Analysis of a gene panel for targeted sequencing of colorectal cancer samples

Patterns of Somatic Variants in Colorectal Adenoma and Carcinoma Tissue and Matched Plasma Samples from the Hungarian Oncogenome Program

Analysis of circulating cell-free DNA (cfDNA) of colorectal adenoma (AD) and cancer (CRC) patients provides a minimally invasive approach that is able to explore genetic alterations. It is unknown whether there are specific genetic variants that could explain the high prevalence of CRC in Hungary. Whole-exome sequencing (WES) was performed on colon tissues (27 AD, 51 CRC) and matched cfDNAs (17 AD, 33 CRC); furthermore, targeted panel sequencing was performed on a subset of cfDNA samples. The most frequently mutated genes were APC, KRAS, and FBN3 in AD, while APC, TP53, TTN, and KRAS were the most frequently mutated in CRC tissue. Variants in KRAS codons 12 (AD: 8/27, CRC: 11/51 (0.216)) and 13 (CRC: 3/51 (0.06)) were the most frequent in our sample set, with G12V (5/27) dominance in ADs and G12D (5/51 (0.098)) in CRCs. In terms of the cfDNA WES results, tumor somatic variants were found in 6/33 of CRC cases. Panel sequencing revealed somatic variants in 8 out of the 12 enrolled patients, identifying 12/20 tumor somatic variants falling on its targeted regions, while WES recovered only 20% in the respective regions in cfDNA of the same patients. In liquid biopsy analyses, WES is less efficient compared to the targeted panel sequencing with a higher coverage depth that can hold a relevant clinical potential to be applied in everyday practice in the future.

Synergistic cytotoxicity of perifosine and ABT-737 to colon cancer cells

An acidic environment and hypoxia within the tumour are hallmarks of cancer that contribute to cell resistance to therapy. Deregulation of the PI3K/Akt pathway is common in colon cancer. Numerous Akt-targeted therapies are being developed, the activity of Akt-inhibitors is, however, strongly pH-dependent. Combination therapy thus represents an opportunity to increase their efficacy. In this study, the cytotoxicity of the Akt inhibitor perifosine and the Bcl-2/Bcl-xL inhibitor ABT-737 was tested in colon cancer HT-29 and HCT-116 cells cultured in monolayer or in the form of spheroids. The efficacy of single drugs and their combination was analysed in different tumour-specific environments including acidosis and hypoxia using a series of viability assays. Changes in protein content and distribution were determined by immunoblotting and a "peeling analysis" of immunohistochemical signals. While the cytotoxicity of single agents was influenced by the tumour-specific microenvironment, perifosine and ABT-737 in combination synergistically induced apoptosis in cells cultured in both 2D and 3D independently on pH and oxygen level. Thus, the combined therapy of perifosine and ABT-737 could be considered as a potential treatment strategy for colon cancer.

ERH Interacts With EIF2α and Regulates the EIF2α/ATF4/CHOP Pathway in Bladder Cancer Cells

Background

There is a lack of research on the molecular interaction of the enhancers of rudimentary homolog (ERH) in bladder cancer (BC) cells. This study aimed to determine the interacting proteins of ERH in human T24 cells.

Methods

First, the ERH gene was overexpressed in human T24 cells. Coimmunoprecipitation (co-IP) and shotgun mass spectrometry (MS) analyses were performed to obtain a list of proteins that interact with ERH. Subsequently, bioinformatic analyses with Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and protein–protein interaction (PPI) studies were performed to analyze the ERH-interactive protein list (ERH-IPL). Then, we selected one of the interacting proteins, EIF2α for verification. An immunofluorescence colocalization assay was performed to validate the co-expression of the selected protein, and the binding sites of the two proteins were predicted by ZDOCK technology. Finally, PCR analysis on the downstream molecules of the interacting protein was performed for verification.

Results

ERH protein was successfully overexpressed in human T24 cells. We obtained a list of 205 proteins that might directly or indirectly interact with the ERH protein by mass spectrometric analysis. The bioinformatic analysis showed that ERH-interacting proteins were related to “ribonucleoprotein complex”, “ATPase activity”, “nuclear speck”, and “translation factor activity, RNA binding”. We further identified one of the key genes, EIF2S1, and confirmed that the corresponding protein EIF2α is co-expressed and may bind with ERH in human T24 cells. The mRNA levels of molecules ATF4 and CHOP were found to be upregulated by ERH.

Conclusion

ERH protein affects “ribonucleoprotein complex”, “ATPase activity”, “nuclear speck”, and “translation factor activity, RNA binding”. The ERH protein can interact with EIF2α and regulate the EIF2α-ATF4/CHOP signaling pathway in human T24 cells.

