ranking algorithms. In addition, the study formulated classification rules to reflect special gene expression patterns for three NHG classes. Some genes and rules were analyzed and supported by recent literature, providing new references for studying breast cancer.

Association of Antifolate Response Signature Status and Clinical Activity of Pemetrexed-Platinum Chemotherapy in Non-Small Cell Lung Cancer: The Piedmont Study

PURPOSE

The Piedmont study is a prospectively designed retrospective evaluation of a new 48-gene antifolate response signature (AF-PRS) in patients with locally advanced/metastatic nonsquamous (NS) non-small cell lung cancer (NSCLC) treated with pemetrexed-containing platinum doublet chemotherapy (PMX-PDC). The study tested the hypothesis that AF-PRS identifies patients with NS-NSCLC who have a higher likelihood of responding positively to PMX-PDC. The goal was to gather clinical evidence supporting AF-PRS as a potential diagnostic test.

EXPERIMENTAL DESIGN

Residual pretreatment FFPE tumor samples and clinical data were analyzed from 105 patients treated with first-line (1L) PMX-PDC. Ninety-five patients had sufficient RNA sequencing (RNA-seq) data quality and clinical annotation for inclusion in the analysis. Associations between AF-PRS status and associate genes and outcome measures including progression-free survival (PFS) and clinical response were evaluated.

RESULTS

Overall, 53% of patients were AF-PRS(+), which was associated with extended PFS, but not overall survival, versus AF-PRS(-) (16.6 months vs. 6.6 months; P = 0.025). In patients who were stage I to III patients at the time of treatment, PFS was further extended in AF-PRS(+) versus AF-PRS(-) (36.2 months vs. 9.3 months; P = 0.03). Complete response (CR) to therapy was noted in 14 of 95 patients. AF-PRS(+) preferentially selected a majority (79%) of CRs, which were evenly split between patients stage I to III (six of seven) and stage IV (five of seven) at the time of treatment.

CONCLUSIONS

AF-PRS identified a significant population of patients with extended PFS and/or clinical response following PMX-PDC treatment. AF-PRS may be a useful diagnostic test for patients indicated for systemic chemotherapy, especially when determining the optimal PDC regimen for locally advanced disease.

Exonuclease 1 genetic variant is associated with clinical outcomes of pemetrexed chemotherapy in lung adenocarcinoma

Pemetrexed is an anti-folate agent which is one of the most frequently used chemotherapy agents for non-squamous non-small cell lung cancer (NSCLC) patients. However, clinical response to pemetrexed chemotherapy and survival outcome of patients varies significantly. We evaluated whether the genetic variants in miRNA target sites may affect the treatment outcome of pemetrexed chemotherapy in lung adenocarcinoma patients. One hundred SNPs in miRNA binding regions in cancer-related genes were obtained from the crosslinking, ligation, and sequencing of hybrids (CLASH) and CancerGenes database, and the associations with the response to pemetrexed chemotherapy and survival outcomes were investigated in 314 lung adenocarcinoma patients. Two polymorphisms, EXO1 rs1047840G>A and CAMKK2 rs1653586G>T, were significantly associated with worse chemotherapy response (adjusted odds ratio [aOR] = 0.41, 95% CI = 0.24-0.68, P = 0.001, under dominant model; and aOR = 0.33, 95% CI = 0.16-0.67, P = 0.002, under dominant model, respectively) and worse OS (adjusted hazard ratio [aHR] = 1.34, 95% CI = 1.01-1.77, P = 0.04, under dominant model; and aHR = 1.50, 95% CI = 1.06-2.13, P = 0.02, under dominant model, respectively) in multivariate analyses. Significantly increased luciferase activity was noted in EXO1 rs1047840 A allele compared to G allele. In conclusion, two SNPs in miRNA binding sites, especially EXO1 rs1047840G>A, were associated with the chemotherapy response and survival outcome in lung adenocarcinoma patients treated with pemetrexed.

Integrating Patient-Specific Information into Logic Models of Complex Diseases: Application to Acute Myeloid Leukemia

High throughput technologies such as deep sequencing and proteomics are increasingly becoming mainstream in clinical practice and support diagnosis and patient stratification. Developing computational models that recapitulate cell physiology and its perturbations in disease is a required step to help with the interpretation of results of high content experiments and to devise personalized treatments. As complete cell-models are difficult to achieve, given limited experimental information and insurmountable computational problems, approximate approaches should be considered. We present here a general approach to modeling complex diseases by embedding patient-specific genomics data into actionable logic models that take into account prior knowledge. We apply the strategy to acute myeloid leukemia (AML) and assemble a network of logical relationships linking most of the genes that are found frequently mutated in AML patients. We derive Boolean models from this network and we show that by priming the model with genomic data we can infer relevant patient-specific clinical features. Here we propose that the integration of literature-derived causal networks with patient-specific data should be explored to help bedside decisions.

Up-regulation of lysophosphatidylcholine acyltransferase 1 (LPCAT1) is linked to poor prognosis in breast cancer

Dysregulation of lipid metabolism is common in cancer. Lysophosphatidylcholine acyltransferase 1 (LPCAT1) has been implicated with various cancer types. Here we analyzed by immunohistochemistry its expression in 2,197 breast cancers. LPCAT1 staining was found in 97.8% of 1,774 interpretable tumors, including 48.1% with weak, 28.7% with moderate, and 14.4% with strong expression. The frequency of LPCAT1 positivity depended on the histological tumor type. Moderate or strong LPCAT1 positivity was more common in cancers of no special type (NST) (46.2%) than in lobular carcinomas (25.9%; p<0.0001). Strong LPCAT1 was associated with BRE grade, tumor cell proliferation and overall survival in all cancers and in the subgroup of NST cancers (p<0.0001, each). In the subset of NST cancers the prognostic effect of LPCAT1 expression was independent of pT, and BRE grade (p<0.0001 each). A comparison with molecular features showed that LPCAT1 was strongly associated with estrogen receptor negativity (p<0.0001), progesterone receptor negativity (p<0,0001), amplification of HER2 (p<0.0001) and MYC (p=0.0066), as well as deletions of PTEN (p<0.0001) and CDKNA2 (p=0.0151). It is concluded that LPCAT1 overexpression is linked to adverse tumor features and poor prognosis in breast cancer. These data also highlight the important role of lipid metabolism in breast cancer biology.