Ornithine decarboxylase (ODC1) gene variant (rs2302615) is associated with gastric cancer independently of Helicobacter pylori CagA serostatus

The primary cause of gastric cancer is chronic infection with Helicobacter pylori (H. pylori), particularly the high-risk genotype cagA, and risk modification by human genetic variants. We studied 94 variants in 54 genes for association with gastric cancer, including rs2302615 in ornithine decarboxylase (ODC1), which may affect response to chemoprevention with the ODC inhibitor, eflornithine (difluoromethylornithine; DFMO). Our population-based, case-control study included 1366 individuals (664 gastric cancer cases and 702 controls) from Western Honduras, a high incidence region of Latin America. CagA seropositivity was strongly associated with cancer (OR = 3.6; 95% CI: 2.6, 5.1). The ODC1 variant rs2302615 was associated with gastric cancer (OR = 1.36; p = 0.018) in a model adjusted for age, sex, and CagA serostatus. Two additional single nucleotide polymorphisms (SNPs) in CASP1 (rs530537) and TLR4 (rs1927914) genes were also associated with gastric cancer in univariate models as well as models adjusted for age, sex, and CagA serostatus. The ODC1 SNP association with gastric cancer was stronger in individuals who carried the TT genotype at the associating TLR4 polymorphism, rs1927914 (OR = 1.77; p = 1.85 × 10^-3). In conclusion, the ODC1 variant, rs2302615, is associated with gastric cancer and supports chemoprevention trials with DFMO, particularly in individuals homozygous for the T allele at rs1927914.

Emerging trends in colorectal cancer: Dysregulated signaling pathways (Review)

Colorectal cancer (CRC) is the third most frequently detected type of cancer, and the second most common cause of cancer‑related mortality globally. The American Cancer Society predicted that approximately 147,950 individuals would be diagnosed with CRC, out of which 53,200 individuals would succumb to the disease in the USA alone in 2020. CRC‑related mortality ranks third among both males and females in the USA. CRC arises from 3 major pathways: i) The adenoma‑carcinoma sequence; ii) serrated pathway; and iii) the inflammatory pathway. The majority of cases of CRC are sporadic and result from risk factors, such as a sedentary lifestyle, obesity, processed diets, alcohol consumption and smoking. CRC is also a common preventable cancer. With widespread CRC screening, the incidence and mortality from CRC have decreased in developed countries. However, over the past few decades, CRC cases and mortality have been on the rise in young adults (age, <50 years). In addition, CRC cases are increasing in developing countries with a low gross domestic product (GDP) due to lifestyle changes. CRC is an etiologically heterogeneous disease classified by tumor location and alterations in global gene expression. Accumulating genetic and epigenetic perturbations and aberrations over time in tumor suppressor genes, oncogenes and DNA mismatch repair genes could be a precursor to the onset of colorectal cancer. CRC can be divided as sporadic, familial, and inherited depending on the origin of the mutation. Germline mutations in APC and MLH1 have been proven to play an etiological role, resulting in the predisposition of individuals to CRC. Genetic alterations cause the dysregulation of signaling pathways leading to drug resistance, the inhibition of apoptosis and the induction of proliferation, invasion and migration, resulting in CRC development and metastasis. Timely detection and effective precision therapies based on the present knowledge of CRC is essential for successful treatment and patient survival. The present review presents the CRC incidence, risk factors, dysregulated signaling pathways and targeted therapies.

Pharmacogenomics to Predict Tumor Therapy Response: A Focus on ATP-Binding Cassette Transporters and Cytochromes P450

Pharmacogenomics is an evolving tool of precision medicine. Recently, due to the introduction of next-generation sequencing and projects generating "Big Data", a plethora of new genetic variants in pharmacogenes have been discovered. Cancer resistance is a major complication often preventing successful anticancer treatments. Pharmacogenomics of both somatic mutations in tumor cells and germline variants may help optimize targeted treatments and improve the response to conventional oncological therapy. In addition, integrative approaches combining copy number variations and long noncoding RNA profiling with germline and somatic variations seem to be a promising approach as well. In pharmacology, expression and enzyme activity are traditionally the more studied aspects of ATP-binding cassette transporters and cytochromes P450. In this review, we briefly introduce the field of pharmacogenomics and the advancements driven by next-generation sequencing and outline the possible roles of genetic variation in the two large pharmacogene superfamilies. Although the evidence needs further substantiation, somatic and copy number variants as well as rare variants and common polymorphisms in these genes could all affect response to cancer therapy. Regulation by long noncoding RNAs has also been shown to play a role. However, in all these areas, more comprehensive studies on larger sets of patients are needed.

Artificial intelligence (AI) and big data in cancer and precision oncology

Artificial intelligence (AI) and machine learning have significantly influenced many facets of the healthcare sector. Advancement in technology has paved the way for analysis of big datasets in a cost- and time-effective manner. Clinical oncology and research are reaping the benefits of AI. The burden of cancer is a global phenomenon. Efforts to reduce mortality rates requires early diagnosis for effective therapeutic interventions. However, metastatic and recurrent cancers evolve and acquire drug resistance. It is imperative to detect novel biomarkers that induce drug resistance and identify therapeutic targets to enhance treatment regimes. The introduction of the next generation sequencing (NGS) platforms address these demands, has revolutionised the future of precision oncology. NGS offers several clinical applications that are important for risk predictor, early detection of disease, diagnosis by sequencing and medical imaging, accurate prognosis, biomarker identification and identification of therapeutic targets for novel drug discovery. NGS generates large datasets that demand specialised bioinformatics resources to analyse the data that is relevant and clinically significant. Through these applications of AI, cancer diagnostics and prognostic prediction are enhanced with NGS and medical imaging that delivers high resolution images. Regardless of the improvements in technology, AI has some challenges and limitations, and the clinical application of NGS remains to be validated. By continuing to enhance the progression of innovation and technology, the future of AI and precision oncology show great promise.