Association between IL-1R2 polymorphisms and lung cancer risk in the Chinese Han population: A case-control study

BACKGROUND

Interleukin-1 receptor 2 (IL-1R2), as an anti-inflammatory cytokine, is involved in the pathogenesis and progression of lung cancer. However, the role of IL-1R2 polymorphisms in patients with lung cancer has yet to be fully elucidated.

METHODS

Six single-nucleotide polymorphisms (SNPs) in IL-1R2 were genotyped in 259 patients and 346 healthy controls. We used the chi-squared test, genetic model analysis, Haploview analysis, and multifactor dimensionality reduction (MDR) to evaluate the potential association between IL-1R2 polymorphisms and lung cancer susceptibility. Bioinformatics analyses were conducted to analyze the expression level of IL-1R2 and its association with the overall survival of lung cancer.

RESULTS

Our results found that rs3218977-GG was associated with a decreased risk of lung cancer (odds ratio [OR] = 0.39; 95% confidence interval [CI]: 0.17-0.87; p = 0.023), and rs2072472 had a significant risk-increasing effect in the dominant model (AG + GG vs. AA: OR = 1.54; 95% CI: 1.09-2.20; p = 0.015). The MDR model also revealed that rs2072472 is the most influential risk factor of lung cancer (testing accuracy = 0.543; cross-validation consistency = 10/10; p = 0.032). In addition, our results indicated that the IL-1R2 mRNA level was downregulated in lung cancer patients, whereas the high expression of IL-1R2 was related to a poor prognosis in lung cancer.

CONCLUSIONS

Our results suggest that genetic variants of IL-1R2 may play a role in lung cancer susceptibility. Further population and functional validations of our findings are warranted.

Differential transcriptional changes in human alveolar epithelial A549 cells exposed to airborne PM2.5 collected from Shanghai, China

Fine particulate matters (PM_2.5) are the core pollutants of haze episode, which pose a serious threat to the human health of developing countries. However, the mechanisms involved in PM_2.5-induced hazard influence are not to fully elucidated. In the present study, human lung epithelial cells (A549) were exposed to various concentrations of PM_2.5 samples collected from Shanghai, China. Illumina RNA-Seq method with transcriptome, Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were further employed to identify the detrimental effects of PM_2.5 on A549 cells in vitro. A total of 712 differentially expressed genes were obtained from global transcriptome profiling of A549 cells after PM_2.5 exposure. In addition, GO function enrichment analysis revealed that major differentially expressed genes (DEGs) involved in the biological process of the immune system and the response to the stress. KEGG pathway analysis further proposes that infectious disease, cancers, cardiovascular disease, and immune disease pathway were the key human disease events that occur in A549 cells under PM_2.5 stress. The data obtained here shed light on the related biological process and gene signaling pathways affected by PM_2.5 exposure. This study aids our understanding of the complicated mechanisms related to PM_2.5-induced health effects and is informative for the prevention and treatment of PM_2.5-induced systemic diseases.

Pemetrexed for advanced stage nonsquamous non-small cell lung cancer: latest evidence about its extended use and outcomes

Non-small cell lung cancer (NSCLC) is still the leading cause of cancer-related death, and the treatment of advanced NSCLC relies on systemic treatments. During the last decade, pemetrexed, an antifolate agent, gradually became a key component of the treatment for patients with advanced nonsquamous NSCLC. It has indeed been shown to be efficient for first-line, maintenance and second- or third-line treatment in this subgroup of NSCLC. Moreover, it is usually well tolerated, with few grade 3 and 4 toxicities. Several studies have tried to identify predictive biomarkers of pemetrexed efficacy. Due to pemetrexed's mechanism of action, thymidilate synthase expression predictive value was investigated but could not be demonstrated. Currently, more than 400 trials of pemetrexed for the treatment of nonsquamous NSCLC are ongoing.

Comparison of immunohistochemistry and mRNA in situ hybridization in detecting thyroid transcription factor-1 expression in non-small cell lung carcinomas tissue

Thyroid transcription factor-1 (TTF-1) reportedly possesses oncogenic and suppressive roles within the same tumor type and may play a dual function in the progression of lung cancer. Immunohistochemistry (IHC) and mRNA in situ hybridization (ISH) are commonly used methods for detecting protein or mRNA expression. The present study compared the concordance rate of the two methods in the evaluation of thyroid transcription factor-1 (TTF-1) expression in non-small cell lung carcinoma (NSCLC) using tissue microarray-based IHC and mRNA ISH. TTF-1 protein and mRNA expression levels were examined in 196 cases of NSCLC. The IHC and mRNA ISH agreement was 91.3% (179/196), and near-perfect agreement was observed between the two methods (κ-coefficient, 0.848). There was no significant difference between IHC and mRNA ISH, as analyzed by the McNemar-Bowker test (P=0.219). The present findings proved that IHC is comparable to mRNA ISH for evaluating TTF-1 expression in NSCLC. These two methods can be used to detect TTF-1 expression in future studies.